diff --git a/.gitattributes b/.gitattributes index 52373fe24473b1aa44333d318f578ae6bf04b49b..b0a9d8ca886cadd67aaa3db7741841f52224509d 100644 --- a/.gitattributes +++ b/.gitattributes @@ -34,3 +34,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text *.zst filter=lfs diff=lfs merge=lfs -text *tfevents* filter=lfs diff=lfs merge=lfs -text tokenizer.json filter=lfs diff=lfs merge=lfs -text +training_logs/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san_856553.out filter=lfs diff=lfs merge=lfs -text +training_logs/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san_856554.out filter=lfs diff=lfs merge=lfs -text diff --git a/training_logs/20260614_113537_metrics_job_856553.csv b/training_logs/20260614_113537_metrics_job_856553.csv new file mode 100644 index 0000000000000000000000000000000000000000..922572fc7ec249ef242844b5fb79abc6f5269663 --- /dev/null +++ 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mode 100644 index 0000000000000000000000000000000000000000..25dce41a187d6e6fb0a17c3d65c61f0540c6654a --- /dev/null +++ b/training_logs/20260614_113537_vllm_metrics_table.csv @@ -0,0 +1,18117 @@ +log_file,datetime_str,n_engines_reporting,unique_ips,total_prompt_throughput_tokens_per_sec,total_generation_throughput_tokens_per_sec,total_running_requests,total_waiting_requests,avg_prompt_throughput_per_engine,avg_generation_throughput_per_engine,avg_running_requests_per_engine,avg_waiting_requests_per_engine,avg_gpu_kv_cache_usage_pct,avg_prefix_cache_hit_rate_pct,min_running_requests,max_running_requests,min_generation_throughput,max_generation_throughput +job_856553,06-13 04:07:42,1,1,10.6,0.0,1,0,10.6,0.0,1.0,0.0,0.3,0.0,1,1,0.0,0.0 +job_856553,06-13 04:07:47,1,1,0.0,46.4,1,0,0.0,46.4,1.0,0.0,0.3,0.0,1,1,46.4,46.4 +job_856553,06-13 04:07:53,1,1,0.0,46.3,1,0,0.0,46.3,1.0,0.0,0.4,0.0,1,1,46.3,46.3 +job_856553,06-13 04:07:58,1,1,61.4,23.2,1,0,61.4,23.2,1.0,0.0,0.5,53.8,1,1,23.2,23.2 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11:55:02,1,1,161.5,369.6,10,0,161.5,369.6,10.0,0.0,40.0,95.0,10,10,369.6,369.6 +job_856553,06-13 11:55:07,1,1,136.1,410.4,10,0,136.1,410.4,10.0,0.0,43.1,95.0,10,10,410.4,410.4 +job_856553,06-13 11:55:12,1,1,142.6,324.7,7,0,142.6,324.7,7.0,0.0,15.7,95.1,7,7,324.7,324.7 +job_856553,06-13 11:55:17,1,1,311.5,407.1,9,0,311.5,407.1,9.0,0.0,19.8,95.1,9,9,407.1,407.1 +job_856553,06-13 11:55:22,1,1,92.2,353.4,7,0,92.2,353.4,7.0,0.0,16.5,95.1,7,7,353.4,353.4 +job_856553,06-13 11:55:27,1,1,127.6,344.4,7,0,127.6,344.4,7.0,0.0,14.0,95.1,7,7,344.4,344.4 +job_856553,06-13 11:55:32,1,1,0.0,496.7,12,0,0.0,496.7,12.0,0.0,44.6,95.0,12,12,496.7,496.7 +job_856553,06-13 11:55:37,1,1,0.0,445.7,11,0,0.0,445.7,11.0,0.0,36.5,95.0,11,11,445.7,445.7 +job_856553,06-13 11:55:42,1,1,98.7,459.6,11,0,98.7,459.6,11.0,0.0,36.9,95.0,11,11,459.6,459.6 +job_856553,06-13 11:55:47,1,1,33.8,396.7,9,0,33.8,396.7,9.0,0.0,25.2,95.0,9,9,396.7,396.7 +job_856553,06-13 11:55:52,1,1,0.0,356.8,8,0,0.0,356.8,8.0,0.0,21.7,95.0,8,8,356.8,356.8 +job_856553,06-13 11:55:57,1,1,222.7,345.0,10,0,222.7,345.0,10.0,0.0,27.9,95.0,10,10,345.0,345.0 +job_856553,06-13 11:56:02,1,1,158.5,393.7,10,0,158.5,393.7,10.0,0.0,30.5,95.0,10,10,393.7,393.7 +job_856553,06-13 11:56:07,1,1,63.8,386.9,10,0,63.8,386.9,10.0,0.0,31.9,95.0,10,10,386.9,386.9 +job_856553,06-13 11:56:12,1,1,84.8,398.2,11,0,84.8,398.2,11.0,0.0,36.7,95.0,11,11,398.2,398.2 +job_856553,06-13 11:56:17,1,1,138.7,450.2,11,0,138.7,450.2,11.0,0.0,39.7,95.0,11,11,450.2,450.2 +job_856553,06-13 11:56:22,1,1,0.0,422.2,10,0,0.0,422.2,10.0,0.0,36.1,95.0,10,10,422.2,422.2 +job_856553,06-13 11:56:27,1,1,166.5,436.1,11,0,166.5,436.1,11.0,0.0,40.8,95.0,11,11,436.1,436.1 +job_856553,06-13 11:56:32,1,1,21.6,572.0,16,0,21.6,572.0,16.0,0.0,64.2,95.9,16,16,572.0,572.0 +job_856553,06-13 11:56:37,1,1,117.1,217.8,6,0,117.1,217.8,6.0,0.0,23.0,95.0,6,6,217.8,217.8 +job_856553,06-13 11:56:42,1,1,68.1,586.8,16,0,68.1,586.8,16.0,0.0,60.4,95.9,16,16,586.8,586.8 +job_856553,06-13 11:56:47,1,1,200.5,599.0,16,0,200.5,599.0,16.0,0.0,64.9,95.9,16,16,599.0,599.0 +job_856553,06-13 11:56:52,1,1,18.0,566.8,15,0,18.0,566.8,15.0,0.0,62.0,95.9,15,15,566.8,566.8 +job_856553,06-13 11:56:57,1,1,273.9,567.8,17,0,273.9,567.8,17.0,0.0,73.7,95.9,17,17,567.8,567.8 +job_856553,06-13 11:57:02,1,1,11.4,368.7,7,0,11.4,368.7,7.0,0.0,22.3,94.3,7,7,368.7,368.7 +job_856553,06-13 11:57:07,1,1,232.5,576.6,19,0,232.5,576.6,19.0,0.0,77.7,95.9,19,19,576.6,576.6 +job_856553,06-13 11:57:12,1,1,0.0,609.2,15,0,0.0,609.2,15.0,0.0,72.5,95.9,15,15,609.2,609.2 +job_856553,06-13 11:57:17,1,1,44.3,586.5,16,0,44.3,586.5,16.0,0.0,79.2,95.9,16,16,586.5,586.5 +job_856553,06-13 11:57:22,1,1,109.2,581.4,16,0,109.2,581.4,16.0,0.0,75.8,95.9,16,16,581.4,581.4 +job_856553,06-13 11:57:27,1,1,39.1,540.2,13,0,39.1,540.2,13.0,0.0,54.6,95.9,13,13,540.2,540.2 +job_856553,06-13 11:57:32,1,1,58.4,500.4,13,0,58.4,500.4,13.0,0.0,55.1,95.9,13,13,500.4,500.4 +job_856553,06-13 11:57:37,1,1,772.9,446.5,10,0,772.9,446.5,10.0,0.0,27.5,94.3,10,10,446.5,446.5 +job_856553,06-13 11:57:42,1,1,151.7,586.2,15,0,151.7,586.2,15.0,0.0,60.0,95.9,15,15,586.2,586.2 +job_856553,06-13 11:57:48,1,1,0.0,408.3,10,0,0.0,408.3,10.0,0.0,26.6,94.9,10,10,408.3,408.3 +job_856553,06-13 11:57:53,1,1,76.8,403.0,10,0,76.8,403.0,10.0,0.0,26.0,94.9,10,10,403.0,403.0 +job_856553,06-13 11:57:58,1,1,0.0,378.0,10,0,0.0,378.0,10.0,0.0,26.6,94.9,10,10,378.0,378.0 +job_856553,06-13 11:58:03,1,1,233.2,387.9,11,0,233.2,387.9,11.0,0.0,28.6,94.8,11,11,387.9,387.9 +job_856553,06-13 11:58:08,1,1,277.7,470.5,14,0,277.7,470.5,14.0,0.0,42.2,94.9,14,14,470.5,470.5 +job_856553,06-13 11:58:13,1,1,0.0,516.8,13,0,0.0,516.8,13.0,0.0,40.1,94.9,13,13,516.8,516.8 +job_856553,06-13 11:58:18,1,1,144.0,509.9,13,0,144.0,509.9,13.0,0.0,38.7,94.9,13,13,509.9,509.9 +job_856553,06-13 11:58:23,1,1,32.9,508.7,13,0,32.9,508.7,13.0,0.0,35.5,94.9,13,13,508.7,508.7 +job_856553,06-13 11:58:28,1,1,0.0,494.0,13,0,0.0,494.0,13.0,0.0,36.2,94.9,13,13,494.0,494.0 +job_856553,06-13 11:58:33,1,1,269.9,315.3,6,0,269.9,315.3,6.0,0.0,14.2,94.9,6,6,315.3,315.3 +job_856553,06-13 11:58:38,1,1,146.2,310.3,7,0,146.2,310.3,7.0,0.0,18.2,94.9,7,7,310.3,310.3 +job_856553,06-13 11:58:43,1,1,122.4,491.6,13,0,122.4,491.6,13.0,0.0,33.4,94.8,13,13,491.6,491.6 +job_856553,06-13 11:58:48,1,1,0.0,475.1,12,0,0.0,475.1,12.0,0.0,33.5,94.8,12,12,475.1,475.1 +job_856553,06-13 11:58:53,1,1,0.0,449.5,11,0,0.0,449.5,11.0,0.0,29.0,94.8,11,11,449.5,449.5 +job_856553,06-13 11:58:58,1,1,102.7,425.0,13,0,102.7,425.0,13.0,0.0,41.5,94.9,13,13,425.0,425.0 +job_856553,06-13 11:59:03,1,1,94.2,496.3,14,0,94.2,496.3,14.0,0.0,42.4,94.9,14,14,496.3,496.3 +job_856553,06-13 11:59:08,1,1,119.3,503.4,14,0,119.3,503.4,14.0,0.0,39.9,94.9,14,14,503.4,503.4 +job_856553,06-13 11:59:13,1,1,10.4,562.1,13,0,10.4,562.1,13.0,0.0,33.9,94.9,13,13,562.1,562.1 +job_856553,06-13 11:59:18,1,1,0.0,473.7,12,0,0.0,473.7,12.0,0.0,34.4,94.9,12,12,473.7,473.7 +job_856553,06-13 11:59:23,1,1,448.0,474.3,13,0,448.0,474.3,13.0,0.0,40.2,94.8,13,13,474.3,474.3 +job_856553,06-13 11:59:28,1,1,0.0,491.7,12,0,0.0,491.7,12.0,0.0,37.2,94.8,12,12,491.7,491.7 +job_856553,06-13 11:59:33,1,1,24.4,459.0,11,0,24.4,459.0,11.0,0.0,33.6,94.8,11,11,459.0,459.0 +job_856553,06-13 11:59:38,1,1,201.6,453.8,12,0,201.6,453.8,12.0,0.0,37.0,94.8,12,12,453.8,453.8 +job_856553,06-13 11:59:43,1,1,274.1,434.1,9,0,274.1,434.1,9.0,0.0,30.5,94.9,9,9,434.1,434.1 +job_856553,06-13 11:59:48,1,1,0.0,414.6,11,0,0.0,414.6,11.0,0.0,32.8,94.8,11,11,414.6,414.6 +job_856553,06-13 11:59:53,1,1,87.0,420.1,11,0,87.0,420.1,11.0,0.0,31.7,94.8,11,11,420.1,420.1 +job_856553,06-13 11:59:58,1,1,239.1,550.1,16,0,239.1,550.1,16.0,0.0,66.2,95.9,16,16,550.1,550.1 +job_856553,06-13 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22:26:49,1,1,8.6,454.1,9,0,8.6,454.1,9.0,0.0,44.5,95.2,9,9,454.1,454.1 +job_856554,06-13 22:26:54,1,1,82.5,369.4,8,0,82.5,369.4,8.0,0.0,40.6,95.2,8,8,369.4,369.4 +job_856554,06-13 22:26:59,1,1,77.4,437.0,10,0,77.4,437.0,10.0,0.0,48.9,95.2,10,10,437.0,437.0 +job_856554,06-13 22:27:04,1,1,110.4,498.4,11,0,110.4,498.4,11.0,0.0,50.4,95.2,11,11,498.4,498.4 +job_856554,06-13 22:27:09,1,1,104.9,491.8,12,0,104.9,491.8,12.0,0.0,50.7,95.2,12,12,491.8,491.8 +job_856554,06-13 22:27:14,1,1,110.0,591.1,11,0,110.0,591.1,11.0,0.0,49.5,95.2,11,11,591.1,591.1 +job_856554,06-13 22:27:19,1,1,29.6,561.3,17,0,29.6,561.3,17.0,0.0,66.6,95.4,17,17,561.3,561.3 +job_856554,06-13 22:27:24,1,1,126.9,540.8,17,0,126.9,540.8,17.0,0.0,56.3,95.4,17,17,540.8,540.8 +job_856554,06-13 22:27:29,1,1,172.8,534.2,15,0,172.8,534.2,15.0,0.0,54.1,95.4,15,15,534.2,534.2 +job_856554,06-13 22:27:34,1,1,61.4,492.6,13,0,61.4,492.6,13.0,0.0,52.4,95.4,13,13,492.6,492.6 +job_856554,06-13 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22:31:50,1,1,0.0,604.8,11,0,0.0,604.8,11.0,0.0,49.8,95.3,11,11,604.8,604.8 +job_856554,06-13 22:31:55,1,1,0.0,553.6,10,0,0.0,553.6,10.0,0.0,48.3,95.3,10,10,553.6,553.6 +job_856554,06-13 22:32:00,1,1,93.5,274.9,5,0,93.5,274.9,5.0,0.0,19.1,95.2,5,5,274.9,274.9 +job_856554,06-13 22:32:05,1,1,146.2,265.0,4,0,146.2,265.0,4.0,0.0,17.6,95.2,4,4,265.0,265.0 +job_856554,06-13 22:32:10,1,1,113.8,302.7,6,0,113.8,302.7,6.0,0.0,19.5,95.2,6,6,302.7,302.7 +job_856554,06-13 22:32:16,1,1,85.2,465.3,9,0,85.2,465.3,9.0,0.0,36.2,95.3,9,9,465.3,465.3 +job_856554,06-13 22:32:21,1,1,0.0,454.2,8,0,0.0,454.2,8.0,0.0,33.1,95.3,8,8,454.2,454.2 +job_856554,06-13 22:32:26,1,1,9.2,286.2,6,0,9.2,286.2,6.0,0.0,10.2,95.4,6,6,286.2,286.2 +job_856554,06-13 22:32:31,1,1,0.0,264.5,5,0,0.0,264.5,5.0,0.0,8.7,95.4,5,5,264.5,264.5 +job_856554,06-13 22:32:36,1,1,0.0,224.8,5,0,0.0,224.8,5.0,0.0,9.0,95.4,5,5,224.8,224.8 +job_856554,06-13 22:32:41,1,1,484.1,295.1,8,0,484.1,295.1,8.0,0.0,23.6,95.4,8,8,295.1,295.1 +job_856554,06-13 22:32:46,1,1,7.6,374.8,9,0,7.6,374.8,9.0,0.0,27.1,95.4,9,9,374.8,374.8 +job_856554,06-13 22:32:51,1,1,0.0,374.4,8,0,0.0,374.4,8.0,0.0,24.6,95.4,8,8,374.4,374.4 +job_856554,06-13 22:32:56,1,1,0.0,363.2,8,0,0.0,363.2,8.0,0.0,25.1,95.4,8,8,363.2,363.2 +job_856554,06-13 22:33:01,1,1,48.7,372.2,9,0,48.7,372.2,9.0,0.0,27.5,95.4,9,9,372.2,372.2 +job_856554,06-13 22:33:06,1,1,0.0,383.6,8,0,0.0,383.6,8.0,0.0,26.9,95.4,8,8,383.6,383.6 +job_856554,06-13 22:33:11,1,1,8.8,375.1,9,0,8.8,375.1,9.0,0.0,30.4,95.4,9,9,375.1,375.1 +job_856554,06-13 22:33:16,1,1,97.7,410.3,10,0,97.7,410.3,10.0,0.0,31.2,95.4,10,10,410.3,410.3 +job_856554,06-13 22:33:21,1,1,0.0,421.1,9,0,0.0,421.1,9.0,0.0,24.8,95.4,9,9,421.1,421.1 +job_856554,06-13 22:33:26,1,1,119.2,423.5,10,0,119.2,423.5,10.0,0.0,26.8,95.4,10,10,423.5,423.5 +job_856554,06-13 22:33:31,1,1,43.7,367.4,7,0,43.7,367.4,7.0,0.0,16.2,94.9,7,7,367.4,367.4 +job_856554,06-13 22:33:36,1,1,0.0,343.3,7,0,0.0,343.3,7.0,0.0,16.6,94.9,7,7,343.3,343.3 +job_856554,06-13 22:33:41,1,1,276.1,364.7,8,0,276.1,364.7,8.0,0.0,13.9,94.9,8,8,364.7,364.7 +job_856554,06-13 22:33:46,1,1,11.4,509.7,10,0,11.4,509.7,10.0,0.0,25.3,95.0,10,10,509.7,509.7 +job_856554,06-13 22:33:51,1,1,0.0,421.0,7,0,0.0,421.0,7.0,0.0,20.0,95.0,7,7,421.0,421.0 +job_856554,06-13 22:33:56,1,1,0.0,252.1,5,0,0.0,252.1,5.0,0.0,18.2,95.0,5,5,252.1,252.1 +job_856554,06-13 22:34:01,1,1,0.0,456.4,9,0,0.0,456.4,9.0,0.0,16.6,94.9,9,9,456.4,456.4 +job_856554,06-13 22:34:06,1,1,0.0,359.0,8,0,0.0,359.0,8.0,0.0,21.6,95.4,8,8,359.0,359.0 +job_856554,06-13 22:34:11,1,1,43.9,556.5,9,0,43.9,556.5,9.0,0.0,22.0,94.9,9,9,556.5,556.5 +job_856554,06-13 22:34:16,1,1,181.2,437.1,10,0,181.2,437.1,10.0,0.0,30.7,95.4,10,10,437.1,437.1 +job_856554,06-13 22:34:21,1,1,82.1,397.9,8,0,82.1,397.9,8.0,0.0,21.7,94.9,8,8,397.9,397.9 +job_856554,06-13 22:34:26,1,1,0.0,392.6,8,0,0.0,392.6,8.0,0.0,22.3,94.9,8,8,392.6,392.6 +job_856554,06-13 22:34:31,1,1,0.0,318.6,6,0,0.0,318.6,6.0,0.0,21.3,94.9,6,6,318.6,318.6 +job_856554,06-13 22:34:36,1,1,155.3,523.4,12,0,155.3,523.4,12.0,0.0,30.6,94.9,12,12,523.4,523.4 +job_856554,06-13 22:34:41,1,1,136.7,564.5,12,0,136.7,564.5,12.0,0.0,30.5,94.9,12,12,564.5,564.5 +job_856554,06-13 22:34:46,1,1,398.0,569.7,14,0,398.0,569.7,14.0,0.0,34.8,94.9,14,14,569.7,569.7 +job_856554,06-13 22:34:51,1,1,53.3,593.1,14,0,53.3,593.1,14.0,0.0,44.8,95.0,14,14,593.1,593.1 +job_856554,06-13 22:34:56,1,1,0.0,382.9,7,0,0.0,382.9,7.0,0.0,19.6,94.9,7,7,382.9,382.9 +job_856554,06-13 22:35:01,1,1,84.8,329.3,7,0,84.8,329.3,7.0,0.0,18.2,94.9,7,7,329.3,329.3 +job_856554,06-13 22:35:06,1,1,171.9,583.0,16,0,171.9,583.0,16.0,0.0,46.9,95.5,16,16,583.0,583.0 +job_856554,06-13 22:35:11,1,1,96.3,539.1,17,0,96.3,539.1,17.0,0.0,53.9,95.5,17,17,539.1,539.1 +job_856554,06-13 22:35:16,1,1,0.0,524.9,17,0,0.0,524.9,17.0,0.0,54.6,95.5,17,17,524.9,524.9 +job_856554,06-13 22:35:21,1,1,0.0,518.5,17,0,0.0,518.5,17.0,0.0,55.3,95.5,17,17,518.5,518.5 +job_856554,06-13 22:35:26,1,1,0.0,540.5,15,0,0.0,540.5,15.0,0.0,47.5,95.5,15,15,540.5,540.5 +job_856554,06-13 22:35:31,1,1,80.3,576.8,14,0,80.3,576.8,14.0,0.0,39.5,95.5,14,14,576.8,576.8 +job_856554,06-13 22:35:36,1,1,57.9,536.6,13,0,57.9,536.6,13.0,0.0,35.4,95.5,13,13,536.6,536.6 +job_856554,06-13 22:35:41,1,1,0.0,448.9,12,0,0.0,448.9,12.0,0.0,32.4,95.5,12,12,448.9,448.9 +job_856554,06-13 22:35:46,1,1,151.5,440.6,12,0,151.5,440.6,12.0,0.0,32.3,95.5,12,12,440.6,440.6 +job_856554,06-13 22:35:51,1,1,174.6,436.7,8,0,174.6,436.7,8.0,0.0,12.9,96.0,8,8,436.7,436.7 +job_856554,06-13 22:35:56,1,1,1.4,395.8,10,0,1.4,395.8,10.0,0.0,29.1,95.5,10,10,395.8,395.8 +job_856554,06-13 22:36:01,1,1,160.5,444.4,13,0,160.5,444.4,13.0,0.0,33.1,95.5,13,13,444.4,444.4 +job_856554,06-13 22:36:06,1,1,213.3,429.2,12,0,213.3,429.2,12.0,0.0,40.1,95.5,12,12,429.2,429.2 +job_856554,06-13 22:36:11,1,1,248.8,498.7,15,0,248.8,498.7,15.0,0.0,49.5,95.5,15,15,498.7,498.7 +job_856554,06-13 22:36:16,1,1,0.0,527.3,14,0,0.0,527.3,14.0,0.0,46.5,95.5,14,14,527.3,527.3 +job_856554,06-13 22:36:21,1,1,132.4,534.8,14,0,132.4,534.8,14.0,0.0,41.5,95.5,14,14,534.8,534.8 +job_856554,06-13 22:36:26,1,1,233.5,522.6,17,0,233.5,522.6,17.0,0.0,47.3,95.5,17,17,522.6,522.6 +job_856554,06-13 22:36:31,1,1,0.0,574.0,16,0,0.0,574.0,16.0,0.0,45.7,95.5,16,16,574.0,574.0 +job_856554,06-13 22:36:37,1,1,0.0,563.3,16,0,0.0,563.3,16.0,0.0,46.5,95.5,16,16,563.3,563.3 +job_856554,06-13 22:36:41,1,1,101.8,303.8,7,0,101.8,303.8,7.0,0.0,26.4,96.0,7,7,303.8,303.8 +job_856554,06-13 22:36:47,1,1,157.5,542.3,18,0,157.5,542.3,18.0,0.0,56.6,95.5,18,18,542.3,542.3 +job_856554,06-13 22:36:52,1,1,0.0,544.5,15,0,0.0,544.5,15.0,0.0,41.2,95.5,15,15,544.5,544.5 +job_856554,06-13 22:36:57,1,1,0.0,544.0,15,0,0.0,544.0,15.0,0.0,42.0,95.5,15,15,544.0,544.0 +job_856554,06-13 22:37:02,1,1,101.2,562.0,15,0,101.2,562.0,15.0,0.0,44.4,95.5,15,15,562.0,562.0 +job_856554,06-13 22:37:07,1,1,108.1,527.9,16,0,108.1,527.9,16.0,0.0,49.4,95.5,16,16,527.9,527.9 +job_856554,06-13 22:37:12,1,1,78.0,578.1,18,0,78.0,578.1,18.0,0.0,63.4,95.5,18,18,578.1,578.1 +job_856554,06-13 22:37:17,1,1,0.0,555.8,16,0,0.0,555.8,16.0,0.0,59.8,95.5,16,16,555.8,555.8 +job_856554,06-13 22:37:22,1,1,0.0,567.4,14,0,0.0,567.4,14.0,0.0,54.9,95.5,14,14,567.4,567.4 +job_856554,06-13 22:37:27,1,1,305.0,531.4,14,0,305.0,531.4,14.0,0.0,50.3,95.5,14,14,531.4,531.4 +job_856554,06-13 22:37:32,1,1,42.0,479.3,14,0,42.0,479.3,14.0,0.0,51.0,95.5,14,14,479.3,479.3 +job_856554,06-13 22:37:37,1,1,0.0,451.6,10,0,0.0,451.6,10.0,0.0,40.8,95.5,10,10,451.6,451.6 +job_856554,06-13 22:37:42,1,1,93.4,328.6,10,0,93.4,328.6,10.0,0.0,39.3,95.5,10,10,328.6,328.6 +job_856554,06-13 22:37:47,1,1,173.1,446.0,12,0,173.1,446.0,12.0,0.0,51.6,95.6,12,12,446.0,446.0 +job_856554,06-13 22:37:52,1,1,159.6,434.7,12,0,159.6,434.7,12.0,0.0,50.3,95.6,12,12,434.7,434.7 +job_856554,06-13 22:37:57,1,1,182.6,474.2,14,0,182.6,474.2,14.0,0.0,56.8,95.6,14,14,474.2,474.2 +job_856554,06-13 22:38:02,1,1,483.1,546.7,18,0,483.1,546.7,18.0,0.0,68.0,95.5,18,18,546.7,546.7 +job_856554,06-13 22:38:07,1,1,117.5,561.5,17,0,117.5,561.5,17.0,0.0,63.0,95.6,17,17,561.5,561.5 +job_856554,06-13 22:38:12,1,1,119.3,571.9,17,0,119.3,571.9,17.0,0.0,67.0,95.6,17,17,571.9,571.9 +job_856554,06-13 22:38:17,1,1,19.5,540.1,17,0,19.5,540.1,17.0,0.0,64.3,95.5,17,17,540.1,540.1 +job_856554,06-13 22:38:22,1,1,0.0,539.8,15,0,0.0,539.8,15.0,0.0,58.4,95.5,15,15,539.8,539.8 +job_856554,06-13 22:38:27,1,1,29.0,543.8,11,0,29.0,543.8,11.0,0.0,46.2,95.3,11,11,543.8,543.8 +job_856554,06-13 22:38:32,1,1,259.8,248.3,6,0,259.8,248.3,6.0,0.0,24.8,95.2,6,6,248.3,248.3 +job_856554,06-13 22:38:37,1,1,0.0,449.1,6,0,0.0,449.1,6.0,0.0,31.8,95.3,6,6,449.1,449.1 +job_856554,06-13 22:38:42,1,1,196.7,554.0,16,0,196.7,554.0,16.0,0.0,58.8,95.6,16,16,554.0,554.0 +job_856554,06-13 22:38:47,1,1,0.8,535.6,15,0,0.8,535.6,15.0,0.0,56.5,95.6,15,15,535.6,535.6 +job_856554,06-13 22:38:52,1,1,172.3,523.6,15,0,172.3,523.6,15.0,0.0,56.4,95.6,15,15,523.6,523.6 +job_856554,06-13 22:38:57,1,1,0.0,540.2,14,0,0.0,540.2,14.0,0.0,53.9,95.6,14,14,540.2,540.2 +job_856554,06-13 22:39:02,1,1,0.0,474.0,13,0,0.0,474.0,13.0,0.0,51.1,95.6,13,13,474.0,474.0 +job_856554,06-13 22:39:07,1,1,759.4,505.3,17,0,759.4,505.3,17.0,0.0,61.5,95.5,17,17,505.3,505.3 +job_856554,06-13 22:39:12,1,1,144.0,537.7,18,0,144.0,537.7,18.0,0.0,62.5,95.5,18,18,537.7,537.7 +job_856554,06-13 22:39:17,1,1,139.6,554.4,17,0,139.6,554.4,17.0,0.0,64.8,95.5,17,17,554.4,554.4 +job_856554,06-13 22:39:22,1,1,83.6,542.9,15,0,83.6,542.9,15.0,0.0,62.4,95.5,15,15,542.9,542.9 +job_856554,06-13 22:39:27,1,1,0.0,479.3,11,0,0.0,479.3,11.0,0.0,42.5,95.5,11,11,479.3,479.3 +job_856554,06-13 22:39:32,1,1,101.9,389.0,11,0,101.9,389.0,11.0,0.0,41.2,95.5,11,11,389.0,389.0 +job_856554,06-13 22:39:37,1,1,537.9,390.9,12,0,537.9,390.9,12.0,0.0,43.4,95.5,12,12,390.9,390.9 +job_856554,06-13 22:39:42,1,1,107.6,472.1,13,0,107.6,472.1,13.0,0.0,41.9,95.5,13,13,472.1,472.1 +job_856554,06-13 22:39:47,1,1,370.1,493.6,15,0,370.1,493.6,15.0,0.0,49.5,95.5,15,15,493.6,493.6 +job_856554,06-13 22:39:52,1,1,256.7,563.3,15,0,256.7,563.3,15.0,0.0,52.4,95.5,15,15,563.3,563.3 +job_856554,06-13 22:39:57,1,1,48.9,436.4,7,0,48.9,436.4,7.0,0.0,28.5,95.3,7,7,436.4,436.4 +job_856554,06-13 22:40:02,1,1,71.6,545.9,17,0,71.6,545.9,17.0,0.0,62.9,95.5,17,17,545.9,545.9 +job_856554,06-13 22:40:07,1,1,49.3,529.7,17,0,49.3,529.7,17.0,0.0,61.7,95.5,17,17,529.7,529.7 +job_856554,06-13 22:40:12,1,1,9.6,538.4,17,0,9.6,538.4,17.0,0.0,61.6,95.5,17,17,538.4,538.4 +job_856554,06-13 22:40:17,1,1,32.8,549.9,16,0,32.8,549.9,16.0,0.0,56.5,95.5,16,16,549.9,549.9 +job_856554,06-13 22:40:22,1,1,100.6,512.3,14,0,100.6,512.3,14.0,0.0,53.7,95.5,14,14,512.3,512.3 +job_856554,06-13 22:40:27,1,1,0.0,493.0,13,0,0.0,493.0,13.0,0.0,53.0,95.5,13,13,493.0,493.0 +job_856554,06-13 22:40:32,1,1,100.1,505.1,14,0,100.1,505.1,14.0,0.0,54.9,95.5,14,14,505.1,505.1 +job_856554,06-13 22:40:36,1,1,0.0,218.0,5,0,0.0,218.0,5.0,0.0,16.8,94.3,5,5,218.0,218.0 +job_856554,06-13 22:40:37,3,3,0.0,1232.0,25,0,0.0,410.6666666666667,8.333333333333334,0.0,37.333333333333336,95.63333333333333,5,11,362.5,451.9 +job_856554,06-13 22:40:39,1,1,0.0,305.9,6,0,0.0,305.9,6.0,0.0,29.9,95.0,6,6,305.9,305.9 +job_856554,06-13 22:40:42,1,1,0.0,398.3,10,0,0.0,398.3,10.0,0.0,45.9,95.5,10,10,398.3,398.3 +job_856554,06-13 22:40:46,1,1,0.0,325.9,7,0,0.0,325.9,7.0,0.0,24.0,95.0,7,7,325.9,325.9 +job_856554,06-13 22:40:47,1,1,0.0,158.3,3,0,0.0,158.3,3.0,0.0,15.7,95.4,3,3,158.3,158.3 +job_856554,06-13 22:40:52,3,3,0.0,770.1,17,0,0.0,256.7,5.666666666666667,0.0,24.8,95.39999999999999,3,8,147.8,336.5 +job_856554,06-13 22:40:57,1,1,1120.3,347.2,12,0,1120.3,347.2,12.0,0.0,45.5,95.5,12,12,347.2,347.2 +job_856554,06-13 22:41:02,1,1,89.1,409.4,12,0,89.1,409.4,12.0,0.0,50.1,95.5,12,12,409.4,409.4 +job_856554,06-13 22:41:07,1,1,375.3,454.8,13,0,375.3,454.8,13.0,0.0,43.5,95.5,13,13,454.8,454.8 +job_856554,06-13 22:41:12,1,1,165.6,466.5,13,0,165.6,466.5,13.0,0.0,49.1,95.5,13,13,466.5,466.5 +job_856554,06-13 22:41:17,1,1,189.8,492.5,15,0,189.8,492.5,15.0,0.0,57.7,95.5,15,15,492.5,492.5 +job_856554,06-13 22:41:22,1,1,325.1,538.7,13,0,325.1,538.7,13.0,0.0,50.9,95.5,13,13,538.7,538.7 +job_856554,06-13 22:41:28,1,1,68.8,455.7,13,0,68.8,455.7,13.0,0.0,53.7,95.5,13,13,455.7,455.7 +job_856554,06-13 22:41:33,1,1,46.3,485.4,13,0,46.3,485.4,13.0,0.0,50.2,95.5,13,13,485.4,485.4 +job_856554,06-13 22:41:38,1,1,0.0,169.0,3,0,0.0,169.0,3.0,0.0,12.8,95.6,3,3,169.0,169.0 +job_856554,06-13 22:41:43,1,1,142.6,516.3,15,0,142.6,516.3,15.0,0.0,59.1,95.5,15,15,516.3,516.3 +job_856554,06-13 22:41:48,1,1,76.9,142.0,3,0,76.9,142.0,3.0,0.0,16.2,95.6,3,3,142.0,142.0 +job_856554,06-13 22:41:53,1,1,0.0,120.3,2,0,0.0,120.3,2.0,0.0,7.9,95.6,2,2,120.3,120.3 +job_856554,06-13 22:41:58,1,1,140.8,565.7,16,0,140.8,565.7,16.0,0.0,65.7,95.5,16,16,565.7,565.7 +job_856554,06-13 22:42:03,1,1,296.5,565.5,14,0,296.5,565.5,14.0,0.0,60.8,95.4,14,14,565.5,565.5 +job_856554,06-13 22:42:08,1,1,0.0,466.7,13,0,0.0,466.7,13.0,0.0,59.7,95.4,13,13,466.7,466.7 +job_856554,06-13 22:42:13,1,1,20.1,400.2,12,0,20.1,400.2,12.0,0.0,54.9,95.5,12,12,400.2,400.2 +job_856554,06-13 22:42:18,1,1,147.3,457.3,13,0,147.3,457.3,13.0,0.0,52.1,95.4,13,13,457.3,457.3 +job_856554,06-13 22:42:23,1,1,306.3,446.9,14,0,306.3,446.9,14.0,0.0,54.1,95.4,14,14,446.9,446.9 +job_856554,06-13 22:42:28,1,1,191.9,530.7,16,0,191.9,530.7,16.0,0.0,61.3,95.4,16,16,530.7,530.7 +job_856554,06-13 22:42:33,1,1,0.0,52.3,1,0,0.0,52.3,1.0,0.0,7.7,95.8,1,1,52.3,52.3 +job_856554,06-13 22:42:38,1,1,0.0,52.0,1,0,0.0,52.0,1.0,0.0,7.8,95.8,1,1,52.0,52.0 +job_856554,06-13 22:42:43,1,1,310.7,114.6,3,0,310.7,114.6,3.0,0.0,12.7,95.6,3,3,114.6,114.6 +job_856554,06-13 22:42:48,1,1,19.9,183.0,4,0,19.9,183.0,4.0,0.0,16.9,95.6,4,4,183.0,183.0 +job_856554,06-13 22:42:53,1,1,0.0,146.4,3,0,0.0,146.4,3.0,0.0,13.1,95.6,3,3,146.4,146.4 +job_856554,06-13 22:42:58,1,1,0.0,578.8,16,0,0.0,578.8,16.0,0.0,61.1,95.4,16,16,578.8,578.8 +job_856554,06-13 22:43:03,1,1,0.0,534.2,14,0,0.0,534.2,14.0,0.0,50.9,95.4,14,14,534.2,534.2 +job_856554,06-13 22:43:08,1,1,0.0,472.3,12,0,0.0,472.3,12.0,0.0,46.9,95.4,12,12,472.3,472.3 +job_856554,06-13 22:43:13,1,1,124.3,443.9,12,0,124.3,443.9,12.0,0.0,53.4,95.4,12,12,443.9,443.9 +job_856554,06-13 22:43:18,1,1,34.2,421.6,11,0,34.2,421.6,11.0,0.0,53.5,95.5,11,11,421.6,421.6 +job_856554,06-13 22:43:23,1,1,524.3,478.8,15,0,524.3,478.8,15.0,0.0,70.1,95.5,15,15,478.8,478.8 +job_856554,06-13 22:43:28,1,1,0.0,527.5,14,0,0.0,527.5,14.0,0.0,53.0,95.1,14,14,527.5,527.5 +job_856554,06-13 22:43:33,1,1,0.0,513.9,13,0,0.0,513.9,13.0,0.0,51.1,95.1,13,13,513.9,513.9 +job_856554,06-13 22:43:38,1,1,658.6,528.8,14,0,658.6,528.8,14.0,0.0,59.3,95.1,14,14,528.8,528.8 +job_856554,06-13 22:43:43,1,1,0.0,509.4,14,0,0.0,509.4,14.0,0.0,60.0,95.1,14,14,509.4,509.4 +job_856554,06-13 22:43:48,1,1,228.4,476.5,14,0,228.4,476.5,14.0,0.0,59.3,95.1,14,14,476.5,476.5 +job_856554,06-13 22:43:53,1,1,442.2,445.8,16,0,442.2,445.8,16.0,0.0,72.5,95.4,16,16,445.8,445.8 +job_856554,06-13 22:43:58,1,1,0.0,577.5,16,0,0.0,577.5,16.0,0.0,73.3,95.4,16,16,577.5,577.5 +job_856554,06-13 22:44:03,1,1,87.2,529.3,14,0,87.2,529.3,14.0,0.0,70.3,95.4,14,14,529.3,529.3 +job_856554,06-13 22:44:08,1,1,0.0,501.4,13,0,0.0,501.4,13.0,0.0,68.8,95.4,13,13,501.4,501.4 +job_856554,06-13 22:44:13,1,1,31.6,488.1,13,0,31.6,488.1,13.0,0.0,68.4,95.4,13,13,488.1,488.1 +job_856554,06-13 22:44:18,1,1,41.1,229.4,5,0,41.1,229.4,5.0,0.0,15.4,95.6,5,5,229.4,229.4 +job_856554,06-13 22:44:23,1,1,0.0,520.8,14,0,0.0,520.8,14.0,0.0,64.3,95.4,14,14,520.8,520.8 +job_856554,06-13 22:44:28,1,1,0.0,516.4,14,0,0.0,516.4,14.0,0.0,55.4,95.1,14,14,516.4,516.4 +job_856554,06-13 22:44:33,1,1,18.6,514.6,14,0,18.6,514.6,14.0,0.0,62.7,95.1,14,14,514.6,514.6 +job_856554,06-13 22:44:38,1,1,61.0,162.7,4,0,61.0,162.7,4.0,0.0,13.1,95.6,4,4,162.7,162.7 +job_856554,06-13 22:44:43,1,1,229.5,453.5,12,0,229.5,453.5,12.0,0.0,57.6,95.2,12,12,453.5,453.5 +job_856554,06-13 22:44:48,1,1,0.0,432.5,12,0,0.0,432.5,12.0,0.0,58.2,95.2,12,12,432.5,432.5 +job_856554,06-13 22:44:53,1,1,190.3,500.7,16,0,190.3,500.7,16.0,0.0,62.5,95.2,16,16,500.7,500.7 +job_856554,06-13 22:44:58,1,1,388.3,543.5,19,0,388.3,543.5,19.0,0.0,79.8,95.1,19,19,543.5,543.5 +job_856554,06-13 22:45:03,1,1,172.6,627.3,20,0,172.6,627.3,20.0,0.0,82.1,95.2,20,20,627.3,627.3 +job_856554,06-13 22:45:08,1,1,0.0,575.5,18,0,0.0,575.5,18.0,0.0,75.5,95.2,18,18,575.5,575.5 +job_856554,06-13 22:45:13,1,1,0.0,541.1,17,0,0.0,541.1,17.0,0.0,75.0,95.2,17,17,541.1,541.1 +job_856554,06-13 22:45:18,1,1,0.0,549.5,16,0,0.0,549.5,16.0,0.0,67.8,95.2,16,16,549.5,549.5 +job_856554,06-13 22:45:23,1,1,167.7,551.7,18,0,167.7,551.7,18.0,0.0,70.5,95.1,18,18,551.7,551.7 +job_856554,06-13 22:45:28,1,1,121.5,570.4,18,0,121.5,570.4,18.0,0.0,66.7,95.1,18,18,570.4,570.4 +job_856554,06-13 22:45:33,1,1,0.0,541.7,16,0,0.0,541.7,16.0,0.0,59.6,95.1,16,16,541.7,541.7 +job_856554,06-13 22:45:38,1,1,156.4,538.7,17,0,156.4,538.7,17.0,0.0,68.5,95.1,17,17,538.7,538.7 +job_856554,06-13 22:45:43,1,1,0.0,521.1,17,0,0.0,521.1,17.0,0.0,69.3,95.1,17,17,521.1,521.1 +job_856554,06-13 22:45:48,1,1,30.8,536.8,17,0,30.8,536.8,17.0,0.0,72.0,95.2,17,17,536.8,536.8 +job_856554,06-13 22:45:53,1,1,103.4,566.7,19,0,103.4,566.7,19.0,0.0,80.7,95.2,19,19,566.7,566.7 +job_856554,06-13 22:45:58,1,1,97.8,145.8,3,0,97.8,145.8,3.0,0.0,4.9,41.4,3,3,145.8,145.8 +job_856554,06-13 22:46:03,1,1,0.0,525.2,14,0,0.0,525.2,14.0,0.0,61.3,95.2,14,14,525.2,525.2 +job_856554,06-13 22:46:08,1,1,0.0,494.7,12,0,0.0,494.7,12.0,0.0,56.2,95.2,12,12,494.7,494.7 +job_856554,06-13 22:46:13,1,1,245.6,432.9,13,0,245.6,432.9,13.0,0.0,60.9,95.2,13,13,432.9,432.9 +job_856554,06-13 22:46:18,1,1,374.4,472.7,15,0,374.4,472.7,15.0,0.0,70.6,95.2,15,15,472.7,472.7 +job_856554,06-13 22:46:23,1,1,56.1,572.5,16,0,56.1,572.5,16.0,0.0,78.8,95.2,16,16,572.5,572.5 +job_856554,06-13 22:46:28,1,1,0.0,575.4,15,0,0.0,575.4,15.0,0.0,78.7,95.2,15,15,575.4,575.4 +job_856554,06-13 22:46:33,1,1,345.7,499.9,15,0,345.7,499.9,15.0,0.0,75.7,95.2,15,15,499.9,499.9 +job_856554,06-13 22:46:38,1,1,0.0,214.0,4,0,0.0,214.0,4.0,0.0,11.2,41.9,4,4,214.0,214.0 +job_856554,06-13 22:46:44,1,1,0.0,499.8,11,0,0.0,499.8,11.0,0.0,57.5,95.2,11,11,499.8,499.8 +job_856554,06-13 22:46:49,1,1,96.0,426.2,12,0,96.0,426.2,12.0,0.0,51.5,95.1,12,12,426.2,426.2 +job_856554,06-13 22:46:54,1,1,79.3,434.0,12,0,79.3,434.0,12.0,0.0,51.2,95.1,12,12,434.0,434.0 +job_856554,06-13 22:46:59,1,1,36.9,362.5,9,0,36.9,362.5,9.0,0.0,42.0,95.1,9,9,362.5,362.5 +job_856554,06-13 22:47:04,1,1,0.0,329.8,9,0,0.0,329.8,9.0,0.0,42.5,95.1,9,9,329.8,329.8 +job_856554,06-13 22:47:09,1,1,0.0,338.9,9,0,0.0,338.9,9.0,0.0,42.9,95.1,9,9,338.9,338.9 +job_856554,06-13 22:47:14,1,1,455.4,404.3,11,0,455.4,404.3,11.0,0.0,54.2,95.2,11,11,404.3,404.3 +job_856554,06-13 22:47:19,1,1,116.9,443.2,12,0,116.9,443.2,12.0,0.0,51.6,95.2,12,12,443.2,443.2 +job_856554,06-13 22:47:24,1,1,153.1,498.0,13,0,153.1,498.0,13.0,0.0,54.4,95.1,13,13,498.0,498.0 +job_856554,06-13 22:47:29,1,1,126.5,464.8,15,0,126.5,464.8,15.0,0.0,63.9,95.2,15,15,464.8,464.8 +job_856554,06-13 22:47:34,1,1,93.2,543.8,15,0,93.2,543.8,15.0,0.0,62.2,95.2,15,15,543.8,543.8 +job_856554,06-13 22:47:39,1,1,9.2,516.7,14,0,9.2,516.7,14.0,0.0,50.3,95.2,14,14,516.7,516.7 +job_856554,06-13 22:47:44,1,1,28.0,516.2,13,0,28.0,516.2,13.0,0.0,46.1,95.2,13,13,516.2,516.2 +job_856554,06-13 22:47:49,1,1,67.5,453.0,12,0,67.5,453.0,12.0,0.0,43.4,95.2,12,12,453.0,453.0 +job_856554,06-13 22:47:54,1,1,48.5,451.1,11,0,48.5,451.1,11.0,0.0,37.1,95.2,11,11,451.1,451.1 +job_856554,06-13 22:47:59,1,1,0.0,342.9,8,0,0.0,342.9,8.0,0.0,26.2,95.2,8,8,342.9,342.9 +job_856554,06-13 22:48:04,1,1,292.6,323.2,11,0,292.6,323.2,11.0,0.0,38.5,95.2,11,11,323.2,323.2 +job_856554,06-13 22:48:09,1,1,8.4,392.1,11,0,8.4,392.1,11.0,0.0,42.6,95.2,11,11,392.1,392.1 +job_856554,06-13 22:48:14,1,1,208.5,403.1,10,0,208.5,403.1,10.0,0.0,42.4,95.2,10,10,403.1,403.1 +job_856554,06-13 22:48:19,1,1,80.4,382.9,10,0,80.4,382.9,10.0,0.0,38.6,95.2,10,10,382.9,382.9 +job_856554,06-13 22:48:24,1,1,269.0,395.2,12,0,269.0,395.2,12.0,0.0,41.9,95.2,12,12,395.2,395.2 +job_856554,06-13 22:48:29,1,1,87.9,410.5,10,0,87.9,410.5,10.0,0.0,36.5,95.2,10,10,410.5,410.5 +job_856554,06-13 22:48:34,1,1,19.8,391.2,12,0,19.8,391.2,12.0,0.0,39.9,95.2,12,12,391.2,391.2 +job_856554,06-13 22:48:39,1,1,35.1,414.9,11,0,35.1,414.9,11.0,0.0,38.0,95.2,11,11,414.9,414.9 +job_856554,06-13 22:48:44,1,1,125.6,417.8,13,0,125.6,417.8,13.0,0.0,38.7,95.2,13,13,417.8,417.8 +job_856554,06-13 22:48:49,1,1,0.0,464.4,12,0,0.0,464.4,12.0,0.0,35.7,95.2,12,12,464.4,464.4 +job_856554,06-13 22:48:54,1,1,248.5,453.4,13,0,248.5,453.4,13.0,0.0,38.1,95.2,13,13,453.4,453.4 +job_856554,06-13 22:48:59,1,1,63.5,461.5,15,0,63.5,461.5,15.0,0.0,42.3,95.2,15,15,461.5,461.5 +job_856554,06-13 22:49:04,1,1,122.4,576.9,18,0,122.4,576.9,18.0,0.0,53.1,95.2,18,18,576.9,576.9 +job_856554,06-13 22:49:09,1,1,69.1,563.7,15,0,69.1,563.7,15.0,0.0,46.6,95.2,15,15,563.7,563.7 +job_856554,06-13 22:49:14,1,1,82.1,537.2,15,0,82.1,537.2,15.0,0.0,50.0,95.2,15,15,537.2,537.2 +job_856554,06-13 22:49:19,1,1,43.7,571.4,16,0,43.7,571.4,16.0,0.0,53.1,95.2,16,16,571.4,571.4 +job_856554,06-13 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a/training_logs/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san_856555.out b/training_logs/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san_856555.out new file mode 100644 index 0000000000000000000000000000000000000000..638a4a0c7f7c19c34285cf50344ec2341fc101d0 --- /dev/null +++ b/training_logs/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san_856555.out @@ -0,0 +1,19450 @@ + +The following have been reloaded with a version change: + 1) GCCcore/.14.3.0 => GCCcore/14.3.0 + + +Lmod is automatically replacing "GCC/14.3.0" with +"nvidia-compilers/25.9-CUDA-13". + +Deactivating conda environment: /e/scratch/jureap59/feuer1/miniforge3/envs/otagent +Activating RL environment: /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl +Python executable: /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/bin/python +Python path check: /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/bin/python +[ray] RAY_TMPDIR=/tmp/ray/ray_856555 +[triton_cache] Triton cache: /tmp/triton_cache_feuer1_856555 +[triton_cache] TorchInductor cache: /tmp/torchinductor_cache_feuer1_856555 +[proxy] ✓ Found proxychains binary at /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 +[proxy] Setting up SSH tunnel to jpbl-s01-01 +[proxy] SSH key: /e/home/jusers/feuer1/jupiter/.ssh/authorized_keys/id_ed25519_jsc +[proxy] Tunnel port: 7003 +[proxy] Node IP: 10.128.34.177 (workers will connect here) +[proxy] ✓ SSH tunnel started successfully +[proxy] ✓ Generated proxychains config at /e/home/jusers/feuer1/jupiter/.proxychains/proxychains_856555.conf +[proxy] - Internal traffic (10.x.x.x, 172.x.x.x, 169.254.x.x) → DIRECT +[proxy] - External traffic (internet) → PROXY via tunnel +[proxy] ✓ Daytona timeout settings configured +[proxy] Testing proxy connectivity... +[proxychains] config file found: /e/home/jusers/feuer1/jupiter/.proxychains/proxychains_856555.conf +[proxychains] preloading /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/lib/libproxychains4.so +[proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e +[proxy] ✓ Proxy connectivity test passed (huggingface.co reachable via wrapped binary) +[proxy] ✓ Tunnel accessible at 10.128.34.177:7003 (workers can connect) +[proxy] ✓ Proxy setup complete (using wrapped binary for Ray workers) +[container_runtime] Using cloud backend: daytona (no local container setup) +=== Universal RL Training Runner === +Config: /e/data1/datasets/playground/ot-baf/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/configs/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san_rl_config.json +Working directory: /e/scratch/jureap59/feuer1/OpenThoughts-Agent +Python: /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/bin/python +Python version: Python 3.12.12 +UV_USE_IO_URING: 0 +Proxy: DISABLED (direct internet or not configured) +======================================== +=== RLJobRunner: rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san === +[wandb_utils] Fixing permissions on: /e/data1/datasets/playground/ot-baf/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/wandb +[wandb_utils] WandB directory ready: /e/data1/datasets/playground/ot-baf/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/wandb + HF_TOKEN=****pDbg + HF_HUB_CACHE=/e/data1/datasets/playground/ot-baf/hf_hub + SUPABASE_URL=https://rpzmyuapoqilpghynmza.s... (direct Supabase config) +Environment configured: + TENSOR_PARALLEL_SIZE=1 + NUM_INFERENCE_ENGINES=56 + POLICY_NUM_NODES=14 + WANDB_DIR=/e/data1/datasets/playground/ot-baf/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/wandb +Starting Ray cluster with 14 nodes, 4 GPUs/node +Cleaning up existing Ray instances... +=== Starting Ray Cluster === + Nodes: 14 + GPUs per node: 4 + CPUs per node: 288 + Head node: jpbo-055-17 (10.128.34.177) + Ray port: 6379 +============================ + Starting Ray head on jpbo-055-17 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_head_jpbo-055-17.log)... + Command: srun --export=ALL,VLLM_HOST_IP=10.128.34.177 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-055-17 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --head --node-ip-address=10.128.34.177 --port=6379 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 + Started Ray head on jpbo-055-17 + Starting Ray worker on jpbo-055-18 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_worker_jpbo-055-18.log)... + Command: srun --export=ALL,VLLM_HOST_IP=10.128.34.178 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-055-18 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --address=10.128.34.177:6379 --node-ip-address=10.128.34.178 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 + Started Ray worker 1 on jpbo-055-18 + Starting Ray worker on jpbo-055-19 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_worker_jpbo-055-19.log)... + Command: srun --export=ALL,VLLM_HOST_IP=10.128.34.179 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-055-19 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --address=10.128.34.177:6379 --node-ip-address=10.128.34.179 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 + Started Ray worker 2 on jpbo-055-19 + Starting Ray worker on jpbo-055-21 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_worker_jpbo-055-21.log)... + Command: srun --export=ALL,VLLM_HOST_IP=10.128.34.181 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-055-21 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --address=10.128.34.177:6379 --node-ip-address=10.128.34.181 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 + Started Ray worker 3 on jpbo-055-21 + Starting Ray worker on jpbo-055-22 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_worker_jpbo-055-22.log)... + Command: srun --export=ALL,VLLM_HOST_IP=10.128.34.182 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-055-22 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --address=10.128.34.177:6379 --node-ip-address=10.128.34.182 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 + Started Ray worker 4 on jpbo-055-22 + Starting Ray worker on jpbo-055-23 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_worker_jpbo-055-23.log)... + Command: srun --export=ALL,VLLM_HOST_IP=10.128.34.183 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-055-23 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --address=10.128.34.177:6379 --node-ip-address=10.128.34.183 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 + Started Ray worker 5 on jpbo-055-23 + Starting Ray worker on jpbo-055-25 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_worker_jpbo-055-25.log)... + Command: srun --export=ALL,VLLM_HOST_IP=10.128.34.185 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-055-25 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --address=10.128.34.177:6379 --node-ip-address=10.128.34.185 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 + Started Ray worker 6 on jpbo-055-25 + Starting Ray worker on jpbo-102-17 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_worker_jpbo-102-17.log)... + Command: srun --export=ALL,VLLM_HOST_IP=10.128.56.65 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-102-17 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --address=10.128.34.177:6379 --node-ip-address=10.128.56.65 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 + Started Ray worker 7 on jpbo-102-17 + Starting Ray worker on jpbo-102-18 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_worker_jpbo-102-18.log)... + Command: srun --export=ALL,VLLM_HOST_IP=10.128.56.66 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-102-18 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --address=10.128.34.177:6379 --node-ip-address=10.128.56.66 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 + Started Ray worker 8 on jpbo-102-18 + Starting Ray worker on jpbo-102-19 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_worker_jpbo-102-19.log)... + Command: srun --export=ALL,VLLM_HOST_IP=10.128.56.67 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-102-19 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --address=10.128.34.177:6379 --node-ip-address=10.128.56.67 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 + Started Ray worker 9 on jpbo-102-19 + Starting Ray worker on jpbo-102-20 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_worker_jpbo-102-20.log)... + Command: srun --export=ALL,VLLM_HOST_IP=10.128.56.68 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-102-20 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --address=10.128.34.177:6379 --node-ip-address=10.128.56.68 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 + Started Ray worker 10 on jpbo-102-20 + Starting Ray worker on jpbo-102-25 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_worker_jpbo-102-25.log)... + Command: srun --export=ALL,VLLM_HOST_IP=10.128.56.73 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-102-25 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --address=10.128.34.177:6379 --node-ip-address=10.128.56.73 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 + Started Ray worker 11 on jpbo-102-25 + Starting Ray worker on jpbo-102-28 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_worker_jpbo-102-28.log)... + Command: srun --export=ALL,VLLM_HOST_IP=10.128.56.76 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-102-28 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --address=10.128.34.177:6379 --node-ip-address=10.128.56.76 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 + Started Ray worker 12 on jpbo-102-28 + Starting Ray worker on jpbo-102-30 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_worker_jpbo-102-30.log)... + Command: srun --export=ALL,VLLM_HOST_IP=10.128.56.78 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-102-30 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --address=10.128.34.177:6379 --node-ip-address=10.128.56.78 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 + Started Ray worker 13 on jpbo-102-30 + Waiting for cluster (56 GPUs, 14 nodes)... +Connecting to Ray at 10.128.34.177:6379 (expecting 14 nodes, 56.0 GPUs) +Ray connection established, polling for resources... +[Ray wait] nodes=14/14 GPUs=56.0/56.0 resources={'object_store_memory': 601295421440.0, 'node:10.128.34.183': 1.0, 'GPU': 56.0, 'CPU': 4032.0, 'accelerator_type:GH200': 14.0, 'memory': 10736461414400.0, 'node:10.128.34.178': 1.0, 'node:10.128.34.179': 1.0, 'node:10.128.56.73': 1.0, 'node:10.128.34.181': 1.0, 'node:10.128.56.67': 1.0, 'node:10.128.34.182': 1.0, 'node:10.128.56.68': 1.0, 'node:10.128.56.65': 1.0, 'node:__internal_head__': 1.0, 'node:10.128.34.177': 1.0, 'node:10.128.56.76': 1.0, 'node:10.128.56.78': 1.0, 'node:10.128.56.66': 1.0, 'node:10.128.34.185': 1.0} +✓ Ray cluster ready +=== Ray Cluster Ready === + Address: 10.128.34.177:6379 + Total GPUs: 56 +========================= +Ray cluster ready at 10.128.34.177:6379 +Total GPUs available: 56 +[RLJobRunner] Pinggy check: url=False, token=False, needs_tunnel=False (agent=terminus-2, env=daytona) +[RLJobRunner] No Pinggy tunnel needed, using local vLLM + +Running SkyRL: + Python: /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/bin/python + Entrypoint: examples.terminal_bench.entrypoints.main_tbench + Args: 134 Hydra arguments + Working dir: /e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train +Using proxychains binary: /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 + +Executing command with srun: /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f $PROXYCHAINS_CONF_FILE /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/bin/python -m examples.terminal_bench.entrypoints.main_tbench +terminal_bench_config=terminal_bench trainer.strategy=fsdp2 trainer.algorithm.advantage_estimator=rloo_n trainer.algorithm.use_kl_loss=false trainer.algorithm.kl_loss_coef=0.0 trainer.algorithm.eps_clip_low=0.2 trainer.algorithm.eps_clip_high=0.2 trainer.algorithm.loss_reduction=seq_mean_token_sum_norm_global trainer.algorithm.use_tis=true trainer.algorithm.tis_imp_ratio_cap=2.0 trainer.epochs=2 trainer.max_steps=80 trainer.update_epochs_per_batch=1 trainer.train_batch_size=64 trainer.policy_mini_batch_size=64 trainer.eval_batch_size=64 trainer.micro_forward_batch_size_per_gpu=4 trainer.micro_train_batch_size_per_gpu=1 trainer.max_prompt_length=999999 trainer.eval_interval=999999 trainer.eval_before_train=false trainer.ckpt_interval=2 trainer.resume_mode=latest trainer.hf_save_interval=5 ++trainer.hf_hub_repo_id=laion/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san ++trainer.hf_hub_private=false ++trainer.hf_hub_revision=main ++trainer.enable_db_registration=false trainer.project_name=OpenThoughts-Agent trainer.log_level=INFO trainer.tracker_commit_each_step=true trainer.logger=console trainer.run_name=rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san trainer.ckpt_path=/e/data1/datasets/playground/ot-baf/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/checkpoints trainer.export_path=/e/data1/datasets/playground/ot-baf/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/exports trainer.policy.optimizer_config.lr=8e-6 trainer.policy.optimizer_config.weight_decay=0.0 trainer.policy.optimizer_config.adam_betas=[0.9,0.999] trainer.policy.optimizer_config.max_grad_norm=0.9 trainer.policy.fsdp_config.cpu_offload=false trainer.policy.fsdp_config.reshard_after_forward=true trainer.policy.fsdp_config.fsdp_size=4 trainer.policy.model.path=/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6 trainer.ref.fsdp_config.cpu_offload=false trainer.ref.fsdp_config.reshard_after_forward=true trainer.ref.fsdp_config.fsdp_size=4 trainer.placement.colocate_all=false trainer.placement.policy_num_nodes=2 trainer.placement.ref_num_nodes=2 trainer.placement.policy_num_gpus_per_node=4 trainer.placement.ref_num_gpus_per_node=4 trainer.fully_async.max_staleness_steps=16 trainer.fully_async.num_parallel_generation_workers=338 generator.backend=vllm generator.timeout_multiplier=1.0 generator.model_dtype=bfloat16 generator.inference_engine_tensor_parallel_size=1 generator.num_inference_engines=48 generator.n_samples_per_prompt=8 generator.eval_n_samples_per_prompt=8 generator.gpu_memory_utilization=0.75 generator.max_num_seqs=24 generator.max_num_batched_tokens=65536 generator.enable_prefix_caching=true generator.enable_chunked_prefill=true generator.run_engines_locally=true generator.weight_sync_backend=nccl generator.async_engine=true generator.batched=false generator.enable_http_endpoint=true generator.enable_ray_prometheus_stats=false generator.vllm_stats_interval=1 generator.append_eos_token_after_stop_str_in_multi_turn=true generator.max_turns=999999 generator.sampling_params.max_generate_length=4096 generator.sampling_params.temperature=1.0 generator.sampling_params.top_p=1.0 generator.sampling_params.top_k=-1 ++generator.engine_init_kwargs.max_model_len=32768 ++generator.engine_init_kwargs.custom_chat_template_chat_completion_path=chat_templates/qwen3_thinking_acc.jinja2 ++generator.engine_init_kwargs.served_model_name=0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6 data.train_data=["/e/scratch/jureap59/feuer1/tasks/exp_rpt_pymethods2test-large"] data.val_data=[] +terminal_bench_config.trials_dir=/e/data1/datasets/playground/ot-baf/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/trace_jobs +terminal_bench_config.harbor.name=terminus-2 +terminal_bench_config.harbor.max_episodes=999999 +terminal_bench_config.harbor.enable_summarize=false +terminal_bench_config.harbor.store_all_messages=true +terminal_bench_config.harbor.trajectory_config.raw_content=true +terminal_bench_config.harbor.enable_episode_logging=false +terminal_bench_config.harbor.record_terminal_session=false +terminal_bench_config.harbor.enable_pane_logging=false +terminal_bench_config.harbor.strict_json_parser=true +terminal_bench_config.harbor.interleaved_thinking=true +terminal_bench_config.harbor.extra_body.chat_template_kwargs.enable_thinking=true +terminal_bench_config.harbor.override_timeout_sec=900 +terminal_bench_config.harbor.override_cpus=1 +terminal_bench_config.harbor.override_memory_mb=2048 +terminal_bench_config.harbor.override_storage_mb=2048 +terminal_bench_config.harbor.auto_snapshot=true +terminal_bench_config.harbor.verifier_override_timeout_sec=120 +terminal_bench_config.harbor.max_retries=3 +terminal_bench_config.harbor.min_wait_sec=60.0 +terminal_bench_config.harbor.max_wait_sec=600.0 +terminal_bench_config.harbor.wait_multiplier=2.0 +terminal_bench_config.harbor.exclude_exceptions=["VerifierTimeoutError","VerifierRuntimeError","RewardFileNotFoundError","RewardFileEmptyError","VerifierOutputParseError"] +terminal_bench_config.harbor.n_concurrent_trials=675 +terminal_bench_config.harbor.log_level=INFO +terminal_bench_config.harbor.enable_reward_shaping=true +terminal_bench_config.harbor.reward_shaper=composite_loop +terminal_bench_config.harbor.loop_outcome_shaper=original +terminal_bench_config.harbor.loop_shaping.outcome_weight=1.0 +terminal_bench_config.harbor.loop_shaping.total_shaping_cap=0.3 +terminal_bench_config.harbor.loop_shaping.terminate.enabled=true +terminal_bench_config.harbor.loop_shaping.terminate.green_bonus=0.3 +terminal_bench_config.harbor.loop_shaping.terminate.red_penalty=0.3 +terminal_bench_config.harbor.loop_shaping.terminate.noterm_penalty=0.2 +terminal_bench_config.harbor.loop_shaping.antithrash.enabled=true +terminal_bench_config.harbor.loop_shaping.antithrash.per_repeat_penalty=0.02 +terminal_bench_config.harbor.loop_shaping.antithrash.cap=0.1 +terminal_bench_config.harbor.collect_rollout_details=true +terminal_bench_config.harbor.enable_error_classification=true +terminal_bench_config.harbor.mask_exceptions=["DaytonaError","EnvironmentStartTimeoutError","NetworkError","ConnectionError","RewardFileNotFoundError","RewardFileEmptyError","AgentEnvironmentTimeoutError","ContextLengthExceededError"] +terminal_bench_config.harbor.default_error_treatment=zero +terminal_bench_config.harbor.passthrough_exceptions=["AgentTimeoutError"] +terminal_bench_config.harbor.zero_exceptions=[] +terminal_bench_config.model_info.max_input_tokens=32000 +terminal_bench_config.model_info.max_output_tokens=4096 +terminal_bench_config.archiving.enabled=false +terminal_bench_config.trace_upload.enabled=true +terminal_bench_config.trace_upload.repo_org=DCAgent +terminal_bench_config.trace_upload.episodes=last +terminal_bench_config.trace_upload.dataset_type=SFT +terminal_bench_config.trace_upload.cleanup=true +[proxychains] config file found: /e/home/jusers/feuer1/jupiter/.proxychains/proxychains_856555.conf +[proxychains] preloading /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/lib/libproxychains4.so +[proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e +2026-06-14 04:05:49.994 | WARNING | skyrl_train.utils.utils:validate_cfg:547 - `generator.sampling_params.logprobs` is `None` but `trainer.algorithm.use_tis` is `True`. Setting `logprobs` to `True`. +2026-06-14 04:05:50.174 | INFO | skyrl_train.utils.utils:prepare_runtime_environment:1106 - Exporting wandb api key to ray runtime env +2026-06-14 04:05:50.174 | INFO | skyrl_train.utils.utils:prepare_runtime_environment:1125 - Exporting RAY_ADDRESS to ray runtime env +2026-06-14 04:05:50.174 | INFO | skyrl_train.utils.utils:prepare_runtime_environment:1150 - Exporting `NCCL_SOCKET_IFNAME` to ray runtime env: ib0 +2026-06-14 04:05:50.174 | INFO | skyrl_train.utils.utils:prepare_runtime_environment:1150 - Exporting `NCCL_SOCKET_FAMILY` to ray runtime env: AF_INET +2026-06-14 04:05:50.174 | INFO | skyrl_train.utils.utils:prepare_runtime_environment:1150 - Exporting `NCCL_DEBUG` to ray runtime env: WARN +2026-06-14 04:05:50,175 INFO worker.py:1680 -- Using address 10.128.34.177:6379 set in the environment variable RAY_ADDRESS +2026-06-14 04:05:50,203 INFO worker.py:1821 -- Connecting to existing Ray cluster at address: 10.128.34.177:6379... +2026-06-14 04:05:50,210 WARNING node.py:1846 -- The object spilling config is specified from an unstable API - system config or environment variable. This is subject to change in the future. You can use the stable API - --object-spilling-directory in ray start or object_spilling_directory in ray.init() to specify the object spilling directory instead. If you need more advanced settings, please open a github issue with the Ray team. +2026-06-14 04:05:50,213 INFO worker.py:2007 -- Connected to Ray cluster. +/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/ray/_private/worker.py:2046: FutureWarning: Tip: In future versions of Ray, Ray will no longer override accelerator visible devices env var if num_gpus=0 or num_gpus=None (default). To enable this behavior and turn off this error message, set RAY_ACCEL_ENV_VAR_OVERRIDE_ON_ZERO=0 + warnings.warn( +(raylet, ip=10.128.56.73) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e +(raylet, ip=10.128.56.73) 2026-06-14 04:05:51,099 WARNING node.py:1846 -- The object spilling config is specified from an unstable API - system config or environment variable. This is subject to change in the future. You can use the stable API - --object-spilling-directory in ray start or object_spilling_directory in ray.init() to specify the object spilling directory instead. If you need more advanced settings, please open a github issue with the Ray team. +2026-06-14 04:05:52.063 | INFO | skyrl_train.utils.ppo_utils:sync_registries:546 - Synced registries to ray actor +(pid=1695573) [2026-06-14 04:05:57,508 E 1695573 1696188] core_worker_process.cc:842: Failed to establish connection to the metrics exporter agent. Metrics will not be exported. Exporter agent status: RpcError: Running out of retries to initialize the metrics agent. rpc_code: 14 +(raylet) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e [repeated 17x across cluster] (Ray deduplicates logs by default. Set RAY_DEDUP_LOGS=0 to disable log deduplication, or see https://docs.ray.io/en/master/ray-observability/user-guides/configure-logging.html#log-deduplication for more options.) +(raylet) 2026-06-14 04:05:52,866 WARNING node.py:1846 -- The object spilling config is specified from an unstable API - system config or environment variable. This is subject to change in the future. You can use the stable API - --object-spilling-directory in ray start or object_spilling_directory in ray.init() to specify the object spilling directory instead. If you need more advanced settings, please open a github issue with the Ray team. [repeated 2x across cluster] +(skyrl_entrypoint pid=1712105) 2026-06-14 04:05:58.330 | INFO  | skyrl_train.entrypoints.main_base:_configure_log_level:225 - SkyRL log level set to: INFO +(skyrl_entrypoint pid=1712105) The tokenizer you are loading from '/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. +(skyrl_entrypoint pid=1712105) 2026-06-14 04:05:58.638 | INFO  | examples.terminal_bench.dataset:_load_data_files:40 - Loading data from: /e/scratch/jureap59/feuer1/tasks/exp_rpt_pymethods2test-large +(skyrl_entrypoint pid=1712105) 2026-06-14 04:06:01.386 | INFO  | examples.terminal_bench.dataset:_load_data_files:50 - Found 5000 valid task directories out of 5000 total directories +(skyrl_entrypoint pid=1712105) 2026-06-14 04:06:01.386 | INFO  | examples.terminal_bench.dataset:__init__:27 - TerminalBenchTaskDataset initialized with 5000 task paths +(skyrl_entrypoint pid=1712105) 2026-06-14 04:06:01.399 | INFO  | skyrl_train.entrypoints.main_base:_setup_trainer:418 - data: +(skyrl_entrypoint pid=1712105) train_data: +(skyrl_entrypoint pid=1712105) - /e/scratch/jureap59/feuer1/tasks/exp_rpt_pymethods2test-large +(skyrl_entrypoint pid=1712105) val_data: [] +(skyrl_entrypoint pid=1712105) trainer: +(skyrl_entrypoint pid=1712105) placement: +(skyrl_entrypoint pid=1712105) colocate_all: false +(skyrl_entrypoint pid=1712105) colocate_policy_ref: true +(skyrl_entrypoint pid=1712105) policy_num_nodes: 2 +(skyrl_entrypoint pid=1712105) policy_num_gpus_per_node: 4 +(skyrl_entrypoint pid=1712105) critic_num_nodes: 1 +(skyrl_entrypoint pid=1712105) critic_num_gpus_per_node: 4 +(skyrl_entrypoint pid=1712105) ref_num_nodes: 2 +(skyrl_entrypoint pid=1712105) ref_num_gpus_per_node: 4 +(skyrl_entrypoint pid=1712105) policy_strict_spread_pg: false +(skyrl_entrypoint pid=1712105) policy_per_gpu_bundles: false +(skyrl_entrypoint pid=1712105) policy_force_cvd_mask: false +(skyrl_entrypoint pid=1712105) sequence_parallel_backend: ulysses +(skyrl_entrypoint pid=1712105) strategy: fsdp2 +(skyrl_entrypoint pid=1712105) policy: +(skyrl_entrypoint pid=1712105) model: +(skyrl_entrypoint pid=1712105) path: /e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6 +(skyrl_entrypoint pid=1712105) lora: +(skyrl_entrypoint pid=1712105) rank: 0 +(skyrl_entrypoint pid=1712105) alpha: 16 +(skyrl_entrypoint pid=1712105) dropout: 0 +(skyrl_entrypoint pid=1712105) lora_sync_path: /tmp/skyrl_lora_sync +(skyrl_entrypoint pid=1712105) target_modules: all-linear +(skyrl_entrypoint pid=1712105) exclude_modules: null +(skyrl_entrypoint pid=1712105) deepspeed_config: ${deepspeed_config.train} +(skyrl_entrypoint pid=1712105) optimizer_config: +(skyrl_entrypoint pid=1712105) optimizer: AdamW +(skyrl_entrypoint pid=1712105) lr: 8.0e-06 +(skyrl_entrypoint pid=1712105) adam_betas: +(skyrl_entrypoint pid=1712105) - 0.9 +(skyrl_entrypoint pid=1712105) - 0.999 +(skyrl_entrypoint pid=1712105) weight_decay: 0.0 +(skyrl_entrypoint pid=1712105) max_grad_norm: 0.9 +(skyrl_entrypoint pid=1712105) offload_after_step: true +(skyrl_entrypoint pid=1712105) num_warmup_steps: 0 +(skyrl_entrypoint pid=1712105) scheduler: constant_with_warmup +(skyrl_entrypoint pid=1712105) optimizer_kwargs: {} +(skyrl_entrypoint pid=1712105) fsdp_config: +(skyrl_entrypoint pid=1712105) cpu_offload: false +(skyrl_entrypoint pid=1712105) reshard_after_forward: true +(skyrl_entrypoint pid=1712105) fsdp_size: 4 +(skyrl_entrypoint pid=1712105) expert_model_parallel_size: 1 +(skyrl_entrypoint pid=1712105) expert_tensor_parallel_size: 1 +(skyrl_entrypoint pid=1712105) moe_token_dispatcher_type: alltoall +(skyrl_entrypoint pid=1712105) moe_router_replay: false +(skyrl_entrypoint pid=1712105) moe_grouped_gemm: false +(skyrl_entrypoint pid=1712105) ep_comm_backend: torch +(skyrl_entrypoint pid=1712105) deepep_num_sms: 20 +(skyrl_entrypoint pid=1712105) deepep_token_chunk_size: null +(skyrl_entrypoint pid=1712105) context_parallel_size: 1 +(skyrl_entrypoint pid=1712105) cp_style: ring_sdpa +(skyrl_entrypoint pid=1712105) cp_rotate_method: allgather +(skyrl_entrypoint pid=1712105) sequence_parallel_size: 1 +(skyrl_entrypoint pid=1712105) use_torch_compile: false +(skyrl_entrypoint pid=1712105) record_memory: false +(skyrl_entrypoint pid=1712105) megatron_config: +(skyrl_entrypoint pid=1712105) tensor_model_parallel_size: 1 +(skyrl_entrypoint pid=1712105) pipeline_model_parallel_size: 1 +(skyrl_entrypoint pid=1712105) context_parallel_size: 1 +(skyrl_entrypoint pid=1712105) expert_model_parallel_size: 1 +(skyrl_entrypoint pid=1712105) expert_tensor_parallel_size: null +(skyrl_entrypoint pid=1712105) ddp_config: +(skyrl_entrypoint pid=1712105) grad_reduce_in_fp32: true +(skyrl_entrypoint pid=1712105) overlap_grad_reduce: false +(skyrl_entrypoint pid=1712105) overlap_param_gather: false +(skyrl_entrypoint pid=1712105) average_in_collective: true +(skyrl_entrypoint pid=1712105) model_config_kwargs: {} +(skyrl_entrypoint pid=1712105) torch_profiler_config: +(skyrl_entrypoint pid=1712105) enable: false +(skyrl_entrypoint pid=1712105) ranks: [] +(skyrl_entrypoint pid=1712105) save_path: null +(skyrl_entrypoint pid=1712105) optimizer_config_kwargs: +(skyrl_entrypoint pid=1712105) overlap_cpu_optimizer_d2h_h2d: false +(skyrl_entrypoint pid=1712105) use_precision_aware_optimizer: false +(skyrl_entrypoint pid=1712105) optimizer_cpu_offload: false +(skyrl_entrypoint pid=1712105) optimizer_offload_fraction: 0.0 +(skyrl_entrypoint pid=1712105) transformer_config_kwargs: +(skyrl_entrypoint pid=1712105) recompute_granularity: full +(skyrl_entrypoint pid=1712105) recompute_modules: +(skyrl_entrypoint pid=1712105) - core_attn +(skyrl_entrypoint pid=1712105) recompute_method: uniform +(skyrl_entrypoint pid=1712105) recompute_num_layers: 1 +(skyrl_entrypoint pid=1712105) empty_cuda_cache: true +(skyrl_entrypoint pid=1712105) ref: +(skyrl_entrypoint pid=1712105) model: +(skyrl_entrypoint pid=1712105) path: ${trainer.policy.model.path} +(skyrl_entrypoint pid=1712105) sequence_parallel_size: 1 +(skyrl_entrypoint pid=1712105) deepspeed_config: ${deepspeed_config.eval} +(skyrl_entrypoint pid=1712105) fsdp_config: +(skyrl_entrypoint pid=1712105) cpu_offload: false +(skyrl_entrypoint pid=1712105) reshard_after_forward: true +(skyrl_entrypoint pid=1712105) fsdp_size: 4 +(skyrl_entrypoint pid=1712105) expert_model_parallel_size: 1 +(skyrl_entrypoint pid=1712105) expert_tensor_parallel_size: 1 +(skyrl_entrypoint pid=1712105) moe_token_dispatcher_type: alltoall +(skyrl_entrypoint pid=1712105) moe_router_replay: false +(skyrl_entrypoint pid=1712105) moe_grouped_gemm: false +(skyrl_entrypoint pid=1712105) ep_comm_backend: torch +(skyrl_entrypoint pid=1712105) deepep_num_sms: 20 +(skyrl_entrypoint pid=1712105) deepep_token_chunk_size: null +(skyrl_entrypoint pid=1712105) context_parallel_size: 1 +(skyrl_entrypoint pid=1712105) cp_style: ring_sdpa +(skyrl_entrypoint pid=1712105) cp_rotate_method: allgather +(skyrl_entrypoint pid=1712105) megatron_config: +(skyrl_entrypoint pid=1712105) tensor_model_parallel_size: 1 +(skyrl_entrypoint pid=1712105) pipeline_model_parallel_size: 1 +(skyrl_entrypoint pid=1712105) context_parallel_size: 1 +(skyrl_entrypoint pid=1712105) expert_model_parallel_size: 1 +(skyrl_entrypoint pid=1712105) expert_tensor_parallel_size: 1 +(skyrl_entrypoint pid=1712105) model_config_kwargs: {} +(skyrl_entrypoint pid=1712105) transformer_config_kwargs: {} +(skyrl_entrypoint pid=1712105) critic: +(skyrl_entrypoint pid=1712105) model: +(skyrl_entrypoint pid=1712105) path: null +(skyrl_entrypoint pid=1712105) lora: +(skyrl_entrypoint pid=1712105) rank: 0 +(skyrl_entrypoint pid=1712105) alpha: 16 +(skyrl_entrypoint pid=1712105) dropout: 0 +(skyrl_entrypoint pid=1712105) target_modules: all-linear +(skyrl_entrypoint pid=1712105) exclude_modules: null +(skyrl_entrypoint pid=1712105) deepspeed_config: ${deepspeed_config.train} +(skyrl_entrypoint pid=1712105) optimizer_config: +(skyrl_entrypoint pid=1712105) optimizer: AdamW +(skyrl_entrypoint pid=1712105) lr: 5.0e-06 +(skyrl_entrypoint pid=1712105) adam_betas: +(skyrl_entrypoint pid=1712105) - 0.9 +(skyrl_entrypoint pid=1712105) - 0.999 +(skyrl_entrypoint pid=1712105) weight_decay: 0.01 +(skyrl_entrypoint pid=1712105) max_grad_norm: 1.0 +(skyrl_entrypoint pid=1712105) offload_after_step: true +(skyrl_entrypoint pid=1712105) num_warmup_steps: 0 +(skyrl_entrypoint pid=1712105) scheduler: constant_with_warmup +(skyrl_entrypoint pid=1712105) optimizer_kwargs: {} +(skyrl_entrypoint pid=1712105) fsdp_config: +(skyrl_entrypoint pid=1712105) cpu_offload: false +(skyrl_entrypoint pid=1712105) reshard_after_forward: true +(skyrl_entrypoint pid=1712105) fsdp_size: -1 +(skyrl_entrypoint pid=1712105) expert_model_parallel_size: 1 +(skyrl_entrypoint pid=1712105) expert_tensor_parallel_size: 1 +(skyrl_entrypoint pid=1712105) moe_token_dispatcher_type: alltoall +(skyrl_entrypoint pid=1712105) moe_router_replay: false +(skyrl_entrypoint pid=1712105) moe_grouped_gemm: false +(skyrl_entrypoint pid=1712105) ep_comm_backend: torch +(skyrl_entrypoint pid=1712105) deepep_num_sms: 20 +(skyrl_entrypoint pid=1712105) deepep_token_chunk_size: null +(skyrl_entrypoint pid=1712105) context_parallel_size: 1 +(skyrl_entrypoint pid=1712105) cp_style: ring_sdpa +(skyrl_entrypoint pid=1712105) cp_rotate_method: allgather +(skyrl_entrypoint pid=1712105) sequence_parallel_size: 1 +(skyrl_entrypoint pid=1712105) algorithm: +(skyrl_entrypoint pid=1712105) advantage_estimator: rloo_n +(skyrl_entrypoint pid=1712105) kl_ctrl: +(skyrl_entrypoint pid=1712105) type: fixed +(skyrl_entrypoint pid=1712105) kl_target: 0.1 +(skyrl_entrypoint pid=1712105) horizon: 10000 +(skyrl_entrypoint pid=1712105) kl_estimator_type: k3 +(skyrl_entrypoint pid=1712105) use_kl_estimator_k3: false +(skyrl_entrypoint pid=1712105) use_abs_kl: false +(skyrl_entrypoint pid=1712105) use_kl_in_reward: false +(skyrl_entrypoint pid=1712105) use_kl_loss: false +(skyrl_entrypoint pid=1712105) kl_loss_coef: 0.0 +(skyrl_entrypoint pid=1712105) use_entropy_loss: false +(skyrl_entrypoint pid=1712105) entropy_loss_coef: 0.01 +(skyrl_entrypoint pid=1712105) advantage_batch_normalize: false +(skyrl_entrypoint pid=1712105) value_head_prefix: value_head +(skyrl_entrypoint pid=1712105) policy_loss_type: regular +(skyrl_entrypoint pid=1712105) loss_reduction: seq_mean_token_sum_norm_global +(skyrl_entrypoint pid=1712105) global_loss_denom: null +(skyrl_entrypoint pid=1712105) grpo_norm_by_std: true +(skyrl_entrypoint pid=1712105) rloo_n_min_group_size: 4 +(skyrl_entrypoint pid=1712105) rloo_n_filter_zero_reward_groups: true +(skyrl_entrypoint pid=1712105) lambd: 1.0 +(skyrl_entrypoint pid=1712105) gamma: 1.0 +(skyrl_entrypoint pid=1712105) eps_clip_low: 0.2 +(skyrl_entrypoint pid=1712105) eps_clip_high: 0.2 +(skyrl_entrypoint pid=1712105) clip_ratio_c: 3.0 +(skyrl_entrypoint pid=1712105) tis_imp_ratio_cap: 2.0 +(skyrl_entrypoint pid=1712105) use_tis: true +(skyrl_entrypoint pid=1712105) sapo: +(skyrl_entrypoint pid=1712105) tau_pos: 1.0 +(skyrl_entrypoint pid=1712105) tau_neg: 1.05 +(skyrl_entrypoint pid=1712105) value_clip: 0.2 +(skyrl_entrypoint pid=1712105) dynamic_sampling: +(skyrl_entrypoint pid=1712105) type: null +(skyrl_entrypoint pid=1712105) max_sample_batches: 30 +(skyrl_entrypoint pid=1712105) min_replace_ratio: 0.3 +(skyrl_entrypoint pid=1712105) clip_cov: +(skyrl_entrypoint pid=1712105) clip_ratio: 0.0002 +(skyrl_entrypoint pid=1712105) clip_cov_lb: 1.0 +(skyrl_entrypoint pid=1712105) clip_cov_ub: 5.0 +(skyrl_entrypoint pid=1712105) kl_cov: +(skyrl_entrypoint pid=1712105) kl_cov_frac: 0.2 +(skyrl_entrypoint pid=1712105) ppo_kl_coef: 1.0 +(skyrl_entrypoint pid=1712105) cispo: +(skyrl_entrypoint pid=1712105) cispo_eps_clip_low: 0 +(skyrl_entrypoint pid=1712105) cispo_eps_clip_high: 5 +(skyrl_entrypoint pid=1712105) z_clip: +(skyrl_entrypoint pid=1712105) enabled: false +(skyrl_entrypoint pid=1712105) alpha: 0.97 +(skyrl_entrypoint pid=1712105) z_thresh: 2.5 +(skyrl_entrypoint pid=1712105) warmup_steps: 25 +(skyrl_entrypoint pid=1712105) mode: zscore +(skyrl_entrypoint pid=1712105) clip_option: adaptive_scaling +(skyrl_entrypoint pid=1712105) clip_factor: 1.0 +(skyrl_entrypoint pid=1712105) skip_update_on_spike: false +(skyrl_entrypoint pid=1712105) stale_clip: +(skyrl_entrypoint pid=1712105) enabled: false +(skyrl_entrypoint pid=1712105) alpha: 0.3 +(skyrl_entrypoint pid=1712105) entropy_threshold: 0.15 +(skyrl_entrypoint pid=1712105) entropy_window: 10 +(skyrl_entrypoint pid=1712105) min_lr_scale: 0.1 +(skyrl_entrypoint pid=1712105) max_seq_len: 1004095 +(skyrl_entrypoint pid=1712105) fully_async: +(skyrl_entrypoint pid=1712105) max_staleness_steps: 16 +(skyrl_entrypoint pid=1712105) num_parallel_generation_workers: 338 +(skyrl_entrypoint pid=1712105) gradient_checkpointing: true +(skyrl_entrypoint pid=1712105) gradient_checkpointing_use_reentrant: false +(skyrl_entrypoint pid=1712105) seed: 42 +(skyrl_entrypoint pid=1712105) resume_mode: latest +(skyrl_entrypoint pid=1712105) resume_path: null +(skyrl_entrypoint pid=1712105) ckpt_path: /e/data1/datasets/playground/ot-baf/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/checkpoints +(skyrl_entrypoint pid=1712105) max_ckpts_to_keep: -1 +(skyrl_entrypoint pid=1712105) ckpt_interval: 2 +(skyrl_entrypoint pid=1712105) hf_save_interval: 5 +(skyrl_entrypoint pid=1712105) hf_upload_mode: latest +(skyrl_entrypoint pid=1712105) export_path: /e/data1/datasets/playground/ot-baf/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/exports +(skyrl_entrypoint pid=1712105) bf16: true +(skyrl_entrypoint pid=1712105) epochs: 2 +(skyrl_entrypoint pid=1712105) max_steps: 80 +(skyrl_entrypoint pid=1712105) update_epochs_per_batch: 1 +(skyrl_entrypoint pid=1712105) train_batch_size: 64 +(skyrl_entrypoint pid=1712105) policy_mini_batch_size: 64 +(skyrl_entrypoint pid=1712105) critic_mini_batch_size: 256 +(skyrl_entrypoint pid=1712105) micro_train_batch_size_per_gpu: 1 +(skyrl_entrypoint pid=1712105) micro_forward_batch_size_per_gpu: 4 +(skyrl_entrypoint pid=1712105) update_ref_every_epoch: false +(skyrl_entrypoint pid=1712105) use_sample_packing: true +(skyrl_entrypoint pid=1712105) eval_batch_size: 64 +(skyrl_entrypoint pid=1712105) eval_before_train: false +(skyrl_entrypoint pid=1712105) eval_interval: 999999 +(skyrl_entrypoint pid=1712105) max_prompt_length: 999999 +(skyrl_entrypoint pid=1712105) flash_attn: true +(skyrl_entrypoint pid=1712105) attn_backend: auto +(skyrl_entrypoint pid=1712105) disable_fast_tokenizer: false +(skyrl_entrypoint pid=1712105) target_modules: null +(skyrl_entrypoint pid=1712105) exclude_modules: null +(skyrl_entrypoint pid=1712105) project_name: OpenThoughts-Agent +(skyrl_entrypoint pid=1712105) run_name: rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san +(skyrl_entrypoint pid=1712105) logger: console +(skyrl_entrypoint pid=1712105) tracker_commit_each_step: true +(skyrl_entrypoint pid=1712105) dump_data_batch: false +(skyrl_entrypoint pid=1712105) dump_eval_results: true +(skyrl_entrypoint pid=1712105) log_level: INFO +(skyrl_entrypoint pid=1712105) rope_scaling: null +(skyrl_entrypoint pid=1712105) rope_theta: null +(skyrl_entrypoint pid=1712105) step_wise_training: false +(skyrl_entrypoint pid=1712105) hf_hub_repo_id: laion/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san +(skyrl_entrypoint pid=1712105) hf_hub_private: false +(skyrl_entrypoint pid=1712105) hf_hub_revision: main +(skyrl_entrypoint pid=1712105) enable_db_registration: false +(skyrl_entrypoint pid=1712105) generator: +(skyrl_entrypoint pid=1712105) model_name: ${trainer.policy.model.path} +(skyrl_entrypoint pid=1712105) model_dtype: bfloat16 +(skyrl_entrypoint pid=1712105) timeout_multiplier: 1.0 +(skyrl_entrypoint pid=1712105) run_engines_locally: true +(skyrl_entrypoint pid=1712105) num_inference_engines: 48 +(skyrl_entrypoint pid=1712105) backend: vllm +(skyrl_entrypoint pid=1712105) weight_sync_backend: nccl +(skyrl_entrypoint pid=1712105) fuse_weights: false +(skyrl_entrypoint pid=1712105) weight_transfer_threshold_cuda_ipc_GB: 1.0 +(skyrl_entrypoint pid=1712105) inference_engine_tensor_parallel_size: 1 +(skyrl_entrypoint pid=1712105) inference_engine_pipeline_parallel_size: 1 +(skyrl_entrypoint pid=1712105) inference_engine_expert_parallel_size: 1 +(skyrl_entrypoint pid=1712105) inference_engine_data_parallel_size: 1 +(skyrl_entrypoint pid=1712105) inference_engine_decode_context_parallel_size: 1 +(skyrl_entrypoint pid=1712105) inference_engine_mp_backend: false +(skyrl_entrypoint pid=1712105) n_samples_per_prompt: 8 +(skyrl_entrypoint pid=1712105) async_engine: true +(skyrl_entrypoint pid=1712105) batched: false +(skyrl_entrypoint pid=1712105) max_input_length: ${trainer.max_prompt_length} +(skyrl_entrypoint pid=1712105) vllm_v1_disable_multiproc: true +(skyrl_entrypoint pid=1712105) enable_prefix_caching: true +(skyrl_entrypoint pid=1712105) enable_chunked_prefill: true +(skyrl_entrypoint pid=1712105) max_num_batched_tokens: 65536 +(skyrl_entrypoint pid=1712105) enforce_eager: true +(skyrl_entrypoint pid=1712105) fully_sharded_loras: false +(skyrl_entrypoint pid=1712105) enable_ray_prometheus_stats: false +(skyrl_entrypoint pid=1712105) vllm_stats_interval: 1 +(skyrl_entrypoint pid=1712105) gpu_memory_utilization: 0.75 +(skyrl_entrypoint pid=1712105) max_num_seqs: 24 +(skyrl_entrypoint pid=1712105) remote_inference_engine_urls: +(skyrl_entrypoint pid=1712105) - 127.0.0.1:8001 +(skyrl_entrypoint pid=1712105) enable_http_endpoint: true +(skyrl_entrypoint pid=1712105) http_endpoint_host: 127.0.0.1 +(skyrl_entrypoint pid=1712105) http_endpoint_port: 8000 +(skyrl_entrypoint pid=1712105) max_turns: 999999 +(skyrl_entrypoint pid=1712105) chat_template: +(skyrl_entrypoint pid=1712105) source: name +(skyrl_entrypoint pid=1712105) name_or_path: null +(skyrl_entrypoint pid=1712105) chat_template_kwargs: {} +(skyrl_entrypoint pid=1712105) engine_init_kwargs: +(skyrl_entrypoint pid=1712105) max_model_len: 32768 +(skyrl_entrypoint pid=1712105) custom_chat_template_chat_completion_path: chat_templates/qwen3_thinking_acc.jinja2 +(skyrl_entrypoint pid=1712105) served_model_name: 0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6 +(skyrl_entrypoint pid=1712105) override_existing_update_group: disable +(skyrl_entrypoint pid=1712105) sampling_params: +(skyrl_entrypoint pid=1712105) max_generate_length: 4096 +(skyrl_entrypoint pid=1712105) repetition_penalty: 1.0 +(skyrl_entrypoint pid=1712105) temperature: 1.0 +(skyrl_entrypoint pid=1712105) top_p: 1.0 +(skyrl_entrypoint pid=1712105) min_p: 0.0 +(skyrl_entrypoint pid=1712105) top_k: -1 +(skyrl_entrypoint pid=1712105) logprobs: 0 +(skyrl_entrypoint pid=1712105) stop: null +(skyrl_entrypoint pid=1712105) use_conversation_multi_turn: true +(skyrl_entrypoint pid=1712105) append_eos_token_after_stop_str_in_multi_turn: true +(skyrl_entrypoint pid=1712105) eval_sampling_params: +(skyrl_entrypoint pid=1712105) max_generate_length: ${generator.sampling_params.max_generate_length} +(skyrl_entrypoint pid=1712105) repetition_penalty: 1.0 +(skyrl_entrypoint pid=1712105) temperature: 0.0 +(skyrl_entrypoint pid=1712105) top_p: 1.0 +(skyrl_entrypoint pid=1712105) min_p: 0.0 +(skyrl_entrypoint pid=1712105) top_k: -1 +(skyrl_entrypoint pid=1712105) logprobs: null +(skyrl_entrypoint pid=1712105) stop: null +(skyrl_entrypoint pid=1712105) eval_n_samples_per_prompt: 8 +(skyrl_entrypoint pid=1712105) zero_reward_on_non_stop: false +(skyrl_entrypoint pid=1712105) apply_overlong_filtering: false +(skyrl_entrypoint pid=1712105) rope_scaling: ${trainer.rope_scaling} +(skyrl_entrypoint pid=1712105) rope_theta: ${trainer.rope_theta} +(skyrl_entrypoint pid=1712105) teacher: +(skyrl_entrypoint pid=1712105) model_path: null +(skyrl_entrypoint pid=1712105) top_k_logprobs: 256 +(skyrl_entrypoint pid=1712105) num_inference_engines: 1 +(skyrl_entrypoint pid=1712105) inference_engine_tensor_parallel_size: 1 +(skyrl_entrypoint pid=1712105) inference_engine_pipeline_parallel_size: 1 +(skyrl_entrypoint pid=1712105) gpu_memory_utilization: 0.9 +(skyrl_entrypoint pid=1712105) enforce_eager: false +(skyrl_entrypoint pid=1712105) backend: vllm +(skyrl_entrypoint pid=1712105) engine_init_kwargs: {} +(skyrl_entrypoint pid=1712105) environment: +(skyrl_entrypoint pid=1712105) env_class: gsm8k +(skyrl_entrypoint pid=1712105) skyrl_gym: +(skyrl_entrypoint pid=1712105) max_env_workers: 32 +(skyrl_entrypoint pid=1712105) text2sql: +(skyrl_entrypoint pid=1712105) db_path: /home/ray/default/sql_data +(skyrl_entrypoint pid=1712105) llm_as_a_judge: +(skyrl_entrypoint pid=1712105) model: gpt-4o-mini +(skyrl_entrypoint pid=1712105) base_url: null +(skyrl_entrypoint pid=1712105) search: +(skyrl_entrypoint pid=1712105) log_requests: false +(skyrl_entrypoint pid=1712105) search_url: http://127.0.0.1:8000/retrieve +(skyrl_entrypoint pid=1712105) topk: 3 +(skyrl_entrypoint pid=1712105) timeout: 30 +(skyrl_entrypoint pid=1712105) rollout: +(skyrl_entrypoint pid=1712105) fanout: +(skyrl_entrypoint pid=1712105) enabled: true +(skyrl_entrypoint pid=1712105) num_coordinators: 4 +(skyrl_entrypoint pid=1712105) cpus_per_coordinator: 8 +(skyrl_entrypoint pid=1712105) deepspeed_config: +(skyrl_entrypoint pid=1712105) train: +(skyrl_entrypoint pid=1712105) zero_optimization: +(skyrl_entrypoint pid=1712105) stage: 3 +(skyrl_entrypoint pid=1712105) offload_param: +(skyrl_entrypoint pid=1712105) device: none +(skyrl_entrypoint pid=1712105) offload_optimizer: +(skyrl_entrypoint pid=1712105) device: none +(skyrl_entrypoint pid=1712105) pin_memory: true +(skyrl_entrypoint pid=1712105) sub_group_size: auto +(skyrl_entrypoint pid=1712105) reduce_bucket_size: auto +(skyrl_entrypoint pid=1712105) stage3_param_persistence_threshold: auto +(skyrl_entrypoint pid=1712105) stage3_prefetch_bucket_size: auto +(skyrl_entrypoint pid=1712105) stage3_max_live_parameters: auto +(skyrl_entrypoint pid=1712105) stage3_max_reuse_distance: auto +(skyrl_entrypoint pid=1712105) round_robin_gradients: true +(skyrl_entrypoint pid=1712105) zero_hpz_partition_size: 1 +(skyrl_entrypoint pid=1712105) zero_quantized_weights: false +(skyrl_entrypoint pid=1712105) zero_quantized_gradients: false +(skyrl_entrypoint pid=1712105) torch_autocast: +(skyrl_entrypoint pid=1712105) enabled: true +(skyrl_entrypoint pid=1712105) dtype: bfloat16 +(skyrl_entrypoint pid=1712105) disable_trace_cache: false +(skyrl_entrypoint pid=1712105) data_types: +(skyrl_entrypoint pid=1712105) grad_accum_dtype: fp32 +(skyrl_entrypoint pid=1712105) gradient_clipping: 1.0 +(skyrl_entrypoint pid=1712105) wall_clock_breakdown: false +(skyrl_entrypoint pid=1712105) prescale_gradient: false +(skyrl_entrypoint pid=1712105) eval: +(skyrl_entrypoint pid=1712105) zero_optimization: +(skyrl_entrypoint pid=1712105) stage: 3 +(skyrl_entrypoint pid=1712105) stage3_param_persistence_threshold: auto +(skyrl_entrypoint pid=1712105) offload_param: +(skyrl_entrypoint pid=1712105) device: cpu +(skyrl_entrypoint pid=1712105) pin_memory: true +(skyrl_entrypoint pid=1712105) torch_autocast: +(skyrl_entrypoint pid=1712105) enabled: true +(skyrl_entrypoint pid=1712105) dtype: bfloat16 +(skyrl_entrypoint pid=1712105) gradient_clipping: 1.0 +(skyrl_entrypoint pid=1712105) prescale_gradient: false +(skyrl_entrypoint pid=1712105) wall_clock_breakdown: false +(skyrl_entrypoint pid=1712105) terminal_bench_config: +(skyrl_entrypoint pid=1712105) trials_dir: /e/data1/datasets/playground/ot-baf/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/trace_jobs +(skyrl_entrypoint pid=1712105) harbor: +(skyrl_entrypoint pid=1712105) name: terminus-2 +(skyrl_entrypoint pid=1712105) max_episodes: 999999 +(skyrl_entrypoint pid=1712105) enable_summarize: false +(skyrl_entrypoint pid=1712105) store_all_messages: true +(skyrl_entrypoint pid=1712105) trajectory_config: +(skyrl_entrypoint pid=1712105) raw_content: true +(skyrl_entrypoint pid=1712105) enable_episode_logging: false +(skyrl_entrypoint pid=1712105) record_terminal_session: false +(skyrl_entrypoint pid=1712105) enable_pane_logging: false +(skyrl_entrypoint pid=1712105) strict_json_parser: true +(skyrl_entrypoint pid=1712105) interleaved_thinking: true +(skyrl_entrypoint pid=1712105) extra_body: +(skyrl_entrypoint pid=1712105) chat_template_kwargs: +(skyrl_entrypoint pid=1712105) enable_thinking: true +(skyrl_entrypoint pid=1712105) override_timeout_sec: 900 +(skyrl_entrypoint pid=1712105) override_cpus: 1 +(skyrl_entrypoint pid=1712105) override_memory_mb: 2048 +(skyrl_entrypoint pid=1712105) override_storage_mb: 2048 +(skyrl_entrypoint pid=1712105) auto_snapshot: true +(skyrl_entrypoint pid=1712105) verifier_override_timeout_sec: 120 +(skyrl_entrypoint pid=1712105) max_retries: 3 +(skyrl_entrypoint pid=1712105) min_wait_sec: 60.0 +(skyrl_entrypoint pid=1712105) max_wait_sec: 600.0 +(skyrl_entrypoint pid=1712105) wait_multiplier: 2.0 +(skyrl_entrypoint pid=1712105) exclude_exceptions: +(skyrl_entrypoint pid=1712105) - VerifierTimeoutError +(skyrl_entrypoint pid=1712105) - VerifierRuntimeError +(skyrl_entrypoint pid=1712105) - RewardFileNotFoundError +(skyrl_entrypoint pid=1712105) - RewardFileEmptyError +(skyrl_entrypoint pid=1712105) - VerifierOutputParseError +(skyrl_entrypoint pid=1712105) n_concurrent_trials: 675 +(skyrl_entrypoint pid=1712105) log_level: INFO +(skyrl_entrypoint pid=1712105) enable_reward_shaping: true +(skyrl_entrypoint pid=1712105) reward_shaper: composite_loop +(skyrl_entrypoint pid=1712105) loop_outcome_shaper: original +(skyrl_entrypoint pid=1712105) loop_shaping: +(skyrl_entrypoint pid=1712105) outcome_weight: 1.0 +(skyrl_entrypoint pid=1712105) total_shaping_cap: 0.3 +(skyrl_entrypoint pid=1712105) terminate: +(skyrl_entrypoint pid=1712105) enabled: true +(skyrl_entrypoint pid=1712105) green_bonus: 0.3 +(skyrl_entrypoint pid=1712105) red_penalty: 0.3 +(skyrl_entrypoint pid=1712105) noterm_penalty: 0.2 +(skyrl_entrypoint pid=1712105) antithrash: +(skyrl_entrypoint pid=1712105) enabled: true +(skyrl_entrypoint pid=1712105) per_repeat_penalty: 0.02 +(skyrl_entrypoint pid=1712105) cap: 0.1 +(skyrl_entrypoint pid=1712105) collect_rollout_details: true +(skyrl_entrypoint pid=1712105) enable_error_classification: true +(skyrl_entrypoint pid=1712105) mask_exceptions: +(skyrl_entrypoint pid=1712105) - DaytonaError +(skyrl_entrypoint pid=1712105) - EnvironmentStartTimeoutError +(skyrl_entrypoint pid=1712105) - NetworkError +(skyrl_entrypoint pid=1712105) - ConnectionError +(skyrl_entrypoint pid=1712105) - RewardFileNotFoundError +(skyrl_entrypoint pid=1712105) - RewardFileEmptyError +(skyrl_entrypoint pid=1712105) - AgentEnvironmentTimeoutError +(skyrl_entrypoint pid=1712105) - ContextLengthExceededError +(skyrl_entrypoint pid=1712105) default_error_treatment: zero +(skyrl_entrypoint pid=1712105) passthrough_exceptions: +(skyrl_entrypoint pid=1712105) - AgentTimeoutError +(skyrl_entrypoint pid=1712105) zero_exceptions: [] +(skyrl_entrypoint pid=1712105) model_info: +(skyrl_entrypoint pid=1712105) max_input_tokens: 32000 +(skyrl_entrypoint pid=1712105) max_output_tokens: 4096 +(skyrl_entrypoint pid=1712105) archiving: +(skyrl_entrypoint pid=1712105) enabled: false +(skyrl_entrypoint pid=1712105) trace_upload: +(skyrl_entrypoint pid=1712105) enabled: true +(skyrl_entrypoint pid=1712105) repo_org: DCAgent +(skyrl_entrypoint pid=1712105) episodes: last +(skyrl_entrypoint pid=1712105) dataset_type: SFT +(skyrl_entrypoint pid=1712105) cleanup: true +(skyrl_entrypoint pid=1712105)  +(skyrl_entrypoint pid=1712105) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/__init__.py:7: RuntimeWarning: Failed to read commit hash: +(skyrl_entrypoint pid=1712105) No module named 'vllm._version' +(skyrl_entrypoint pid=1712105) from .version import __version__, __version_tuple__ # isort:skip +(pid=1695635) [2026-06-14 04:06:04,884 E 1695635 1697234] core_worker_process.cc:842: Failed to establish connection to the metrics exporter agent. Metrics will not be exported. Exporter agent status: RpcError: Running out of retries to initialize the metrics agent. rpc_code: 14 [repeated 18x across cluster] +(skyrl_entrypoint pid=1712105) W0614 04:06:05.300000 1712105 envs/rl/lib/python3.12/site-packages/torch/utils/cpp_extension.py:117] No CUDA runtime is found, using CUDA_HOME='/e/software/default/stages/2026/software/CUDA/13' +(raylet) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e +(raylet) 2026-06-14 04:06:07,362 WARNING node.py:1846 -- The object spilling config is specified from an unstable API - system config or environment variable. This is subject to change in the future. You can use the stable API - --object-spilling-directory in ray start or object_spilling_directory in ray.init() to specify the object spilling directory instead. If you need more advanced settings, please open a github issue with the Ray team. +(pid=1695802) [2026-06-14 04:06:08,184 E 1695802 1710802] core_worker_process.cc:842: Failed to establish connection to the metrics exporter agent. Metrics will not be exported. Exporter agent status: RpcError: Running out of retries to initialize the metrics agent. rpc_code: 14 [repeated 268x across cluster] +(raylet, ip=10.128.34.185) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e [repeated 41x across cluster] +(raylet, ip=10.128.34.185) 2026-06-14 04:06:11,675 WARNING node.py:1846 -- The object spilling config is specified from an unstable API - system config or environment variable. This is subject to change in the future. You can use the stable API - --object-spilling-directory in ray start or object_spilling_directory in ray.init() to specify the object spilling directory instead. If you need more advanced settings, please open a github issue with the Ray team. [repeated 6x across cluster] +(pid=153532, ip=10.128.56.65) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/__init__.py:7: RuntimeWarning: Failed to read commit hash: +(pid=153532, ip=10.128.56.65) No module named 'vllm._version' +(pid=153532, ip=10.128.56.65) from .version import __version__, __version_tuple__ # isort:skip +(raylet, ip=10.128.34.183) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e [repeated 78x across cluster] +(raylet, ip=10.128.34.179) 2026-06-14 04:06:17,497 WARNING node.py:1846 -- The object spilling config is specified from an unstable API - system config or environment variable. This is subject to change in the future. You can use the stable API - --object-spilling-directory in ray start or object_spilling_directory in ray.init() to specify the object spilling directory instead. If you need more advanced settings, please open a github issue with the Ray team. [repeated 18x across cluster] +(pid=153669, ip=10.128.56.65) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/__init__.py:7: RuntimeWarning: Failed to read commit hash: [repeated 8x across cluster] +(pid=153669, ip=10.128.56.65) No module named 'vllm._version' [repeated 8x across cluster] +(pid=153669, ip=10.128.56.65) from .version import __version__, __version_tuple__ # isort:skip [repeated 8x across cluster] +[2026-06-14 04:06:20,392 E 1711755 1712079] core_worker_process.cc:842: Failed to establish connection to the metrics exporter agent. Metrics will not be exported. Exporter agent status: RpcError: Running out of retries to initialize the metrics agent. rpc_code: 14 +(RegistryActor pid=3945653, ip=10.128.56.73) [2026-06-14 04:06:21,117 E 3945653 3945693] core_worker_process.cc:842: Failed to establish connection to the metrics exporter agent. Metrics will not be exported. Exporter agent status: RpcError: Running out of retries to initialize the metrics agent. rpc_code: 14 +(raylet, ip=10.128.34.182) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e [repeated 90x across cluster] +(raylet, ip=10.128.56.67) 2026-06-14 04:06:23,282 WARNING node.py:1846 -- The object spilling config is specified from an unstable API - system config or environment variable. This is subject to change in the future. You can use the stable API - --object-spilling-directory in ray start or object_spilling_directory in ray.init() to specify the object spilling directory instead. If you need more advanced settings, please open a github issue with the Ray team. [repeated 12x across cluster] +(pid=3942257, ip=10.128.56.76) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/__init__.py:7: RuntimeWarning: Failed to read commit hash: [repeated 15x across cluster] +(pid=3942257, ip=10.128.56.76) No module named 'vllm._version' [repeated 15x across cluster] +(pid=3942257, ip=10.128.56.76) from .version import __version__, __version_tuple__ # isort:skip [repeated 15x across cluster] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) 2026-06-14 04:06:24.492 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:152 - setup_envvars_for_vllm: distributed_executor_backend=uni, SKYRL_ENABLE_NUMA_AFFINITY=1, CUDA_VISIBLE_DEVICES=0, VLLM_ENABLE_V1_MULTIPROCESSING= +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) 2026-06-14 04:06:24.494 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:167 - setup_envvars_for_vllm: numa_enabled=True +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) 2026-06-14 04:06:24.494 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:170 - setup_envvars_for_vllm: set VLLM_ENABLE_V1_MULTIPROCESSING=0 for NUMA affinity +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) 2026-06-14 04:06:25.458 | INFO | skyrl_train.utils.numa:set_numa_affinity_for_gpu:340 - NUMA affinity: bound process to CPUs 0-71 (NUMA node 0) for GPU 0 +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) 2026-06-14 04:06:25.482 | DEBUG | skyrl_train.utils.numa:_set_membind_via_libnuma:375 - NUMA affinity: set memory preferred to NUMA node 0 +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) 2026-06-14 04:06:25.482 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:618 - BaseVLLMInferenceEngine: vllm_v1_disable_multiproc=True, vllm.__version__=dev, VLLM_ENABLE_V1_MULTIPROCESSING=0 +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) 2026-06-14 04:06:25.482 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:626 - BaseVLLMInferenceEngine: set VLLM_ENABLE_V1_MULTIPROCESSING=0 +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) 2026-06-14 04:06:25.482 | WARNING | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1192 - OpenAI API sampling params overridden: temperature=1.0, top_p=1.0, top_k=-1 +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) 2026-06-14 04:06:25.510 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1244 - Engine startup stagger: sleeping 2.96s (attempt 1/5) to avoid port collisions +(skyrl_entrypoint pid=1712105) [2026-06-14 04:06:22,884 E 1712105 1712148] core_worker_process.cc:842: Failed to establish connection to the metrics exporter agent. Metrics will not be exported. Exporter agent status: RpcError: Running out of retries to initialize the metrics agent. rpc_code: 14 [repeated 2x across cluster] +(raylet, ip=10.128.34.181) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e [repeated 57x across cluster] +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) The argument `trust_remote_code` is to be used with Auto classes. It has no effect here and is ignored. +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) The argument `trust_remote_code` is to be used with Auto classes. It has no effect here and is ignored. +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) The tokenizer you are loading from '/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. +(raylet, ip=10.128.56.66) 2026-06-14 04:06:27,907 WARNING node.py:1846 -- The object spilling config is specified from an unstable API - system config or environment variable. This is subject to change in the future. You can use the stable API - --object-spilling-directory in ray start or object_spilling_directory in ray.init() to specify the object spilling directory instead. If you need more advanced settings, please open a github issue with the Ray team. [repeated 16x across cluster] +(pid=1507676, ip=10.128.34.181) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/__init__.py:7: RuntimeWarning: Failed to read commit hash: [repeated 16x across cluster] +(pid=1507676, ip=10.128.34.181) No module named 'vllm._version' [repeated 16x across cluster] +(pid=1507676, ip=10.128.34.181) from .version import __version__, __version_tuple__ # isort:skip [repeated 16x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) 2026-06-14 04:06:29.440 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:152 - setup_envvars_for_vllm: distributed_executor_backend=uni, SKYRL_ENABLE_NUMA_AFFINITY=1, CUDA_VISIBLE_DEVICES=0, VLLM_ENABLE_V1_MULTIPROCESSING= [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) 2026-06-14 04:06:29.441 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:167 - setup_envvars_for_vllm: numa_enabled=True [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) 2026-06-14 04:06:29.441 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:170 - setup_envvars_for_vllm: set VLLM_ENABLE_V1_MULTIPROCESSING=0 for NUMA affinity [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) 2026-06-14 04:06:30.591 | INFO | skyrl_train.utils.numa:set_numa_affinity_for_gpu:340 - NUMA affinity: bound process to CPUs 0-71 (NUMA node 0) for GPU 0 [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) 2026-06-14 04:06:30.615 | DEBUG | skyrl_train.utils.numa:_set_membind_via_libnuma:375 - NUMA affinity: set memory preferred to NUMA node 0 [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) 2026-06-14 04:06:30.616 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:618 - BaseVLLMInferenceEngine: vllm_v1_disable_multiproc=True, vllm.__version__=dev, VLLM_ENABLE_V1_MULTIPROCESSING=0 [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) 2026-06-14 04:06:30.616 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:626 - BaseVLLMInferenceEngine: set VLLM_ENABLE_V1_MULTIPROCESSING=0 [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) 2026-06-14 04:06:30.616 | WARNING | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1192 - OpenAI API sampling params overridden: temperature=1.0, top_p=1.0, top_k=-1 [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) 2026-06-14 04:06:28.108 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1244 - Engine startup stagger: sleeping 2.19s (attempt 1/5) to avoid port collisions [repeated 7x across cluster] +(skyrl_entrypoint pid=1712105) [2026-06-14 04:06:31] INFO inference_engine_client_http_endpoint.py:350: Starting server on 0.0.0.0:8000 +(skyrl_entrypoint pid=1712105) [2026-06-14 04:06:31] INFO inference_engine_client_http_endpoint.py:242: Starting inference HTTP endpoint... +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e [repeated 115x across cluster] +(skyrl_entrypoint pid=1712105) [2026-06-14 04:06:32] INFO inference_engine_client_http_endpoint.py:229: Server ready after 2 attempts (2 seconds) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:06:32.044 | INFO  | skyrl_train.inference_engines.inference_engine_client:_spin_up_http_endpoint:969 - InferenceEngineClient HTTP endpoint started on 127.0.0.1:8000 +(skyrl_entrypoint pid=1712105) 2026-06-14 04:06:32.044 | INFO  | skyrl_train.inference_engines.inference_engine_client:__init__:61 - InferenceEngineClient initialized with 48 engines. +(skyrl_entrypoint pid=1712105) 2026-06-14 04:06:32.046 | INFO  | examples.terminal_bench.terminal_bench_generator:_configure_harbor_logging:316 - Harbor logging level set to INFO +(skyrl_entrypoint pid=1712105) 2026-06-14 04:06:32.047 | INFO  | examples.terminal_bench.terminal_bench_generator:__init__:212 - TerminalBenchGenerator initialized with HarborConfigBuilder. Exposed fields: ['name', 'max_episodes', 'enable_summarize', 'store_all_messages', 'trajectory_config', 'enable_episode_logging', 'record_terminal_session', 'enable_pane_logging', 'strict_json_parser', 'interleaved_thinking', 'extra_body', 'override_timeout_sec', 'override_cpus', 'override_memory_mb', 'override_storage_mb', 'auto_snapshot', 'verifier_override_timeout_sec', 'max_retries', 'min_wait_sec', 'max_wait_sec', 'wait_multiplier', 'exclude_exceptions', 'n_concurrent_trials', 'log_level', 'enable_reward_shaping', 'reward_shaper', 'loop_outcome_shaper', 'loop_shaping', 'collect_rollout_details', 'enable_error_classification', 'mask_exceptions', 'default_error_treatment', 'passthrough_exceptions', 'zero_exceptions']. Retry config: max_retries=3, backoff=60.0-600.0s. Concurrent trials: 675. Reward shaping: enabled=True, shaper=composite_loop. Error classification: enabled=True +(skyrl_entrypoint pid=1712105) 2026-06-14 04:06:32.047 | INFO  | examples.terminal_bench.terminal_bench_generator:__init__:230 - TerminalBenchGenerator initialized with custom chat template read from: chat_templates/qwen3_thinking_acc.jinja2 +(skyrl_entrypoint pid=1712105) 2026-06-14 04:06:32.048 | INFO  | skyrl_train.utils.trainer_utils:build_dataloader:656 - Total steps: 156 +(skyrl_entrypoint pid=1712105) 2026-06-14 04:06:32.048 | INFO  | skyrl_train.fully_async_trainer:_build_train_dataloader_and_compute_training_steps:357 - Length of train_dataloader: 5000 +(skyrl_entrypoint pid=1712105) 2026-06-14 04:06:32.048 | INFO  | skyrl_train.fully_async_trainer:_build_train_dataloader_and_compute_training_steps:358 - Number of steps per epoch: 78 +(skyrl_entrypoint pid=1712105) 2026-06-14 04:06:32.048 | INFO  | skyrl_train.fully_async_trainer:_build_train_dataloader_and_compute_training_steps:359 - Total training steps: 80 +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) The argument `trust_remote_code` is to be used with Auto classes. It has no effect here and is ignored. [repeated 16x across cluster] +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) The tokenizer you are loading from '/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. [repeated 8x across cluster] +(raylet, ip=10.128.56.78) 2026-06-14 04:06:33,048 WARNING node.py:1846 -- The object spilling config is specified from an unstable API - system config or environment variable. This is subject to change in the future. You can use the stable API - --object-spilling-directory in ray start or object_spilling_directory in ray.init() to specify the object spilling directory instead. If you need more advanced settings, please open a github issue with the Ray team. [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/__init__.py:7: RuntimeWarning: Failed to read commit hash: [repeated 20x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) No module named 'vllm._version' [repeated 20x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) from .version import __version__, __version_tuple__ # isort:skip [repeated 20x across cluster] +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) 2026-06-14 04:06:34.109 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:152 - setup_envvars_for_vllm: distributed_executor_backend=uni, SKYRL_ENABLE_NUMA_AFFINITY=1, CUDA_VISIBLE_DEVICES=3, VLLM_ENABLE_V1_MULTIPROCESSING= [repeated 11x across cluster] +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) 2026-06-14 04:06:34.110 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:167 - setup_envvars_for_vllm: numa_enabled=True [repeated 11x across cluster] +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) 2026-06-14 04:06:34.110 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:170 - setup_envvars_for_vllm: set VLLM_ENABLE_V1_MULTIPROCESSING=0 for NUMA affinity [repeated 11x across cluster] +(pid=3949363, ip=10.128.56.78) Using blocking ray.get inside async actor. This blocks the event loop. Please use `await` on object ref with asyncio.gather if you want to yield execution to the event loop instead. +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) 2026-06-14 04:06:35.246 | INFO | skyrl_train.utils.numa:set_numa_affinity_for_gpu:340 - NUMA affinity: bound process to CPUs 216-287 (NUMA node 3) for GPU 3 [repeated 11x across cluster] +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) 2026-06-14 04:06:35.271 | DEBUG | skyrl_train.utils.numa:_set_membind_via_libnuma:375 - NUMA affinity: set memory preferred to NUMA node 3 [repeated 11x across cluster] +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) 2026-06-14 04:06:35.271 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:618 - BaseVLLMInferenceEngine: vllm_v1_disable_multiproc=True, vllm.__version__=dev, VLLM_ENABLE_V1_MULTIPROCESSING=0 [repeated 11x across cluster] +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) 2026-06-14 04:06:35.271 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:626 - BaseVLLMInferenceEngine: set VLLM_ENABLE_V1_MULTIPROCESSING=0 [repeated 11x across cluster] +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) 2026-06-14 04:06:35.271 | WARNING | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1192 - OpenAI API sampling params overridden: temperature=1.0, top_p=1.0, top_k=-1 [repeated 11x across cluster] +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) 2026-06-14 04:06:35.299 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1244 - Engine startup stagger: sleeping 2.23s (attempt 1/5) to avoid port collisions [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e [repeated 23x across cluster] +(bundle_reservation_check_func pid=1712179) [2026-06-14 04:06:37,381 E 1712179 1712219] core_worker_process.cc:842: Failed to establish connection to the metrics exporter agent. Metrics will not be exported. Exporter agent status: RpcError: Running out of retries to initialize the metrics agent. rpc_code: 14 +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) The argument `trust_remote_code` is to be used with Auto classes. It has no effect here and is ignored. [repeated 20x across cluster] +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) The tokenizer you are loading from '/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) (EngineCore_DP0 pid=153931) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/__init__.py:1617: UserWarning: Please use the new API settings to control TF32 behavior, such as torch.backends.cudnn.conv.fp32_precision = 'tf32' or torch.backends.cuda.matmul.fp32_precision = 'ieee'. Old settings, e.g, torch.backends.cuda.matmul.allow_tf32 = True, torch.backends.cudnn.allow_tf32 = True, allowTF32CuDNN() and allowTF32CuBLAS() will be deprecated after Pytorch 2.9. Please see https://pytorch.org/docs/main/notes/cuda.html#tensorfloat-32-tf32-on-ampere-and-later-devices (Triggered internally at /pytorch/aten/src/ATen/Context.cpp:80.) +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) (EngineCore_DP0 pid=153931) _C._set_float32_matmul_precision(precision) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/__init__.py:7: RuntimeWarning: Failed to read commit hash: [repeated 11x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) No module named 'vllm._version' [repeated 11x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) from .version import __version__, __version_tuple__ # isort:skip [repeated 11x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) 2026-06-14 04:06:37.930 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:152 - setup_envvars_for_vllm: distributed_executor_backend=uni, SKYRL_ENABLE_NUMA_AFFINITY=1, CUDA_VISIBLE_DEVICES=3, VLLM_ENABLE_V1_MULTIPROCESSING= [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) 2026-06-14 04:06:37.931 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:167 - setup_envvars_for_vllm: numa_enabled=True [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) 2026-06-14 04:06:37.931 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:170 - setup_envvars_for_vllm: set VLLM_ENABLE_V1_MULTIPROCESSING=0 for NUMA affinity [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=153669, ip=10.128.56.65) (EngineCore_DP0 pid=153939) _C._set_float32_matmul_precision(precision) +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) 2026-06-14 04:06:39.086 | INFO | skyrl_train.utils.numa:set_numa_affinity_for_gpu:340 - NUMA affinity: bound process to CPUs 216-287 (NUMA node 3) for GPU 3 [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) 2026-06-14 04:06:39.109 | DEBUG | skyrl_train.utils.numa:_set_membind_via_libnuma:375 - NUMA affinity: set memory preferred to NUMA node 3 [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) 2026-06-14 04:06:39.110 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:618 - BaseVLLMInferenceEngine: vllm_v1_disable_multiproc=True, vllm.__version__=dev, VLLM_ENABLE_V1_MULTIPROCESSING=0 [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) 2026-06-14 04:06:39.110 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:626 - BaseVLLMInferenceEngine: set VLLM_ENABLE_V1_MULTIPROCESSING=0 [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) 2026-06-14 04:06:39.110 | WARNING | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1192 - OpenAI API sampling params overridden: temperature=1.0, top_p=1.0, top_k=-1 [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) 2026-06-14 04:06:39.138 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1244 - Engine startup stagger: sleeping 2.29s (attempt 1/5) to avoid port collisions [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) (EngineCore_DP0 pid=1507543) _C._set_float32_matmul_precision(precision) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) (EngineCore_DP0 pid=153955) _C._set_float32_matmul_precision(precision) +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e [repeated 32x across cluster] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) [W614 04:06:42.911579847 socket.cpp:767] [c10d] The client socket cannot be initialized to connect to [jpbo-102-17-interconnect-1.jupiter.internal]:53647 (errno: 97 - Address family not supported by protocol). +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) [W614 04:06:42.912048991 Utils.hpp:166] Warning: Environment variable NCCL_BLOCKING_WAIT is deprecated; use TORCH_NCCL_BLOCKING_WAIT instead (function operator()) +(AsyncVLLMInferenceEngine pid=153669, ip=10.128.56.65) [rank0]:[W614 04:06:42.893831222 Utils.hpp:137] Warning: Environment variable TORCH_NCCL_TRACE_BUFFER_SIZE is deprecated; use TORCH_FR_BUFFER_SIZE instead (function operator()) +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) (EngineCore_DP0 pid=1507555) _C._set_float32_matmul_precision(precision) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) [2026-06-14 04:06:41,740 E 1507188 1507290] core_worker_process.cc:842: Failed to establish connection to the metrics exporter agent. Metrics will not be exported. Exporter agent status: RpcError: Running out of retries to initialize the metrics agent. rpc_code: 14 [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) (EngineCore_DP0 pid=153943) _C._set_float32_matmul_precision(precision) +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) The argument `trust_remote_code` is to be used with Auto classes. It has no effect here and is ignored. [repeated 26x across cluster] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) The tokenizer you are loading from '/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. [repeated 13x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) 2026-06-14 04:06:43 INFO [ipv4-debug] hostname=jpbo-102-30.jupiter.internal +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) 2026-06-14 04:06:43 INFO [ipv4-debug] _global_node.node_ip_address=10.128.56.78 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) 2026-06-14 04:06:43 INFO [ipv4-debug] get_node_ip_address()=10.128.56.78 +(skyrl_entrypoint pid=1712105) 2026-06-14 04:06:43.557 | INFO  | skyrl_train.workers.worker:_initiate_actors:637 - Initializing process group for RayActorGroup +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) (EngineCore_DP0 pid=1507824) _C._set_float32_matmul_precision(precision) +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) (EngineCore_DP0 pid=1507551) _C._set_float32_matmul_precision(precision) +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) (EngineCore_DP0 pid=153931) Loading safetensors checkpoint shards: 0% Completed | 0/4 [00:00 [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) 2026-06-14 04:06:41.823 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:167 - setup_envvars_for_vllm: numa_enabled=True [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) 2026-06-14 04:06:41.823 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:170 - setup_envvars_for_vllm: set VLLM_ENABLE_V1_MULTIPROCESSING=0 for NUMA affinity [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) (EngineCore_DP0 pid=1496303) _C._set_float32_matmul_precision(precision) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) (EngineCore_DP0 pid=1507560) _C._set_float32_matmul_precision(precision) +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) (EngineCore_DP0 pid=1496316) _C._set_float32_matmul_precision(precision) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) 2026-06-14 04:06:42.951 | INFO | skyrl_train.utils.numa:set_numa_affinity_for_gpu:340 - NUMA affinity: bound process to CPUs 216-287 (NUMA node 3) for GPU 3 [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) 2026-06-14 04:06:42.976 | DEBUG | skyrl_train.utils.numa:_set_membind_via_libnuma:375 - NUMA affinity: set memory preferred to NUMA node 3 [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) 2026-06-14 04:06:42.976 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:618 - BaseVLLMInferenceEngine: vllm_v1_disable_multiproc=True, vllm.__version__=dev, VLLM_ENABLE_V1_MULTIPROCESSING=0 [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) 2026-06-14 04:06:42.976 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:626 - BaseVLLMInferenceEngine: set VLLM_ENABLE_V1_MULTIPROCESSING=0 [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) 2026-06-14 04:06:42.976 | WARNING | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1192 - OpenAI API sampling params overridden: temperature=1.0, top_p=1.0, top_k=-1 [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) 2026-06-14 04:06:43.006 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1244 - Engine startup stagger: sleeping 1.53s (attempt 1/5) to avoid port collisions [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) (EngineCore_DP0 pid=1507832) _C._set_float32_matmul_precision(precision) +(pid=3949441, ip=10.128.56.78) Using blocking ray.get inside async actor. This blocks the event loop. Please use `await` on object ref with asyncio.gather if you want to yield execution to the event loop instead. +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) (EngineCore_DP0 pid=1507848) _C._set_float32_matmul_precision(precision) +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) (EngineCore_DP0 pid=1496308) _C._set_float32_matmul_precision(precision) +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e [repeated 58x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) [W614 04:06:46.626981556 socket.cpp:767] [c10d] The client socket cannot be initialized to connect to [jpbo-055-18.jupiter.internal]:60097 (errno: 97 - Address family not supported by protocol). [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) [W614 04:06:46.627432875 Utils.hpp:166] Warning: Environment variable NCCL_BLOCKING_WAIT is deprecated; use TORCH_NCCL_BLOCKING_WAIT instead (function operator()) [repeated 11x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) [rank0]:[W614 04:06:46.629934712 Utils.hpp:137] Warning: Environment variable TORCH_NCCL_TRACE_BUFFER_SIZE is deprecated; use TORCH_FR_BUFFER_SIZE instead (function operator()) [repeated 11x across cluster] +(get_addr_port pid=1507843, ip=10.128.34.179) [2026-06-14 04:06:47,480 E 1507843 1507891] core_worker_process.cc:842: Failed to establish connection to the metrics exporter agent. Metrics will not be exported. Exporter agent status: RpcError: Running out of retries to initialize the metrics agent. rpc_code: 14 [repeated 17x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) (EngineCore_DP0 pid=1496327) _C._set_float32_matmul_precision(precision) +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) The argument `trust_remote_code` is to be used with Auto classes. It has no effect here and is ignored. [repeated 18x across cluster] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) The tokenizer you are loading from '/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) (EngineCore_DP0 pid=3942493) _C._set_float32_matmul_precision(precision) +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) (EngineCore_DP0 pid=1496308) Loading safetensors checkpoint shards: 0% Completed | 0/4 [00:00 [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=4037604, ip=10.128.56.68) 2026-06-14 04:06:45.740 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:167 - setup_envvars_for_vllm: numa_enabled=True [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=4037604, ip=10.128.56.68) 2026-06-14 04:06:45.740 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:170 - setup_envvars_for_vllm: set VLLM_ENABLE_V1_MULTIPROCESSING=0 for NUMA affinity [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) (EngineCore_DP0 pid=3942487) _C._set_float32_matmul_precision(precision) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) (EngineCore_DP0 pid=153955) Loading safetensors checkpoint shards: 25% Completed | 1/4 [00:06<00:18, 6.23s/it] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) (EngineCore_DP0 pid=1497134) _C._set_float32_matmul_precision(precision) +(AsyncVLLMInferenceEngine pid=4037604, ip=10.128.56.68) 2026-06-14 04:06:46.890 | INFO | skyrl_train.utils.numa:set_numa_affinity_for_gpu:340 - NUMA affinity: bound process to CPUs 216-287 (NUMA node 3) for GPU 3 [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=4037604, ip=10.128.56.68) 2026-06-14 04:06:46.915 | DEBUG | skyrl_train.utils.numa:_set_membind_via_libnuma:375 - NUMA affinity: set memory preferred to NUMA node 3 [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=4037604, ip=10.128.56.68) 2026-06-14 04:06:46.915 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:618 - BaseVLLMInferenceEngine: vllm_v1_disable_multiproc=True, vllm.__version__=dev, VLLM_ENABLE_V1_MULTIPROCESSING=0 [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=4037604, ip=10.128.56.68) 2026-06-14 04:06:46.915 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:626 - BaseVLLMInferenceEngine: set VLLM_ENABLE_V1_MULTIPROCESSING=0 [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=4037604, ip=10.128.56.68) 2026-06-14 04:06:46.915 | WARNING | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1192 - OpenAI API sampling params overridden: temperature=1.0, top_p=1.0, top_k=-1 [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=4037604, ip=10.128.56.68) 2026-06-14 04:06:46.947 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1244 - Engine startup stagger: sleeping 1.51s (attempt 1/5) to avoid port collisions [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) (EngineCore_DP0 pid=3942483) _C._set_float32_matmul_precision(precision) +(pid=1712285) Using blocking ray.get inside async actor. This blocks the event loop. Please use `await` on object ref with asyncio.gather if you want to yield execution to the event loop instead. [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) (EngineCore_DP0 pid=3942507) _C._set_float32_matmul_precision(precision) +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) (EngineCore_DP0 pid=1497138) _C._set_float32_matmul_precision(precision) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) (EngineCore_DP0 pid=1497158) _C._set_float32_matmul_precision(precision) +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e [repeated 16x across cluster] +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) [W614 04:06:51.204854300 socket.cpp:767] [c10d] The client socket cannot be initialized to connect to [jpbo-102-30.jupiter.internal]:34397 (errno: 97 - Address family not supported by protocol). [repeated 10x across cluster] +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) [W614 04:06:51.205181686 Utils.hpp:166] Warning: Environment variable NCCL_BLOCKING_WAIT is deprecated; use TORCH_NCCL_BLOCKING_WAIT instead (function operator()) [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) [rank0]:[W614 04:06:51.310544255 Utils.hpp:137] Warning: Environment variable TORCH_NCCL_TRACE_BUFFER_SIZE is deprecated; use TORCH_FR_BUFFER_SIZE instead (function operator()) [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) (EngineCore_DP0 pid=1508209) _C._set_float32_matmul_precision(precision) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) [2026-06-14 04:06:51,410 E 1496779 1496881] core_worker_process.cc:842: Failed to establish connection to the metrics exporter agent. Metrics will not be exported. Exporter agent status: RpcError: Running out of retries to initialize the metrics agent. rpc_code: 14 [repeated 11x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) (EngineCore_DP0 pid=1508201) _C._set_float32_matmul_precision(precision) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) (EngineCore_DP0 pid=1497142) _C._set_float32_matmul_precision(precision) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) (EngineCore_DP0 pid=1508221) _C._set_float32_matmul_precision(precision) +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) The argument `trust_remote_code` is to be used with Auto classes. It has no effect here and is ignored. [repeated 14x across cluster] +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) The tokenizer you are loading from '/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) (EngineCore_DP0 pid=3942483) Loading safetensors checkpoint shards: 0% Completed | 0/4 [00:00 10.128.34.177 (routable head IP) for coordinator litellm base_url connectivity +(skyrl_entrypoint pid=1712105) 2026-06-14 04:07:08.979 | INFO  | examples.terminal_bench.rollout_coordinator:__init__:405 - [RolloutDispatcher] configured num_coordinators=4, cpus_per_coordinator=8 +(skyrl_entrypoint pid=1712105) 2026-06-14 04:07:09.000 | INFO  | examples.terminal_bench.rollout_coordinator:startup:434 - [RolloutDispatcher] PlacementGroup ready: 4 bundles x 8 CPU (SPREAD) +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) (EngineCore_DP0 pid=3942507) The tokenizer you are loading from '/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. [repeated 19x across cluster] +(raylet, ip=10.128.34.179) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) 2026-06-14 04:07:09.388 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1301 - Initializing OpenAIServingChat with custom_chat_template read from: chat_templates/qwen3_thinking_acc.jinja2 [repeated 19x across cluster] +(AsyncVLLMInferenceEngine pid=4037604, ip=10.128.56.68) (EngineCore_DP0 pid=4037833) Loading safetensors checkpoint shards: 0% Completed | 0/4 [00:00 168 (// 4) +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) (EngineCore_DP0 pid=1508039) +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) (EngineCore_DP0 pid=1508201) The tokenizer you are loading from '/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) (EngineCore_DP0 pid=1508043) +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) (EngineCore_DP0 pid=1508055) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) (EngineCore_DP0 pid=1508031) +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) (EngineCore_DP0 pid=3946090) +(raylet, ip=10.128.34.179) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) (EngineCore_DP0 pid=3946102) +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) (EngineCore_DP0 pid=3946095) +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) (EngineCore_DP0 pid=3946082) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:07:14.184 | INFO | examples.terminal_bench.terminal_bench_generator:_configure_harbor_logging:316 - Harbor logging level set to INFO +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:07:14.185 | INFO | examples.terminal_bench.terminal_bench_generator:__init__:212 - TerminalBenchGenerator initialized with HarborConfigBuilder. Exposed fields: ['name', 'max_episodes', 'enable_summarize', 'store_all_messages', 'trajectory_config', 'enable_episode_logging', 'record_terminal_session', 'enable_pane_logging', 'strict_json_parser', 'interleaved_thinking', 'extra_body', 'override_timeout_sec', 'override_cpus', 'override_memory_mb', 'override_storage_mb', 'auto_snapshot', 'verifier_override_timeout_sec', 'max_retries', 'min_wait_sec', 'max_wait_sec', 'wait_multiplier', 'exclude_exceptions', 'n_concurrent_trials', 'log_level', 'enable_reward_shaping', 'reward_shaper', 'loop_outcome_shaper', 'loop_shaping', 'collect_rollout_details', 'enable_error_classification', 'mask_exceptions', 'default_error_treatment', 'passthrough_exceptions', 'zero_exceptions']. Retry config: max_retries=3, backoff=60.0-600.0s. Concurrent trials: 168. Reward shaping: enabled=True, shaper=composite_loop. Error classification: enabled=True +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:07:14.185 | INFO | examples.terminal_bench.terminal_bench_generator:__init__:230 - TerminalBenchGenerator initialized with custom chat template read from: chat_templates/qwen3_thinking_acc.jinja2 +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:07:14.185 | INFO | examples.terminal_bench.rollout_coordinator:__init__:246 - [RolloutCoordinator 0/4] constructed (http=10.128.34.177:8000) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:07:14.188 | INFO | examples.terminal_bench.terminal_bench_generator:_create_orchestrator:372 - QueueOrchestrator created and started with n_concurrent_trials=168, rollback_hook registered for ContextLengthExceededError/AgentTimeoutError +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:07:14.188 | INFO | examples.terminal_bench.terminal_bench_generator:startup:329 - TerminalBenchGenerator startup complete. Shared orchestrator ready with n_concurrent_trials=168 +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:07:14.188 | INFO | examples.terminal_bench.rollout_coordinator:startup:254 - [RolloutCoordinator 0] startup complete +(skyrl_entrypoint pid=1712105) 2026-06-14 04:07:14.189 | INFO  | examples.terminal_bench.rollout_coordinator:startup:469 - [RolloutDispatcher] coordinator 1/4 started +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) [2026-06-14 04:07:14,468 E 3949441 3949552] core_worker_process.cc:842: Failed to establish connection to the metrics exporter agent. Metrics will not be exported. Exporter agent status: RpcError: Running out of retries to initialize the metrics agent. rpc_code: 14 +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) 2026-06-14 04:07:13.355 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1301 - Initializing OpenAIServingChat with custom_chat_template read from: chat_templates/qwen3_thinking_acc.jinja2 [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=4037604, ip=10.128.56.68) (EngineCore_DP0 pid=4037833) Loading safetensors checkpoint shards: 50% Completed | 2/4 [00:08<00:08, 4.11s/it] [repeated 44x across cluster] +(raylet, ip=10.128.34.183) 2026-06-14 04:07:17,078 WARNING node.py:1846 -- The object spilling config is specified from an unstable API - system config or environment variable. This is subject to change in the future. You can use the stable API - --object-spilling-directory in ray start or object_spilling_directory in ray.init() to specify the object spilling directory instead. If you need more advanced settings, please open a github issue with the Ray team. +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) (EngineCore_DP0 pid=3945770) +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) (EngineCore_DP0 pid=3945782) +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) (EngineCore_DP0 pid=3945778) +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) (EngineCore_DP0 pid=3945796) +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) (EngineCore_DP0 pid=1508039) The tokenizer you are loading from '/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. [repeated 13x across cluster] +(raylet, ip=10.128.34.183) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e [repeated 6x across cluster] +(FSDPPolicyWorkerBase pid=1712285) [2026-06-14 04:07:14,843 E 1712285 1712485] core_worker_process.cc:842: Failed to establish connection to the metrics exporter agent. Metrics will not be exported. Exporter agent status: RpcError: Running out of retries to initialize the metrics agent. rpc_code: 14 [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) 2026-06-14 04:07:18.014 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1301 - Initializing OpenAIServingChat with custom_chat_template read from: chat_templates/qwen3_thinking_acc.jinja2 [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) (EngineCore_DP0 pid=4037843) +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) (EngineCore_DP0 pid=4037857) +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) (EngineCore_DP0 pid=4037837) +(AsyncVLLMInferenceEngine pid=4037604, ip=10.128.56.68) (EngineCore_DP0 pid=4037833) +(AsyncVLLMInferenceEngine pid=4037604, ip=10.128.56.68) (EngineCore_DP0 pid=4037833) Loading safetensors checkpoint shards: 100% Completed | 4/4 [00:13<00:00, 3.48s/it] [repeated 24x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:07:21.638 | INFO | examples.terminal_bench.rollout_coordinator:_scale_terminal_bench_cfg:121 - [RolloutCoordinator] scaled n_concurrent_trials 675 -> 168 (// 4) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:07:21.846 | INFO | examples.terminal_bench.terminal_bench_generator:_configure_harbor_logging:316 - Harbor logging level set to INFO +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:07:21.847 | INFO | examples.terminal_bench.terminal_bench_generator:__init__:212 - TerminalBenchGenerator initialized with HarborConfigBuilder. Exposed fields: ['name', 'max_episodes', 'enable_summarize', 'store_all_messages', 'trajectory_config', 'enable_episode_logging', 'record_terminal_session', 'enable_pane_logging', 'strict_json_parser', 'interleaved_thinking', 'extra_body', 'override_timeout_sec', 'override_cpus', 'override_memory_mb', 'override_storage_mb', 'auto_snapshot', 'verifier_override_timeout_sec', 'max_retries', 'min_wait_sec', 'max_wait_sec', 'wait_multiplier', 'exclude_exceptions', 'n_concurrent_trials', 'log_level', 'enable_reward_shaping', 'reward_shaper', 'loop_outcome_shaper', 'loop_shaping', 'collect_rollout_details', 'enable_error_classification', 'mask_exceptions', 'default_error_treatment', 'passthrough_exceptions', 'zero_exceptions']. Retry config: max_retries=3, backoff=60.0-600.0s. Concurrent trials: 168. Reward shaping: enabled=True, shaper=composite_loop. Error classification: enabled=True +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:07:21.847 | INFO | examples.terminal_bench.terminal_bench_generator:__init__:230 - TerminalBenchGenerator initialized with custom chat template read from: chat_templates/qwen3_thinking_acc.jinja2 +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:07:21.847 | INFO | examples.terminal_bench.rollout_coordinator:__init__:246 - [RolloutCoordinator 1/4] constructed (http=10.128.34.177:8000) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:07:21.850 | INFO | examples.terminal_bench.terminal_bench_generator:_create_orchestrator:372 - QueueOrchestrator created and started with n_concurrent_trials=168, rollback_hook registered for ContextLengthExceededError/AgentTimeoutError +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:07:21.850 | INFO | examples.terminal_bench.terminal_bench_generator:startup:329 - TerminalBenchGenerator startup complete. Shared orchestrator ready with n_concurrent_trials=168 +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:07:21.850 | INFO | examples.terminal_bench.rollout_coordinator:startup:254 - [RolloutCoordinator 1] startup complete +(skyrl_entrypoint pid=1712105) 2026-06-14 04:07:21.851 | INFO  | examples.terminal_bench.rollout_coordinator:startup:469 - [RolloutDispatcher] coordinator 2/4 started +(AsyncVLLMInferenceEngine pid=4037604, ip=10.128.56.68) (EngineCore_DP0 pid=4037833) The tokenizer you are loading from '/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. [repeated 9x across cluster] +(raylet, ip=10.128.34.178) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e [repeated 6x across cluster] +(raylet, ip=10.128.34.178) 2026-06-14 04:07:24,761 WARNING node.py:1846 -- The object spilling config is specified from an unstable API - system config or environment variable. This is subject to change in the future. You can use the stable API - --object-spilling-directory in ray start or object_spilling_directory in ray.init() to specify the object spilling directory instead. If you need more advanced settings, please open a github issue with the Ray team. +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) 2026-06-14 04:07:24.867 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1301 - Initializing OpenAIServingChat with custom_chat_template read from: chat_templates/qwen3_thinking_acc.jinja2 [repeated 8x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:07:29.874 | INFO | examples.terminal_bench.rollout_coordinator:_scale_terminal_bench_cfg:121 - [RolloutCoordinator] scaled n_concurrent_trials 675 -> 168 (// 4) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:07:30.095 | INFO  | examples.terminal_bench.rollout_coordinator:startup:469 - [RolloutDispatcher] coordinator 3/4 started +(RolloutCoordinator pid=1508077, ip=10.128.34.178) The tokenizer you are loading from '/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:07:30.090 | INFO | examples.terminal_bench.terminal_bench_generator:_configure_harbor_logging:316 - Harbor logging level set to INFO +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:07:30.091 | INFO | examples.terminal_bench.terminal_bench_generator:__init__:212 - TerminalBenchGenerator initialized with HarborConfigBuilder. Exposed fields: ['name', 'max_episodes', 'enable_summarize', 'store_all_messages', 'trajectory_config', 'enable_episode_logging', 'record_terminal_session', 'enable_pane_logging', 'strict_json_parser', 'interleaved_thinking', 'extra_body', 'override_timeout_sec', 'override_cpus', 'override_memory_mb', 'override_storage_mb', 'auto_snapshot', 'verifier_override_timeout_sec', 'max_retries', 'min_wait_sec', 'max_wait_sec', 'wait_multiplier', 'exclude_exceptions', 'n_concurrent_trials', 'log_level', 'enable_reward_shaping', 'reward_shaper', 'loop_outcome_shaper', 'loop_shaping', 'collect_rollout_details', 'enable_error_classification', 'mask_exceptions', 'default_error_treatment', 'passthrough_exceptions', 'zero_exceptions']. Retry config: max_retries=3, backoff=60.0-600.0s. Concurrent trials: 168. Reward shaping: enabled=True, shaper=composite_loop. Error classification: enabled=True +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:07:30.091 | INFO | examples.terminal_bench.terminal_bench_generator:__init__:230 - TerminalBenchGenerator initialized with custom chat template read from: chat_templates/qwen3_thinking_acc.jinja2 +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:07:30.091 | INFO | examples.terminal_bench.rollout_coordinator:__init__:246 - [RolloutCoordinator 2/4] constructed (http=10.128.34.177:8000) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:07:30.094 | INFO | examples.terminal_bench.terminal_bench_generator:_create_orchestrator:372 - QueueOrchestrator created and started with n_concurrent_trials=168, rollback_hook registered for ContextLengthExceededError/AgentTimeoutError +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:07:30.094 | INFO | examples.terminal_bench.terminal_bench_generator:startup:329 - TerminalBenchGenerator startup complete. Shared orchestrator ready with n_concurrent_trials=168 +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:07:30.094 | INFO | examples.terminal_bench.rollout_coordinator:startup:254 - [RolloutCoordinator 2] startup complete +(raylet, ip=10.128.56.73) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e +(raylet, ip=10.128.56.73) 2026-06-14 04:07:32,994 WARNING node.py:1846 -- The object spilling config is specified from an unstable API - system config or environment variable. This is subject to change in the future. You can use the stable API - --object-spilling-directory in ray start or object_spilling_directory in ray.init() to specify the object spilling directory instead. If you need more advanced settings, please open a github issue with the Ray team. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:07:38.227 | INFO | examples.terminal_bench.rollout_coordinator:_scale_terminal_bench_cfg:121 - [RolloutCoordinator] scaled n_concurrent_trials 675 -> 168 (// 4) +(raylet, ip=10.128.56.73) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e [repeated 5x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) The tokenizer you are loading from '/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:07:38.441 | INFO | examples.terminal_bench.terminal_bench_generator:_configure_harbor_logging:316 - Harbor logging level set to INFO +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:07:38.442 | INFO | examples.terminal_bench.terminal_bench_generator:__init__:212 - TerminalBenchGenerator initialized with HarborConfigBuilder. Exposed fields: ['name', 'max_episodes', 'enable_summarize', 'store_all_messages', 'trajectory_config', 'enable_episode_logging', 'record_terminal_session', 'enable_pane_logging', 'strict_json_parser', 'interleaved_thinking', 'extra_body', 'override_timeout_sec', 'override_cpus', 'override_memory_mb', 'override_storage_mb', 'auto_snapshot', 'verifier_override_timeout_sec', 'max_retries', 'min_wait_sec', 'max_wait_sec', 'wait_multiplier', 'exclude_exceptions', 'n_concurrent_trials', 'log_level', 'enable_reward_shaping', 'reward_shaper', 'loop_outcome_shaper', 'loop_shaping', 'collect_rollout_details', 'enable_error_classification', 'mask_exceptions', 'default_error_treatment', 'passthrough_exceptions', 'zero_exceptions']. Retry config: max_retries=3, backoff=60.0-600.0s. Concurrent trials: 168. Reward shaping: enabled=True, shaper=composite_loop. Error classification: enabled=True +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:07:38.442 | INFO | examples.terminal_bench.terminal_bench_generator:__init__:230 - TerminalBenchGenerator initialized with custom chat template read from: chat_templates/qwen3_thinking_acc.jinja2 +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:07:38.442 | INFO | examples.terminal_bench.rollout_coordinator:__init__:246 - [RolloutCoordinator 3/4] constructed (http=10.128.34.177:8000) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:07:38.445 | INFO | examples.terminal_bench.terminal_bench_generator:_create_orchestrator:372 - QueueOrchestrator created and started with n_concurrent_trials=168, rollback_hook registered for ContextLengthExceededError/AgentTimeoutError +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:07:38.445 | INFO | examples.terminal_bench.terminal_bench_generator:startup:329 - TerminalBenchGenerator startup complete. Shared orchestrator ready with n_concurrent_trials=168 +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:07:38.445 | INFO | examples.terminal_bench.rollout_coordinator:startup:254 - [RolloutCoordinator 3] startup complete +(skyrl_entrypoint pid=1712105) 2026-06-14 04:07:38.445 | INFO  | examples.terminal_bench.rollout_coordinator:startup:469 - [RolloutDispatcher] coordinator 4/4 started +(skyrl_entrypoint pid=1712105) 2026-06-14 04:07:38.446 | INFO  | examples.terminal_bench.rollout_coordinator:startup:477 - [RolloutDispatcher] 4 coordinators started +(skyrl_entrypoint pid=1712105) 2026-06-14 04:07:38.446 | INFO  | skyrl_train.fully_async_trainer:train:485 - Generator startup complete +(skyrl_entrypoint pid=1712105) 2026-06-14 04:07:38.446 | INFO  | skyrl_train.fully_async_trainer:_train_loop:510 - Started: 'load_checkpoints' +(skyrl_entrypoint pid=1712105) 2026-06-14 04:07:38.455 | INFO  | skyrl_train.trainer:load_checkpoints:1735 - Loading checkpoint from: /e/data1/datasets/playground/ot-baf/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/checkpoints/global_step_78 +(skyrl_entrypoint pid=1712105) 2026-06-14 04:07:38.456 | INFO  | skyrl_train.trainer:load_checkpoints:1741 - Resuming from global_step: 78 +(skyrl_entrypoint pid=1712105) 2026-06-14 04:07:38.466 | INFO  | skyrl_train.trainer:load_checkpoints:1757 - Successfully loaded trainer state +(skyrl_entrypoint pid=1712105) 2026-06-14 04:07:38.482 | INFO  | skyrl_train.trainer:load_checkpoints:1767 - Successfully loaded dataloader state +(skyrl_entrypoint pid=1712105) 2026-06-14 04:07:38.482 | INFO  | skyrl_train.trainer:load_checkpoints:1776 - Loading policy checkpoint from /e/data1/datasets/playground/ot-baf/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/checkpoints/global_step_78/policy +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [2026-06-14 04:07:39,841 E 1508398 1508438] core_worker_process.cc:842: Failed to establish connection to the metrics exporter agent. Metrics will not be exported. Exporter agent status: RpcError: Running out of retries to initialize the metrics agent. rpc_code: 14 +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [2026-06-14 04:07:47,096 E 1496555 1496595] core_worker_process.cc:842: Failed to establish connection to the metrics exporter agent. Metrics will not be exported. Exporter agent status: RpcError: Running out of retries to initialize the metrics agent. rpc_code: 14 +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [2026-06-14 04:07:54,778 E 1508077 1508117] core_worker_process.cc:842: Failed to establish connection to the metrics exporter agent. Metrics will not be exported. Exporter agent status: RpcError: Running out of retries to initialize the metrics agent. rpc_code: 14 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py:4876: UserWarning: barrier(): using the device under current context. You can specify `device_id` in `init_process_group` to mute this warning. +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) warnings.warn( # warn only once +(skyrl_entrypoint pid=1712105) 2026-06-14 04:07:57.128 | INFO  | skyrl_train.trainer:load_checkpoints:1786 - Successfully loaded policy checkpoint +(skyrl_entrypoint pid=1712105) 2026-06-14 04:07:57.128 | INFO  | skyrl_train.trainer:load_checkpoints:1802 - Successfully loaded complete checkpoint state from global_step_78 +(skyrl_entrypoint pid=1712105) 2026-06-14 04:07:57.129 | INFO  | skyrl_train.fully_async_trainer:_train_loop:512 - Resumed training from global_step 78 +(skyrl_entrypoint pid=1712105) 2026-06-14 04:07:57.144 | INFO  | skyrl_train.utils.data_tracker:load_state:97 - Loaded data tracker state: epoch=0, consumed_in_epoch=4965, total_consumed=4965 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/__init__.py:7: RuntimeWarning: Failed to read commit hash: +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) No module named 'vllm._version' +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) from .version import __version__, __version_tuple__ # isort:skip +(skyrl_entrypoint pid=1712105) 2026-06-14 04:07:57.145 | INFO  | skyrl_train.fully_async_trainer:_train_loop:510 - Finished: 'load_checkpoints', time cost: 18.70s +(skyrl_entrypoint pid=1712105) 2026-06-14 04:07:57.145 | INFO  | skyrl_train.fully_async_trainer:_train_loop:544 - Started: 'init_weight_sync_state' +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [2026-06-14 04:08:03,012 E 3946333 3946373] core_worker_process.cc:842: Failed to establish connection to the metrics exporter agent. Metrics will not be exported. Exporter agent status: RpcError: Running out of retries to initialize the metrics agent. rpc_code: 14 +(FSDPPolicyWorkerBase pid=1712285) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/__init__.py:7: RuntimeWarning: Failed to read commit hash: [repeated 7x across cluster] +(FSDPPolicyWorkerBase pid=1712285) No module named 'vllm._version' [repeated 7x across cluster] +(FSDPPolicyWorkerBase pid=1712285) from .version import __version__, __version_tuple__ # isort:skip [repeated 7x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) 2026-06-14 04:08:03.039 | INFO  | logging:info:2216 - [weight-sync] hostname=jpbo-102-30.jupiter.internal +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) 2026-06-14 04:08:03.039 | INFO  | logging:info:2216 - [weight-sync] _global_node.node_ip_address=10.128.56.78 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) 2026-06-14 04:08:03.040 | INFO  | logging:info:2216 - [weight-sync] get_node_ip_address()=10.128.56.78 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) 2026-06-14 04:08:03.040 | INFO  | logging:info:2216 - [weight-sync] Using master_addr=10.128.56.78, master_port=36449 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) [rank0]:[W614 04:08:03.424483062 socket.cpp:767] [c10d] The client socket cannot be initialized to connect to [jpbo-102-30-interconnect-1.jupiter.internal]:36449 (errno: 97 - Address family not supported by protocol). +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) (EngineCore_DP0 pid=4037843) 2026-06-14 04:08:03.191 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:init_weight_update_communicator:223 - torch.distributed.get_rank(): 0, rank_offset: 45, rank: 45, world_size: 49, group_name: skyrl +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) (EngineCore_DP0 pid=4037843) 2026-06-14 04:08:03.194 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:init_weight_update_communicator:234 - init_weight_update_communicator: master_address=10.128.56.78, master_port=36449, +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py:4876: UserWarning: barrier(): using the device under current context. You can specify `device_id` in `init_process_group` to mute this warning. +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) warnings.warn( # warn only once +(skyrl_entrypoint pid=1712105) 2026-06-14 04:08:03.604 | INFO  | skyrl_train.trainer:init_weight_sync_state:874 - Initialized weight sync state for policy model and inference engines. +(skyrl_entrypoint pid=1712105) 2026-06-14 04:08:03.604 | INFO  | skyrl_train.fully_async_trainer:_train_loop:544 - Finished: 'init_weight_sync_state', time cost: 6.46s +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) [rank0]:[W614 04:08:07.806454810 Utils.hpp:137] Warning: Environment variable TORCH_NCCL_TRACE_BUFFER_SIZE is deprecated; use TORCH_FR_BUFFER_SIZE instead (function operator()) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:08:14.272 | INFO  | skyrl_train.fully_async_trainer:_train_loop:548 - Finished: 'sync_weights_to_inference_engines', time cost: 10.67s +(skyrl_entrypoint pid=1712105) 2026-06-14 04:08:14.273 | INFO  | skyrl_train.callbacks.builtin:on_train_begin:270 - HFHubUploadCallback initialized: repo=laion/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san, upload_steps=5, export_path=/e/data1/datasets/playground/ot-baf/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/exports +(skyrl_entrypoint pid=1712105) Training Step Progress: 98%|█████████▊| 78/80 [00:00 -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:18:00.891 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 16 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:18:00.898 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (5941) != token count (3625), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:18:00.944 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3828', repetition_id=1): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:18:00.946 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 19 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:18:00.993 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3828', repetition_id=2): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:18:00.996 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 6 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:18:00.999 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (9182) != token count (1781), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:18:01.011 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3828', repetition_id=3): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:18:01.013 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 11 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:18:01.023 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (10944) != token count (7081), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:18:01.030 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #3: logprob count (1627) != token count (242), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:18:01.056 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3828', repetition_id=4): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:18:01.058 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 18 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:18:01.114 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3828', repetition_id=5): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:18:01.116 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 8 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:18:01.145 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3828', repetition_id=6): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:18:01.147 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 4 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:18:01.157 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3828', repetition_id=7): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:18:01.159 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 6 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:18:01.160 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (1403) != token count (613), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:18:01.171 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:884 - TIS alignment: 73550/86892 tokens exact, 0 via LCS fallback, 13342 unaligned; 0 LCS-fallback messages, 5 failed messages (of 88 assistant messages). Non-zero LCS/failure means serving↔training tokenizer divergence. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:18:01.171 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 8/8 successful, 0 failed instances, 0 masked (excluded from baseline) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:18:01.171 | INFO | examples.terminal_bench.terminal_bench_generator:generate:1000 - Reward component averages (n=8): antithrash=0.000, outcome=0.250, total=-0.150, terminate=-0.150 +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 17%|█▋ | 11/64 [09:46<47:06, 53.33s/it, buffer qsize=0]  +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 17%|█▋ | 11/64 [09:46<47:06, 53.33s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) 2026-06-14 04:18:03.067 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:18:05.271 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:18:12.925 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:18:16.555 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e +(skyrl_entrypoint pid=1712105) 2026-06-14 04:18:48.591 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:19:22.805 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:19:26.169 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:20:12.214 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:20:27.637 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:20:43.194 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:20:52.548 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:20:55.707 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:20:55.737 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:21:00.121 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:21:01.730 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:21:15.087 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:21:24.977 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:21:38.067 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:21:38.785 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:22:07.562 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:22:13.100 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:22:19.775 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:22:27.261 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:23:00.761 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:23:03.477 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:23:04.001 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:23:34.043 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:23:46.426 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:24:16.895 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:24:20.768 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:24:22.118 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:24:24.780 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:24:25.128 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:24:26.357 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:24:29.403 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:24:35.238 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:24:40.205 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:25:35.293 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:25:54.517 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:25:56.010 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:26:48.974 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:26:57.485 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:27:00.573 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:27:00.883 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:27:01.890 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:27:04.679 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:27:08.689 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:27:27.403 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:27:28.742 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:27:30.733 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:27:34.693 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:27:36.851 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:27:39.693 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:27:50.130 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:28:06.788 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:28:06.892 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:28:07.674 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:28:13.957 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:28:20.006 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:28:20.713 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:28:23.335 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:28:23.811 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:28:27.877 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:28:32.805 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:28:35.856 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:28:37.867 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:28:51.170 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:29:04.791 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:29:13.345 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:29:16.420 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:29:17.984 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:29:22.998 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:29:28.078 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:29:37.688 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:29:49.335 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:30:15.330 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:30:32.494 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:30:41.766 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:31:04.417 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:31:08.449 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:31:22.686 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:31:23.398 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:31:44.617 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:31:51.376 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:32:19.451 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:32:34.084 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:32:37.309 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:33:08.980 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:33:22.499 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:33:55.695 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:34:19.601 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:34:33.465 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:34:40.495 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:34:50.614 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:34:51.938 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:35:06.441 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:35:10.938 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:35:25.951 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1489', repetition_id=0): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:35:25.968 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:35:25.979 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 11 turns +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:35:26.019 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1489', repetition_id=1): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:35:26.021 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 13 turns +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:35:26.073 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1489', repetition_id=2): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:35:26.075 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 15 turns +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:35:26.085 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (6124) != token count (4941), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:35:26.132 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1489', repetition_id=3): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:35:26.134 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 16 turns +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:35:26.178 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1489', repetition_id=4): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:35:26.180 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 5 turns +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:35:26.182 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (1210) != token count (781), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:35:26.196 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1489', repetition_id=5): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:35:26.198 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 14 turns +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:35:26.199 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (954) != token count (576), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:35:26.237 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1489', repetition_id=6): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:35:26.239 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 9 turns +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:35:26.272 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1489', repetition_id=7): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:35:26.274 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 17 turns +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:35:26.321 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:884 - TIS alignment: 100708/107006 tokens exact, 0 via LCS fallback, 6298 unaligned; 0 LCS-fallback messages, 3 failed messages (of 100 assistant messages). Non-zero LCS/failure means serving↔training tokenizer divergence. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:35:26.321 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 8/8 successful, 0 failed instances, 0 masked (excluded from baseline) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:35:26.321 | INFO | examples.terminal_bench.terminal_bench_generator:generate:1000 - Reward component averages (n=8): antithrash=0.000, outcome=1.000, total=0.300, terminate=0.300 +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 19%|█▉ | 12/64 [27:11<2:25:01, 167.33s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 19%|█▉ | 12/64 [27:11<2:25:01, 167.33s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) 2026-06-14 04:35:48.831 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:35:49.585 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:36:11.427 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:36:14.174 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:36:31.818 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:36:32.172 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:36:44.283 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-0560', repetition_id=0): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:36:44.309 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 14 turns +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:36:44.346 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-0560', repetition_id=1): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:36:44.348 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 6 turns +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:36:44.349 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (1020) != token count (503), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:36:44.370 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-0560', repetition_id=2): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:36:44.371 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 12 turns +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:36:44.420 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-0560', repetition_id=3): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:36:44.422 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 5 turns +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:36:44.445 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-0560', repetition_id=4): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:36:44.446 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 20 turns +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:36:44.502 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-0560', repetition_id=5): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:36:44.504 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 8 turns +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:36:44.537 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-0560', repetition_id=6): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:36:44.538 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 8 turns +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:36:44.545 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (5398) != token count (4805), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:36:44.568 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-0560', repetition_id=7): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:36:44.570 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 13 turns +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:36:44.615 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:884 - TIS alignment: 109390/114698 tokens exact, 0 via LCS fallback, 5308 unaligned; 0 LCS-fallback messages, 2 failed messages (of 86 assistant messages). Non-zero LCS/failure means serving↔training tokenizer divergence. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:36:44.615 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 8/8 successful, 0 failed instances, 0 masked (excluded from baseline) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 04:36:44.616 | INFO | examples.terminal_bench.terminal_bench_generator:generate:1000 - Reward component averages (n=8): antithrash=0.000, outcome=0.875, total=0.225, terminate=0.225 +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 20%|██ | 13/64 [28:30<2:11:33, 154.78s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 20%|██ | 13/64 [28:30<2:11:33, 154.78s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) 2026-06-14 04:36:55.183 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:37:14.281 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1096 - Exception VerifierTimeoutError not in config, using default treatment: ZERO +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:37:14.281 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-3277', repetition_id=0) failed with Harbor exception: Verifier execution timed out after 120.0 seconds (type=VerifierTimeoutError, exclude_from_baseline=False) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:37:14.281 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1096 - Exception VerifierTimeoutError not in config, using default treatment: ZERO +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:37:14.281 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-3277', repetition_id=1) failed with Harbor exception: Verifier execution timed out after 120.0 seconds (type=VerifierTimeoutError, exclude_from_baseline=False) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:37:14.281 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1096 - Exception VerifierTimeoutError not in config, using default treatment: ZERO +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:37:14.281 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-3277', repetition_id=2) failed with Harbor exception: Verifier execution timed out after 120.0 seconds (type=VerifierTimeoutError, exclude_from_baseline=False) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:37:14.282 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1096 - Exception VerifierTimeoutError not in config, using default treatment: ZERO +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:37:14.282 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-3277', repetition_id=3) failed with Harbor exception: Verifier execution timed out after 120.0 seconds (type=VerifierTimeoutError, exclude_from_baseline=False) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:37:14.282 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1096 - Exception VerifierTimeoutError not in config, using default treatment: ZERO +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:37:14.282 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-3277', repetition_id=4) failed with Harbor exception: Verifier execution timed out after 120.0 seconds (type=VerifierTimeoutError, exclude_from_baseline=False) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:37:14.282 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1096 - Exception VerifierTimeoutError not in config, using default treatment: ZERO +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:37:14.282 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-3277', repetition_id=5) failed with Harbor exception: Verifier execution timed out after 120.0 seconds (type=VerifierTimeoutError, exclude_from_baseline=False) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:37:14.282 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1096 - Exception VerifierTimeoutError not in config, using default treatment: ZERO +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:37:14.282 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-3277', repetition_id=6) failed with Harbor exception: Verifier execution timed out after 120.0 seconds (type=VerifierTimeoutError, exclude_from_baseline=False) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:37:14.284 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3277', repetition_id=7): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 22%|██▏ | 14/64 [28:59<1:51:30, 133.81s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 22%|██▏ | 14/64 [28:59<1:51:30, 133.81s/it, buffer qsize=0] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:37:14.310 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 18 turns +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:37:14.360 | INFO | examples.terminal_bench.terminal_bench_generator:generate:904 - Exception breakdown: {'VerifierTimeoutError': 7} +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:37:14.360 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 1/8 successful, 1 failed instances, 0 masked (excluded from baseline) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:37:14.360 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:948 - TIS mode: 7/8 trajectories missing logprobs (likely due to context length errors). Filled with zeros. These trajectories will have no gradient contribution from TIS. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:37:14.360 | INFO | examples.terminal_bench.terminal_bench_generator:generate:1000 - Reward component averages (n=1): antithrash=0.000, outcome=0.000, total=-0.300, terminate=-0.300 +(skyrl_entrypoint pid=1712105) 2026-06-14 04:37:15.426 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:37:48.491 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:38:10.863 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:38:15.999 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:38:16.845 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:38:20.165 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:38:52.954 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:39:02.375 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:39:06.206 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:39:07.161 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:39:26.221 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:39:28.088 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:39:28.781 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:39:30.032 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:39:35.600 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:39:43.048 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:40:09.193 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:40:23.421 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:40:26.666 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:40:28.501 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:40:34.124 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:40:48.635 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:40:51.028 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:40:59.147 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:41:39.162 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:41:43.366 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:41:52.818 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:42:28.141 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:42:54.065 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:43:00.539 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:43:21.589 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:43:26.764 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:43:56.548 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:44:08.735 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:44:19.809 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:44:27.755 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:44:50.178 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1363', repetition_id=0): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:44:50.181 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 6 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:44:50.223 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1363', repetition_id=1): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:44:50.226 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 8 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:44:50.227 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (738) != token count (316), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:44:50.249 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1363', repetition_id=2): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:44:50.251 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 17 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:44:50.301 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1363', repetition_id=3): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:44:50.304 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 9 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:44:50.340 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1363', repetition_id=4): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:44:50.342 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 10 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:44:50.344 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (3172) != token count (539), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:44:50.380 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1363', repetition_id=5): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:44:50.382 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 10 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:44:50.402 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1363', repetition_id=6): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:44:50.404 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 10 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:44:50.440 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1363', repetition_id=7): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:44:50.442 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 22 turns +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 23%|██▎ | 15/64 [36:35<2:40:09, 196.11s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 23%|██▎ | 15/64 [36:35<2:40:09, 196.11s/it, buffer qsize=0] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:44:50.506 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:884 - TIS alignment: 100202/101057 tokens exact, 0 via LCS fallback, 855 unaligned; 0 LCS-fallback messages, 2 failed messages (of 92 assistant messages). Non-zero LCS/failure means serving↔training tokenizer divergence. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:44:50.506 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 8/8 successful, 0 failed instances, 0 masked (excluded from baseline) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:44:50.506 | INFO | examples.terminal_bench.terminal_bench_generator:generate:1000 - Reward component averages (n=8): antithrash=0.000, outcome=0.000, total=-0.300, terminate=-0.300 +(skyrl_entrypoint pid=1712105) 2026-06-14 04:45:38.159 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:45:51.251 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:46:06.898 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:46:25.286 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:46:25.907 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:46:29.763 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:46:41.862 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:46:51.512 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:47:06.807 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:49:33.216 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:49:42.806 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:49:47.506 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:49:52.484 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:49:58.653 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:50:00.104 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:50:00.249 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:50:03.128 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:50:08.008 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-2605', repetition_id=0): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:50:08.010 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 19 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:50:08.056 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-2605', repetition_id=1): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': -0.02, 'shaping_total': -0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:50:08.058 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 10 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:50:08.092 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-2605', repetition_id=2): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:50:08.094 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 8 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:50:08.114 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-2605', repetition_id=3): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:50:08.115 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 12 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:50:08.160 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:50:08.161 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-2605', repetition_id=4) failed with Harbor exception: Context length limit reached: 30943 tokens used, only 1057 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:50:08.162 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-2605', repetition_id=5): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:50:08.164 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 11 turns +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 25%|██▌ | 16/64 [41:53<2:57:55, 222.41s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 25%|██▌ | 16/64 [41:53<2:57:55, 222.41s/it, buffer qsize=0] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:50:08.196 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:50:08.196 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-2605', repetition_id=6) failed with Harbor exception: Context length limit reached: 30877 tokens used, only 1123 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:50:08.196 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:50:08.196 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-2605', repetition_id=7) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:50:08.197 | INFO | examples.terminal_bench.terminal_bench_generator:generate:904 - Exception breakdown: {'ContextLengthExceededError': 3} +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:50:08.197 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 5/8 successful, 1 failed instances, 3 masked (excluded from baseline) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:50:08.197 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:948 - TIS mode: 3/8 trajectories missing logprobs (likely due to context length errors). Filled with zeros. These trajectories will have no gradient contribution from TIS. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:50:08.197 | INFO | examples.terminal_bench.terminal_bench_generator:generate:1000 - Reward component averages (n=5): antithrash=-0.004, outcome=0.000, total=-0.300, terminate=-0.300 +(skyrl_entrypoint pid=1712105) 2026-06-14 04:50:31.843 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:50:33.821 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:50:52.094 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:51:05.167 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:51:12.936 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:51:24.831 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:51:27.421 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:51:32.961 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:51:39.148 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:51:43.958 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:51:44.604 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:52:15.829 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:52:27.473 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:52:28.016 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:52:30.804 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:53:01.459 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:53:41.200 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:53:41.577 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:53:51.491 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:54:15.891 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:54:42.520 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3184', repetition_id=0): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:54:42.522 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 17 turns +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:54:42.571 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3184', repetition_id=1): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:54:42.573 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 14 turns +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:54:42.583 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #3: logprob count (10403) != token count (1215), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:54:42.587 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #4: logprob count (2098) != token count (1636), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:54:42.609 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3184', repetition_id=2): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:54:42.611 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 10 turns +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:54:42.613 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (1969) != token count (649), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:54:42.632 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:54:42.632 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-3184', repetition_id=3) failed with Harbor exception: Context length limit reached: 30098 tokens used, only 1902 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:54:42.633 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3184', repetition_id=4): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:54:42.635 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 13 turns +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:54:42.672 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3184', repetition_id=5): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:54:42.674 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 7 turns +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:54:42.691 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3184', repetition_id=6): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:54:42.693 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 10 turns +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:54:42.717 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3184', repetition_id=7): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:54:42.718 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 7 turns +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:54:42.739 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:884 - TIS alignment: 72233/75733 tokens exact, 0 via LCS fallback, 3500 unaligned; 0 LCS-fallback messages, 3 failed messages (of 78 assistant messages). Non-zero LCS/failure means serving↔training tokenizer divergence. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:54:42.739 | INFO | examples.terminal_bench.terminal_bench_generator:generate:904 - Exception breakdown: {'ContextLengthExceededError': 1} +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:54:42.739 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 7/8 successful, 1 failed instances, 1 masked (excluded from baseline) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:54:42.739 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:948 - TIS mode: 1/8 trajectories missing logprobs (likely due to context length errors). Filled with zeros. These trajectories will have no gradient contribution from TIS. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 04:54:42.739 | INFO | examples.terminal_bench.terminal_bench_generator:generate:1000 - Reward component averages (n=7): antithrash=0.000, outcome=0.286, total=-0.129, terminate=-0.129 +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 27%|██▋ | 17/64 [46:28<3:03:51, 234.72s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 27%|██▋ | 17/64 [46:28<3:03:51, 234.72s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) 2026-06-14 04:55:09.160 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:55:13.443 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:55:29.295 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:55:32.624 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:55:56.634 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:56:04.364 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:56:04.364 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-3882', repetition_id=0) failed with Harbor exception: Context length limit reached: 31253 tokens used, only 747 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:56:04.366 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3882', repetition_id=1): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:56:04.369 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 9 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:56:04.371 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (3264) != token count (1066), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:56:04.375 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #2: logprob count (1068) != token count (920), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:56:04.396 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3882', repetition_id=2): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:56:04.398 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 10 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:56:04.399 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (2900) != token count (233), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:56:04.426 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:56:04.427 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-3882', repetition_id=3) failed with Harbor exception: Context length limit reached: 30805 tokens used, only 1195 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:56:04.427 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3882', repetition_id=4): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:56:04.429 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 5 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:56:04.442 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3882', repetition_id=5): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:56:04.444 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 10 turns +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 28%|██▊ | 18/64 [47:50<2:30:22, 196.15s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 28%|██▊ | 18/64 [47:50<2:30:22, 196.15s/it, buffer qsize=0] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:56:04.462 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #5: logprob count (2422) != token count (2423), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:56:04.478 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3882', repetition_id=6): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:56:04.480 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 13 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:56:04.487 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (4082) != token count (3487), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:56:04.522 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:56:04.522 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-3882', repetition_id=7) failed with Harbor exception: Context length limit reached: 31043 tokens used, only 957 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:56:04.523 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:884 - TIS alignment: 36592/44721 tokens exact, 0 via LCS fallback, 8129 unaligned; 0 LCS-fallback messages, 5 failed messages (of 47 assistant messages). Non-zero LCS/failure means serving↔training tokenizer divergence. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:56:04.523 | INFO | examples.terminal_bench.terminal_bench_generator:generate:904 - Exception breakdown: {'ContextLengthExceededError': 3} +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:56:04.523 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 5/8 successful, 1 failed instances, 3 masked (excluded from baseline) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:56:04.523 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:948 - TIS mode: 3/8 trajectories missing logprobs (likely due to context length errors). Filled with zeros. These trajectories will have no gradient contribution from TIS. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:56:04.523 | INFO | examples.terminal_bench.terminal_bench_generator:generate:1000 - Reward component averages (n=5): antithrash=0.000, outcome=0.800, total=0.180, terminate=0.180 +(skyrl_entrypoint pid=1712105) 2026-06-14 04:56:22.020 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:56:49.093 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:56:52.141 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:57:13.917 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:57:15.498 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:57:15.499 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-4773', repetition_id=0) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:57:15.499 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:57:15.499 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-4773', repetition_id=1) failed with Harbor exception: Context length limit reached: 30662 tokens used, only 1338 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:57:15.499 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:57:15.499 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-4773', repetition_id=2) failed with Harbor exception: Context length limit reached: 30368 tokens used, only 1632 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:57:15.499 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:57:15.499 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-4773', repetition_id=3) failed with Harbor exception: Context length limit reached: 30737 tokens used, only 1263 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:57:15.501 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-4773', repetition_id=4): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:57:15.504 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 24 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:57:15.544 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #13: logprob count (841) != token count (840), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:57:15.562 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:57:15.562 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-4773', repetition_id=5) failed with Harbor exception: Context length limit reached: 31341 tokens used, only 659 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:57:15.563 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-4773', repetition_id=6): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:57:15.565 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 8 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:57:15.590 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:57:15.590 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-4773', repetition_id=7) failed with Harbor exception: Context length limit reached: 30341 tokens used, only 1659 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:57:15.590 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:884 - TIS alignment: 19452/20292 tokens exact, 0 via LCS fallback, 840 unaligned; 0 LCS-fallback messages, 1 failed messages (of 32 assistant messages). Non-zero LCS/failure means serving↔training tokenizer divergence. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:57:15.590 | INFO | examples.terminal_bench.terminal_bench_generator:generate:904 - Exception breakdown: {'ContextLengthExceededError': 6} +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:57:15.590 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 2/8 successful, 1 failed instances, 6 masked (excluded from baseline) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:57:15.590 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:948 - TIS mode: 6/8 trajectories missing logprobs (likely due to context length errors). Filled with zeros. These trajectories will have no gradient contribution from TIS. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 04:57:15.590 | INFO | examples.terminal_bench.terminal_bench_generator:generate:1000 - Reward component averages (n=2): antithrash=0.000, outcome=0.000, total=-0.300, terminate=-0.300 +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 30%|██▉ | 19/64 [49:01<2:02:15, 163.02s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 30%|██▉ | 19/64 [49:01<2:02:15, 163.02s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) 2026-06-14 04:57:41.083 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:57:59.543 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:58:00.529 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:58:04.072 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1656', repetition_id=0): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:58:04.076 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 9 turns +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:58:04.078 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (1750) != token count (401), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:58:04.100 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1656', repetition_id=1): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:58:04.102 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 15 turns +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:58:04.118 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #3: logprob count (4395) != token count (4394), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:58:04.159 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1656', repetition_id=2): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:58:04.161 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 9 turns +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:58:04.190 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1656', repetition_id=3): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:58:04.192 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 14 turns +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:58:04.239 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1656', repetition_id=4): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:58:04.241 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 14 turns +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:58:04.247 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (3191) != token count (2674), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:58:04.288 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1656', repetition_id=5): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:58:04.291 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 8 turns +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:58:04.336 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1656', repetition_id=6): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:58:04.338 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 9 turns +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:58:04.373 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1656', repetition_id=7): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:58:04.375 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 12 turns +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:58:04.377 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (2924) != token count (1080), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:58:04.415 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:884 - TIS alignment: 90466/99015 tokens exact, 0 via LCS fallback, 8549 unaligned; 0 LCS-fallback messages, 4 failed messages (of 90 assistant messages). Non-zero LCS/failure means serving↔training tokenizer divergence. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:58:04.415 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 8/8 successful, 0 failed instances, 0 masked (excluded from baseline) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:58:04.415 | INFO | examples.terminal_bench.terminal_bench_generator:generate:1000 - Reward component averages (n=8): antithrash=0.000, outcome=0.000, total=-0.300, terminate=-0.300 +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 31%|███▏ | 20/64 [49:49<1:36:33, 131.67s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 31%|███▏ | 20/64 [49:49<1:36:33, 131.67s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) 2026-06-14 04:58:18.397 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:58:33.459 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:58:48.819 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:58:59.941 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:59:23.938 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1994', repetition_id=0): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:59:23.941 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 20 turns +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:59:24.005 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:59:24.005 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-1994', repetition_id=1) failed with Harbor exception: Context length limit reached: 31878 tokens used, only 122 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:59:24.005 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:59:24.005 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-1994', repetition_id=2) failed with Harbor exception: Context length limit reached: 30207 tokens used, only 1793 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:59:24.005 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:59:24.005 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-1994', repetition_id=3) failed with Harbor exception: Context length limit reached: 30656 tokens used, only 1344 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:59:24.005 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:59:24.005 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-1994', repetition_id=4) failed with Harbor exception: Context length limit reached: 30072 tokens used, only 1928 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:59:24.005 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:59:24.005 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-1994', repetition_id=5) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:59:24.006 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1994', repetition_id=6): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:59:24.009 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 14 turns +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:59:24.044 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #10: logprob count (1035) != token count (1034), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:59:24.057 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:59:24.057 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-1994', repetition_id=7) failed with Harbor exception: Context length limit reached: 30469 tokens used, only 1531 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:59:24.058 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:884 - TIS alignment: 27939/28973 tokens exact, 0 via LCS fallback, 1034 unaligned; 0 LCS-fallback messages, 1 failed messages (of 34 assistant messages). Non-zero LCS/failure means serving↔training tokenizer divergence. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:59:24.058 | INFO | examples.terminal_bench.terminal_bench_generator:generate:904 - Exception breakdown: {'ContextLengthExceededError': 6} +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:59:24.058 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 2/8 successful, 1 failed instances, 6 masked (excluded from baseline) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:59:24.058 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:948 - TIS mode: 6/8 trajectories missing logprobs (likely due to context length errors). Filled with zeros. These trajectories will have no gradient contribution from TIS. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 04:59:24.058 | INFO | examples.terminal_bench.terminal_bench_generator:generate:1000 - Reward component averages (n=2): antithrash=0.000, outcome=0.000, total=-0.300, terminate=-0.300 +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 33%|███▎ | 21/64 [51:09<1:23:51, 117.01s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 33%|███▎ | 21/64 [51:09<1:23:51, 117.01s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) 2026-06-14 04:59:29.066 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 04:59:44.911 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 05:00:12.365 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 05:00:28.452 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 05:00:38.363 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 05:00:55.586 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 05:01:07.857 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 05:02:05.956 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 05:02:14.805 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 05:02:38.762 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:02:40.308 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:02:40.308 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-3670', repetition_id=0) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:02:40.308 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:02:40.308 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-3670', repetition_id=1) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:02:40.308 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:02:40.308 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-3670', repetition_id=2) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:02:40.308 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:02:40.308 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-3670', repetition_id=3) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:02:40.308 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:02:40.308 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-3670', repetition_id=4) failed with Harbor exception: Context length limit reached: 32289 tokens used, only -289 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:02:40.308 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:02:40.308 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-3670', repetition_id=5) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:02:40.308 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:02:40.308 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-3670', repetition_id=6) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:02:40.309 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3670', repetition_id=7): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:02:40.312 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 4 turns +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:02:40.314 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (1906) != token count (478), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:02:40.321 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:884 - TIS alignment: 1102/1580 tokens exact, 0 via LCS fallback, 478 unaligned; 0 LCS-fallback messages, 1 failed messages (of 4 assistant messages). Non-zero LCS/failure means serving↔training tokenizer divergence. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:02:40.321 | INFO | examples.terminal_bench.terminal_bench_generator:generate:904 - Exception breakdown: {'ContextLengthExceededError': 7} +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:02:40.321 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 1/8 successful, 1 failed instances, 7 masked (excluded from baseline) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:02:40.321 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:948 - TIS mode: 7/8 trajectories missing logprobs (likely due to context length errors). Filled with zeros. These trajectories will have no gradient contribution from TIS. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:02:40.321 | INFO | examples.terminal_bench.terminal_bench_generator:generate:1000 - Reward component averages (n=1): antithrash=0.000, outcome=0.000, total=-0.300, terminate=-0.300 +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 34%|███▍ | 22/64 [54:25<1:37:49, 139.75s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 34%|███▍ | 22/64 [54:25<1:37:49, 139.75s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) 2026-06-14 05:03:19.727 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 05:03:24.845 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 05:03:25.706 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 05:03:35.838 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 05:03:47.910 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 05:04:41.573 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 05:04:42.193 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 05:04:55.499 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:04:58.857 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-0246', repetition_id=0): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:04:58.860 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 13 turns +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:04:58.865 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (5026) != token count (3472), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:04:58.897 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:04:58.897 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-0246', repetition_id=1) failed with Harbor exception: Context length limit reached: 30547 tokens used, only 1453 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:04:58.898 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-0246', repetition_id=2): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:04:58.900 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 7 turns +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:04:58.919 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-0246', repetition_id=3): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:04:58.921 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 9 turns +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:04:58.953 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:04:58.953 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-0246', repetition_id=4) failed with Harbor exception: Context length limit reached: 30136 tokens used, only 1864 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:04:58.953 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:04:58.953 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-0246', repetition_id=5) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:04:58.953 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-0246', repetition_id=6): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:04:58.955 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 5 turns +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:04:58.960 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (3709) != token count (3091), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:04:58.962 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #2: logprob count (328) != token count (324), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:04:58.973 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-0246', repetition_id=7): reward shaped 1.000 -> 1.280 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': -0.02, 'shaping_total': 0.27999999999999997}) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:04:58.975 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 17 turns +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:04:58.976 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (1271) != token count (646), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:04:59.012 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:884 - TIS alignment: 54494/62027 tokens exact, 0 via LCS fallback, 7533 unaligned; 0 LCS-fallback messages, 4 failed messages (of 51 assistant messages). Non-zero LCS/failure means serving↔training tokenizer divergence. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:04:59.012 | INFO | examples.terminal_bench.terminal_bench_generator:generate:904 - Exception breakdown: {'ContextLengthExceededError': 3} +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:04:59.012 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 5/8 successful, 1 failed instances, 3 masked (excluded from baseline) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:04:59.012 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:948 - TIS mode: 3/8 trajectories missing logprobs (likely due to context length errors). Filled with zeros. These trajectories will have no gradient contribution from TIS. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:04:59.012 | INFO | examples.terminal_bench.terminal_bench_generator:generate:1000 - Reward component averages (n=5): antithrash=-0.004, outcome=0.400, total=-0.064, terminate=-0.060 +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 36%|███▌ | 23/64 [56:44<1:35:17, 139.44s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 36%|███▌ | 23/64 [56:44<1:35:17, 139.44s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) 2026-06-14 05:05:02.189 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 05:05:24.948 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:05:26.534 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:05:26.534 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-3383', repetition_id=0) failed with Harbor exception: Context length limit reached: 31715 tokens used, only 285 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:05:26.537 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3383', repetition_id=1): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:05:26.540 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 17 turns +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:05:26.603 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:05:26.603 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-3383', repetition_id=2) failed with Harbor exception: Context length limit reached: 30656 tokens used, only 1344 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:05:26.604 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3383', repetition_id=3): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:05:26.607 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 19 turns +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:05:26.660 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3383', repetition_id=4): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:05:26.662 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 10 turns +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:05:26.710 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3383', repetition_id=5): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:05:26.712 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 21 turns +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 38%|███▊ | 24/64 [57:12<1:11:07, 106.69s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 38%|███▊ | 24/64 [57:12<1:11:07, 106.69s/it, buffer qsize=0] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:05:26.779 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #21: logprob count (1216) != token count (1215), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:05:26.781 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3383', repetition_id=6): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:05:26.784 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 13 turns +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:05:26.839 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:05:26.839 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-3383', repetition_id=7) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:05:26.840 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:884 - TIS alignment: 97343/98558 tokens exact, 0 via LCS fallback, 1215 unaligned; 0 LCS-fallback messages, 1 failed messages (of 80 assistant messages). Non-zero LCS/failure means serving↔training tokenizer divergence. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:05:26.840 | INFO | examples.terminal_bench.terminal_bench_generator:generate:904 - Exception breakdown: {'ContextLengthExceededError': 3} +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:05:26.840 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 5/8 successful, 1 failed instances, 3 masked (excluded from baseline) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:05:26.840 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:948 - TIS mode: 3/8 trajectories missing logprobs (likely due to context length errors). Filled with zeros. These trajectories will have no gradient contribution from TIS. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:05:26.840 | INFO | examples.terminal_bench.terminal_bench_generator:generate:1000 - Reward component averages (n=5): antithrash=0.000, outcome=0.000, total=-0.300, terminate=-0.300 +(skyrl_entrypoint pid=1712105) 2026-06-14 05:05:45.416 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 05:06:34.340 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 05:06:51.008 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 05:06:57.107 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 05:07:10.275 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 05:07:16.437 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 05:07:30.105 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 05:07:30.105 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-4190', repetition_id=0) failed with Harbor exception: Context length limit reached: 31917 tokens used, only 83 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 05:07:30.105 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 05:07:30.105 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-4190', repetition_id=1) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 05:07:30.108 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-4190', repetition_id=2): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 05:07:30.115 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 16 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 05:07:30.132 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (4824) != token count (3972), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 05:07:30.194 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 05:07:30.194 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-4190', repetition_id=3) failed with Harbor exception: Context length limit reached: 30143 tokens used, only 1857 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 05:07:30.194 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1078 - Exception AgentTimeoutError classified as PASSTHROUGH (use verifier reward) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 05:07:30.194 | INFO | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1158 - Trajectory TrajectoryID(instance_id='pymethods2test-4190', repetition_id=4): AgentTimeoutError classified as PASSTHROUGH, using verifier reward +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 05:07:30.194 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-4190', repetition_id=4): reward shaped 0.000 -> -0.200 (components={'outcome': 0.0, 'terminate': -0.2, 'antithrash': 0.0, 'shaping_total': -0.2}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 05:07:30.194 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1300 - Trajectory TrajectoryID(instance_id='pymethods2test-4190', repetition_id=4) failed: Invalid chat history structure. chat_history: [] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 05:07:30.195 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-4190', repetition_id=5): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 05:07:30.198 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 10 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 05:07:30.233 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 05:07:30.233 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-4190', repetition_id=6) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 05:07:30.237 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-4190', repetition_id=7): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 05:07:30.239 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 13 turns +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 05:07:30.248 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (12772) != token count (3023), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 39%|███▉ | 25/64 [59:15<1:12:34, 111.64s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 39%|███▉ | 25/64 [59:15<1:12:34, 111.64s/it, buffer qsize=0] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 05:07:30.288 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:884 - TIS alignment: 32863/39858 tokens exact, 0 via LCS fallback, 6995 unaligned; 0 LCS-fallback messages, 2 failed messages (of 39 assistant messages). Non-zero LCS/failure means serving↔training tokenizer divergence. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 05:07:30.288 | INFO | examples.terminal_bench.terminal_bench_generator:generate:904 - Exception breakdown: {'ContextLengthExceededError': 4, 'InvalidChatHistory': 1} +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 05:07:30.288 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 3/8 successful, 1 failed instances, 5 masked (excluded from baseline) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 05:07:30.288 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:948 - TIS mode: 5/8 trajectories missing logprobs (likely due to context length errors). Filled with zeros. These trajectories will have no gradient contribution from TIS. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) 2026-06-14 05:07:30.288 | INFO | examples.terminal_bench.terminal_bench_generator:generate:1000 - Reward component averages (n=3): antithrash=0.000, outcome=0.000, total=-0.300, terminate=-0.300 +(skyrl_entrypoint pid=1712105) 2026-06-14 05:07:59.355 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 05:08:18.113 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:08:19.768 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:08:19.768 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-4223', repetition_id=0) failed with Harbor exception: Context length limit reached: 30594 tokens used, only 1406 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:08:19.768 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:08:19.768 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-4223', repetition_id=1) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:08:19.768 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:08:19.768 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-4223', repetition_id=2) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:08:19.768 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:08:19.768 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-4223', repetition_id=3) failed with Harbor exception: Context length limit reached: 30302 tokens used, only 1698 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:08:19.768 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:08:19.768 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-4223', repetition_id=4) failed with Harbor exception: Context length limit reached: 32119 tokens used, only -119 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:08:19.768 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:08:19.768 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-4223', repetition_id=5) failed with Harbor exception: Context length limit reached: 31764 tokens used, only 236 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:08:19.770 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-4223', repetition_id=6): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:08:19.773 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 18 turns +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:08:19.829 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-4223', repetition_id=7): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:08:19.831 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 3 turns +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:08:19.837 | INFO | examples.terminal_bench.terminal_bench_generator:generate:904 - Exception breakdown: {'ContextLengthExceededError': 6} +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:08:19.837 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 2/8 successful, 1 failed instances, 6 masked (excluded from baseline) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:08:19.837 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:948 - TIS mode: 6/8 trajectories missing logprobs (likely due to context length errors). Filled with zeros. These trajectories will have no gradient contribution from TIS. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:08:19.837 | INFO | examples.terminal_bench.terminal_bench_generator:generate:1000 - Reward component averages (n=2): antithrash=0.000, outcome=1.000, total=0.300, terminate=0.300 +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 41%|████ | 26/64 [1:00:05<59:02, 93.21s/it, buffer qsize=0]  +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 41%|████ | 26/64 [1:00:05<59:02, 93.21s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) 2026-06-14 05:08:20.181 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 05:08:20.536 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 05:08:44.406 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:09:09.383 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:09:09.384 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-0430', repetition_id=0) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:09:09.386 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-0430', repetition_id=1): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:09:09.388 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 10 turns +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:09:09.438 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:09:09.438 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-0430', repetition_id=2) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:09:09.441 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-0430', repetition_id=3): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:09:09.442 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 8 turns +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 42%|████▏ | 27/64 [1:00:54<49:29, 80.25s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 42%|████▏ | 27/64 [1:00:54<49:29, 80.25s/it, buffer qsize=0] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:09:09.448 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (9829) != token count (2931), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:09:09.470 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-0430', repetition_id=4): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:09:09.472 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 7 turns +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:09:09.501 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:09:09.501 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-0430', repetition_id=5) failed with Harbor exception: Context length limit reached: 31654 tokens used, only 346 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:09:09.501 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:09:09.501 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-0430', repetition_id=6) failed with Harbor exception: Context length limit reached: 30515 tokens used, only 1485 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:09:09.501 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:09:09.501 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-0430', repetition_id=7) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:09:09.502 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:884 - TIS alignment: 40385/43316 tokens exact, 0 via LCS fallback, 2931 unaligned; 0 LCS-fallback messages, 1 failed messages (of 25 assistant messages). Non-zero LCS/failure means serving↔training tokenizer divergence. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:09:09.502 | INFO | examples.terminal_bench.terminal_bench_generator:generate:904 - Exception breakdown: {'ContextLengthExceededError': 5} +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:09:09.502 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 3/8 successful, 1 failed instances, 5 masked (excluded from baseline) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:09:09.502 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:948 - TIS mode: 5/8 trajectories missing logprobs (likely due to context length errors). Filled with zeros. These trajectories will have no gradient contribution from TIS. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:09:09.502 | INFO | examples.terminal_bench.terminal_bench_generator:generate:1000 - Reward component averages (n=3): antithrash=0.000, outcome=0.000, total=-0.300, terminate=-0.300 +(skyrl_entrypoint pid=1712105) 2026-06-14 05:09:14.574 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 05:10:19.469 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:10:21.141 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-2323', repetition_id=0): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:10:21.144 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 3 turns +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:10:21.145 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (931) != token count (276), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:10:21.150 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:10:21.151 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-2323', repetition_id=1) failed with Harbor exception: Context length limit reached: 30223 tokens used, only 1777 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:10:21.153 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-2323', repetition_id=2): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:10:21.155 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 19 turns +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:10:21.212 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:10:21.213 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-2323', repetition_id=3) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:10:21.213 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:10:21.213 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-2323', repetition_id=4) failed with Harbor exception: Context length limit reached: 29983 tokens used, only 2017 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:10:21.213 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:10:21.213 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-2323', repetition_id=5) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:10:21.213 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:10:21.213 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-2323', repetition_id=6) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:10:21.214 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-2323', repetition_id=7): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:10:21.216 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 14 turns +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:10:21.252 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:884 - TIS alignment: 32059/32335 tokens exact, 0 via LCS fallback, 276 unaligned; 0 LCS-fallback messages, 1 failed messages (of 36 assistant messages). Non-zero LCS/failure means serving↔training tokenizer divergence. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:10:21.252 | INFO | examples.terminal_bench.terminal_bench_generator:generate:904 - Exception breakdown: {'ContextLengthExceededError': 5} +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:10:21.253 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 3/8 successful, 1 failed instances, 5 masked (excluded from baseline) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:10:21.253 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:948 - TIS mode: 5/8 trajectories missing logprobs (likely due to context length errors). Filled with zeros. These trajectories will have no gradient contribution from TIS. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:10:21.253 | INFO | examples.terminal_bench.terminal_bench_generator:generate:1000 - Reward component averages (n=3): antithrash=0.000, outcome=0.000, total=-0.300, terminate=-0.300 +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 44%|████▍ | 28/64 [1:02:06<46:37, 77.71s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 44%|████▍ | 28/64 [1:02:06<46:37, 77.71s/it, buffer qsize=0] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:10:29.886 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-4558', repetition_id=0): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:10:29.889 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 13 turns +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:10:29.915 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #5: logprob count (3692) != token count (3693), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:10:29.946 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:10:29.946 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-4558', repetition_id=1) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:10:29.947 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:10:29.947 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-4558', repetition_id=2) failed with Harbor exception: Context length limit reached: 31393 tokens used, only 607 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:10:29.948 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-4558', repetition_id=3): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:10:29.950 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 13 turns +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:10:29.983 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-4558', repetition_id=4): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:10:29.985 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 17 turns +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:10:29.987 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (1194) != token count (688), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:10:29.993 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #3: logprob count (1179) != token count (1182), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:10:30.040 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:10:30.040 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-4558', repetition_id=5) failed with Harbor exception: Context length limit reached: 30978 tokens used, only 1022 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:10:30.040 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1096 - Exception VerifierTimeoutError not in config, using default treatment: ZERO +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:10:30.040 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-4558', repetition_id=6) failed with Harbor exception: Verifier execution timed out after 120.0 seconds (type=VerifierTimeoutError, exclude_from_baseline=False) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:10:30.042 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-4558', repetition_id=7): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:10:30.044 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 11 turns +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:10:30.082 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:884 - TIS alignment: 55806/61369 tokens exact, 0 via LCS fallback, 5563 unaligned; 0 LCS-fallback messages, 3 failed messages (of 54 assistant messages). Non-zero LCS/failure means serving↔training tokenizer divergence. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:10:30.083 | INFO | examples.terminal_bench.terminal_bench_generator:generate:904 - Exception breakdown: {'ContextLengthExceededError': 3, 'VerifierTimeoutError': 1} +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:10:30.083 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 4/8 successful, 1 failed instances, 3 masked (excluded from baseline) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:10:30.083 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:948 - TIS mode: 4/8 trajectories missing logprobs (likely due to context length errors). Filled with zeros. These trajectories will have no gradient contribution from TIS. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:10:30.083 | INFO | examples.terminal_bench.terminal_bench_generator:generate:1000 - Reward component averages (n=4): antithrash=0.000, outcome=0.750, total=0.150, terminate=0.150 +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 45%|████▌ | 29/64 [1:02:15<33:19, 57.13s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 45%|████▌ | 29/64 [1:02:15<33:19, 57.13s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) 2026-06-14 05:10:39.547 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) 2026-06-14 05:12:18.931 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:12:21.680 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:12:21.680 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-1453', repetition_id=0) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:12:21.680 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:12:21.680 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-1453', repetition_id=1) failed with Harbor exception: Context length limit reached: 31966 tokens used, only 34 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:12:21.680 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:12:21.680 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-1453', repetition_id=2) failed with Harbor exception: Context length limit reached: 30780 tokens used, only 1220 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:12:21.680 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:12:21.680 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-1453', repetition_id=3) failed with Harbor exception: Context length limit reached: 30193 tokens used, only 1807 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:12:21.680 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:12:21.680 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-1453', repetition_id=4) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:12:21.680 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:12:21.680 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-1453', repetition_id=5) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:12:21.680 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:12:21.680 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-1453', repetition_id=6) failed with Harbor exception: Context length limit reached: 31488 tokens used, only 512 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:12:21.680 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:12:21.680 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-1453', repetition_id=7) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:12:21.680 | INFO | examples.terminal_bench.terminal_bench_generator:generate:904 - Exception breakdown: {'ContextLengthExceededError': 8} +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:12:21.680 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 0/8 successful, 1 failed instances, 8 masked (excluded from baseline) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) 2026-06-14 05:12:21.680 | ERROR | examples.terminal_bench.terminal_bench_generator:generate:956 - TIS mode: ALL 8 trajectories missing logprobs. This batch cannot be used for TIS training. Check if Harbor is collecting rollout_details (collect_rollout_details=true) and if context length errors are preventing logprob collection. +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 47%|████▋ | 30/64 [1:04:07<41:36, 73.42s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 47%|████▋ | 30/64 [1:04:07<41:36, 73.42s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) 2026-06-14 05:12:36.047 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:12:38.183 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3723', repetition_id=0): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:12:38.186 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 18 turns +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:12:38.244 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3723', repetition_id=1): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:12:38.246 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 18 turns +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:12:38.249 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #2: logprob count (590) != token count (589), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:12:38.304 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3723', repetition_id=2): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:12:38.306 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 6 turns +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:12:38.323 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:12:38.323 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-3723', repetition_id=3) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:12:38.325 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-3723', repetition_id=4): reward shaped 1.000 -> 1.300 (components={'outcome': 1.0, 'terminate': 0.3, 'antithrash': 0.0, 'shaping_total': 0.3}) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:12:38.327 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 11 turns +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:12:38.329 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (5152) != token count (780), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:12:38.355 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:12:38.355 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-3723', repetition_id=5) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:12:38.355 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:12:38.355 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-3723', repetition_id=6) failed with Harbor exception: Context length limit reached: 30249 tokens used, only 1751 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:12:38.355 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:12:38.355 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-3723', repetition_id=7) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:12:38.355 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:884 - TIS alignment: 41296/42665 tokens exact, 0 via LCS fallback, 1369 unaligned; 0 LCS-fallback messages, 2 failed messages (of 53 assistant messages). Non-zero LCS/failure means serving↔training tokenizer divergence. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:12:38.355 | INFO | examples.terminal_bench.terminal_bench_generator:generate:904 - Exception breakdown: {'ContextLengthExceededError': 4} +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:12:38.356 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 4/8 successful, 1 failed instances, 4 masked (excluded from baseline) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:12:38.356 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:948 - TIS mode: 4/8 trajectories missing logprobs (likely due to context length errors). Filled with zeros. These trajectories will have no gradient contribution from TIS. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:12:38.356 | INFO | examples.terminal_bench.terminal_bench_generator:generate:1000 - Reward component averages (n=4): antithrash=0.000, outcome=0.250, total=-0.150, terminate=-0.150 +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 48%|████▊ | 31/64 [1:04:23<31:02, 56.43s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 48%|████▊ | 31/64 [1:04:23<31:02, 56.43s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) 2026-06-14 05:13:47.749 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 50%|█████ | 32/64 [1:07:28<50:38, 94.95s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 50%|█████ | 32/64 [1:07:28<50:38, 94.95s/it, buffer qsize=0] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:15:43.308 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:15:43.308 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-0112', repetition_id=0) failed with Harbor exception: Context length limit reached: 30827 tokens used, only 1173 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:15:43.308 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:15:43.308 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-0112', repetition_id=1) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:15:43.310 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-0112', repetition_id=2): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:15:43.312 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 4 turns +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:15:43.314 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (4564) != token count (362), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:15:43.330 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:15:43.330 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-0112', repetition_id=3) failed with Harbor exception: Context length limit reached: 30112 tokens used, only 1888 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:15:43.330 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1078 - Exception AgentTimeoutError classified as PASSTHROUGH (use verifier reward) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:15:43.330 | INFO | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1158 - Trajectory TrajectoryID(instance_id='pymethods2test-0112', repetition_id=4): AgentTimeoutError classified as PASSTHROUGH, using verifier reward +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:15:43.331 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-0112', repetition_id=4): reward shaped 0.000 -> -0.200 (components={'outcome': 0.0, 'terminate': -0.2, 'antithrash': 0.0, 'shaping_total': -0.2}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:15:43.333 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 5 turns +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:15:43.346 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:15:43.346 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-0112', repetition_id=5) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:15:43.346 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:15:43.346 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-0112', repetition_id=6) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:15:43.346 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:15:43.346 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-0112', repetition_id=7) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:15:43.346 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:884 - TIS alignment: 11543/11905 tokens exact, 0 via LCS fallback, 362 unaligned; 0 LCS-fallback messages, 1 failed messages (of 9 assistant messages). Non-zero LCS/failure means serving↔training tokenizer divergence. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:15:43.346 | INFO | examples.terminal_bench.terminal_bench_generator:generate:904 - Exception breakdown: {'ContextLengthExceededError': 6} +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:15:43.346 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 2/8 successful, 1 failed instances, 6 masked (excluded from baseline) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:15:43.346 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:948 - TIS mode: 6/8 trajectories missing logprobs (likely due to context length errors). Filled with zeros. These trajectories will have no gradient contribution from TIS. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:15:43.346 | INFO | examples.terminal_bench.terminal_bench_generator:generate:1000 - Reward component averages (n=2): antithrash=0.000, outcome=0.000, total=-0.250, terminate=-0.250 +(skyrl_entrypoint pid=1712105) 2026-06-14 05:16:12.773 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:16:14.338 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:16:14.338 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-1408', repetition_id=0) failed with Harbor exception: Context length limit reached: 33174 tokens used, only -1174 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:16:14.338 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:16:14.338 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-1408', repetition_id=1) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:16:14.338 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:16:14.338 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-1408', repetition_id=2) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:16:14.338 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:16:14.338 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-1408', repetition_id=3) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:16:14.338 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:16:14.338 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-1408', repetition_id=4) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:16:14.338 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1096 - Exception VerifierTimeoutError not in config, using default treatment: ZERO +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:16:14.338 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-1408', repetition_id=5) failed with Harbor exception: Verifier execution timed out after 120.0 seconds (type=VerifierTimeoutError, exclude_from_baseline=False) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:16:14.338 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:16:14.338 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-1408', repetition_id=6) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:16:14.338 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:16:14.338 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-1408', repetition_id=7) failed with Harbor exception: Context length limit reached: 30110 tokens used, only 1890 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:16:14.338 | INFO | examples.terminal_bench.terminal_bench_generator:generate:904 - Exception breakdown: {'ContextLengthExceededError': 7, 'VerifierTimeoutError': 1} +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:16:14.338 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 0/8 successful, 1 failed instances, 7 masked (excluded from baseline) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:16:14.338 | ERROR | examples.terminal_bench.terminal_bench_generator:generate:956 - TIS mode: ALL 8 trajectories missing logprobs. This batch cannot be used for TIS training. Check if Harbor is collecting rollout_details (collect_rollout_details=true) and if context length errors are preventing logprob collection. +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 52%|█████▏ | 33/64 [1:07:59<39:09, 75.78s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 52%|█████▏ | 33/64 [1:07:59<39:09, 75.78s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) 2026-06-14 05:16:23.121 | WARNING  | skyrl_train.inference_engines.inference_engine_client:_chat_completion_with_retry:451 - Inference engine error: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:16:24.513 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:16:24.514 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-2928', repetition_id=0) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:16:24.514 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:16:24.514 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-2928', repetition_id=1) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:16:24.514 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:16:24.514 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-2928', repetition_id=2) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:16:24.514 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:16:24.514 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-2928', repetition_id=3) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:16:24.516 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-2928', repetition_id=4): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:16:24.518 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 10 turns +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:16:24.563 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:16:24.564 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-2928', repetition_id=5) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:16:24.564 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:16:24.564 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-2928', repetition_id=6) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:16:24.564 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:16:24.564 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-2928', repetition_id=7) failed with Harbor exception: Context length limit reached: 30552 tokens used, only 1448 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:16:24.564 | INFO | examples.terminal_bench.terminal_bench_generator:generate:904 - Exception breakdown: {'ContextLengthExceededError': 7} +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:16:24.564 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 1/8 successful, 1 failed instances, 7 masked (excluded from baseline) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:16:24.564 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:948 - TIS mode: 7/8 trajectories missing logprobs (likely due to context length errors). Filled with zeros. These trajectories will have no gradient contribution from TIS. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:16:24.564 | INFO | examples.terminal_bench.terminal_bench_generator:generate:1000 - Reward component averages (n=1): antithrash=0.000, outcome=0.000, total=-0.300, terminate=-0.300 +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 53%|█████▎ | 34/64 [1:08:10<28:03, 56.13s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 53%|█████▎ | 34/64 [1:08:10<28:03, 56.13s/it, buffer qsize=0] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:17:34.831 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-2804', repetition_id=0): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:17:34.834 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 17 turns +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:17:34.877 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-2804', repetition_id=1): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:17:34.879 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 21 turns +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:17:34.941 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:17:34.941 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-2804', repetition_id=2) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:17:34.943 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-2804', repetition_id=3): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:17:34.945 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 9 turns +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:17:34.975 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:17:34.975 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-2804', repetition_id=4) failed with Harbor exception: Context length limit reached: 30782 tokens used, only 1218 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:17:34.977 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-2804', repetition_id=5): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:17:34.979 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 10 turns +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:17:34.987 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (4251) != token count (4186), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:17:35.014 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-2804', repetition_id=6): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:17:35.016 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 9 turns +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:17:35.035 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (17009) != token count (13783), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:17:35.054 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1078 - Exception AgentTimeoutError classified as PASSTHROUGH (use verifier reward) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:17:35.054 | INFO | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1158 - Trajectory TrajectoryID(instance_id='pymethods2test-2804', repetition_id=7): AgentTimeoutError classified as PASSTHROUGH, using verifier reward +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:17:35.055 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-2804', repetition_id=7): reward shaped 0.000 -> -0.200 (components={'outcome': 0.0, 'terminate': -0.2, 'antithrash': 0.0, 'shaping_total': -0.2}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:17:35.057 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 4 turns +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:17:35.065 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (6116) != token count (4224), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:17:35.077 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:884 - TIS alignment: 63575/85768 tokens exact, 0 via LCS fallback, 22193 unaligned; 0 LCS-fallback messages, 3 failed messages (of 70 assistant messages). Non-zero LCS/failure means serving↔training tokenizer divergence. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:17:35.077 | INFO | examples.terminal_bench.terminal_bench_generator:generate:904 - Exception breakdown: {'ContextLengthExceededError': 2} +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:17:35.077 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 6/8 successful, 1 failed instances, 2 masked (excluded from baseline) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:17:35.077 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:948 - TIS mode: 2/8 trajectories missing logprobs (likely due to context length errors). Filled with zeros. These trajectories will have no gradient contribution from TIS. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:17:35.077 | INFO | examples.terminal_bench.terminal_bench_generator:generate:1000 - Reward component averages (n=6): antithrash=0.000, outcome=0.000, total=-0.283, terminate=-0.283 +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 55%|█████▍ | 35/64 [1:09:20<29:12, 60.44s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 55%|█████▍ | 35/64 [1:09:20<29:12, 60.44s/it, buffer qsize=0] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:18:01.714 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-0709', repetition_id=0): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:18:01.716 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 8 turns +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:18:01.732 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (11365) != token count (11366), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:18:01.737 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #2: logprob count (6307) != token count (2090), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:18:01.755 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:18:01.755 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-0709', repetition_id=1) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:18:01.757 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-0709', repetition_id=2): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:18:01.758 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 10 turns +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:18:01.794 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:18:01.794 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-0709', repetition_id=3) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:18:01.794 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:18:01.794 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-0709', repetition_id=4) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:18:01.795 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-0709', repetition_id=5): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:18:01.797 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 11 turns +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:18:01.823 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:18:01.823 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-0709', repetition_id=6) failed with Harbor exception: Context length limit reached: 30968 tokens used, only 1032 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:18:01.824 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:18:01.824 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-0709', repetition_id=7) failed with Harbor exception: Context length limit reached: 30353 tokens used, only 1647 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:18:01.824 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:884 - TIS alignment: 33234/46690 tokens exact, 0 via LCS fallback, 13456 unaligned; 0 LCS-fallback messages, 2 failed messages (of 29 assistant messages). Non-zero LCS/failure means serving↔training tokenizer divergence. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:18:01.824 | INFO | examples.terminal_bench.terminal_bench_generator:generate:904 - Exception breakdown: {'ContextLengthExceededError': 5} +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:18:01.824 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 3/8 successful, 1 failed instances, 5 masked (excluded from baseline) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:18:01.824 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:948 - TIS mode: 5/8 trajectories missing logprobs (likely due to context length errors). Filled with zeros. These trajectories will have no gradient contribution from TIS. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) 2026-06-14 05:18:01.824 | INFO | examples.terminal_bench.terminal_bench_generator:generate:1000 - Reward component averages (n=3): antithrash=0.000, outcome=0.000, total=-0.300, terminate=-0.300 +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 56%|█████▋ | 36/64 [1:09:47<23:29, 50.33s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 56%|█████▋ | 36/64 [1:09:47<23:29, 50.33s/it, buffer qsize=0] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:20:03.018 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (4485) != token count (2860), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:20:03.021 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #2: logprob count (947) != token count (948), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:20:03.039 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1078 - Exception AgentTimeoutError classified as PASSTHROUGH (use verifier reward) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:20:03.039 | INFO | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1158 - Trajectory TrajectoryID(instance_id='pymethods2test-1279', repetition_id=4): AgentTimeoutError classified as PASSTHROUGH, using verifier reward +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:20:03.049 | WARNING | skyrl_train.generators.utils:get_response_ids_and_loss_mask_from_messages:1162 - TIS alignment FAILED for assistant message #1: logprob count (12536) != token count (3031), and no token ids/strings available for fallback. Zeroing this message's logprobs. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:20:03.049 | DEBUG | examples.terminal_bench.terminal_bench_generator:_classify_exception:1083 - Exception ContextLengthExceededError classified as MASK (infrastructure failure) [repeated 6x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:20:03.049 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-1279', repetition_id=7) failed with Harbor exception: (type=ContextLengthExceededError, exclude_from_baseline=True) [repeated 4x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:20:03.041 | DEBUG | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1279 - Trajectory TrajectoryID(instance_id='pymethods2test-1279', repetition_id=4): reward shaped 0.000 -> -0.300 (components={'outcome': 0.0, 'terminate': -0.3, 'antithrash': 0.0, 'shaping_total': -0.3}) [repeated 2x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:20:03.043 | DEBUG | skyrl_train.generators.utils:extract_logprobs_from_rollout_details:772 - Extracted logprobs from rollout_details: 1 turns [repeated 2x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:20:03.049 | WARNING | examples.terminal_bench.terminal_bench_generator:_process_trial_result:1181 - Trajectory TrajectoryID(instance_id='pymethods2test-1279', repetition_id=6) failed with Harbor exception: Context length limit reached: 30531 tokens used, only 1469 free tokens remaining (limit: 32000). Summarization is disabled (enable_summarize=False). (type=ContextLengthExceededError, exclude_from_baseline=True) [repeated 2x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:20:03.050 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:884 - TIS alignment: 8485/15324 tokens exact, 0 via LCS fallback, 6839 unaligned; 0 LCS-fallback messages, 3 failed messages (of 6 assistant messages). Non-zero LCS/failure means serving↔training tokenizer divergence. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:20:03.050 | INFO | examples.terminal_bench.terminal_bench_generator:generate:904 - Exception breakdown: {'ContextLengthExceededError': 6} +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:20:03.050 | INFO | examples.terminal_bench.terminal_bench_generator:generate:908 - Batch generation complete: 2/8 successful, 1 failed instances, 6 masked (excluded from baseline) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:20:03.050 | WARNING | examples.terminal_bench.terminal_bench_generator:generate:948 - TIS mode: 6/8 trajectories missing logprobs (likely due to context length errors). Filled with zeros. These trajectories will have no gradient contribution from TIS. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) 2026-06-14 05:20:03.050 | INFO | examples.terminal_bench.terminal_bench_generator:generate:1000 - Reward component averages (n=2): antithrash=0.000, outcome=0.500, total=0.000, terminate=0.000 +(skyrl_entrypoint pid=1712105) +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 58%|█████▊ | 37/64 [1:11:48<32:13, 71.60s/it, buffer qsize=0] +(skyrl_entrypoint pid=1712105) Generation Buffer Progress: 58%|█████▊ | 37/64 [1:11:48<32:13, 71.60s/it, buffer qsize=0] +slurmstepd: error: *** JOB 856555 ON jpbo-055-17 CANCELLED AT 2026-06-14T11:23:56 *** +Preserving Ray logs to /e/data1/datasets/playground/ot-baf/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/ray_logs/ +2026-06-14 11:23:56.691 | ERROR | __main__:main:134 - Training failed: Task failed because the node it was running on is dead or unavailable. Node IP: 10.128.34.177, node ID: 53bb45a0396f584a1d90d4f7b15281adc33510f232c8d3753c55797f. This can happen if the node was preempted, had a hardware failure, or its raylet crashed unexpectedly. To see node death information, use `ray list nodes --filter node_id=53bb45a0396f584a1d90d4f7b15281adc33510f232c8d3753c55797f`, check the Ray dashboard cluster page, search the node ID in the GCS logs, or use `ray logs raylet.out -ip 10.128.34.177`. +2026-06-14 11:23:56.691 | INFO | __main__:main:137 - Shutting down Ray on head node... +(skyrl_entrypoint pid=1712105) [fd-monitor] Started monitoring (every 120s) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:05:58] OK: 50 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:05:58] OK: RSS 1.38 GiB | node mem 150.6/858.0 GiB used (17.6%), avail 707.3 GiB +(skyrl_entrypoint pid=1712105) ⚙️ Running in WANDB offline mode +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) WARNING 06-14 04:06:27 [arg_utils.py:1256] The global random seed is set to 57. Since VLLM_ENABLE_V1_MULTIPROCESSING is set to False, this may affect the random state of the Python process that launched vLLM. +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) INFO 06-14 04:06:27 [model.py:529] Resolved architecture: Qwen3ForCausalLM +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) INFO 06-14 04:06:27 [model.py:1549] Using max model len 32768 +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) INFO 06-14 04:06:27 [arg_utils.py:1469] Using ray runtime env (env vars redacted): {'env_vars': {'NCCL_CUMEM_ENABLE': '***', 'NCCL_DEBUG': '***', 'NCCL_DEBUG_SUBSYS': '***', 'NCCL_SOCKET_FAMILY': '***', 'NCCL_SOCKET_IFNAME': '***', 'RAY_ADDRESS': '***', 'RAY_USE_UVLOOP': '***', 'SKYRL_WORKER_NCCL_TIMEOUT_IN_S': '***', 'TORCH_FR_BUFFER_SIZE': '***', 'TORCH_NCCL_ASYNC_ERROR_HANDLING': '***', 'TORCH_NCCL_DEBUG_INFO_TEMP_FILE': '***', 'TORCH_NCCL_DUMP_ON_TIMEOUT': '***', 'TORCH_NCCL_TRACE_BUFFER_SIZE': '***', 'VLLM_ALLOW_INSECURE_SERIALIZATION': '***', 'VLLM_ALLOW_RUNTIME_LORA_UPDATING': '***', 'VLLM_DISABLE_COMPILE_CACHE': '***', 'WANDB_API_KEY': '***'}} +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) INFO 06-14 04:06:27 [scheduler.py:224] Chunked prefill is enabled with max_num_batched_tokens=65536. +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) INFO 06-14 04:06:27 [vllm.py:690] Asynchronous scheduling is enabled. +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) WARNING 06-14 04:06:27 [vllm.py:728] Enforce eager set, overriding optimization level to -O0 +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) INFO 06-14 04:06:27 [vllm.py:846] Cudagraph is disabled under eager mode +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) WARNING 06-14 04:06:27 [serial_utils.py:57] Allowing insecure serialization using pickle due to VLLM_ALLOW_INSECURE_SERIALIZATION=1 +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) WARNING 06-14 04:06:27 [system_utils.py:140] We must use the `spawn` multiprocessing start method. Overriding VLLM_WORKER_MULTIPROC_METHOD to 'spawn'. See https://docs.vllm.ai/en/latest/usage/troubleshooting.html#python-multiprocessing for more information. Reasons: In a Ray actor and can only be spawned +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) WARNING 06-14 04:06:32 [arg_utils.py:1256] The global random seed is set to 48. Since VLLM_ENABLE_V1_MULTIPROCESSING is set to False, this may affect the random state of the Python process that launched vLLM. [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) INFO 06-14 04:06:32 [model.py:529] Resolved architecture: Qwen3ForCausalLM [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) INFO 06-14 04:06:32 [model.py:1549] Using max model len 32768 [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) INFO 06-14 04:06:32 [arg_utils.py:1469] Using ray runtime env (env vars redacted): {'env_vars': {'NCCL_CUMEM_ENABLE': '***', 'NCCL_DEBUG': '***', 'NCCL_DEBUG_SUBSYS': '***', 'NCCL_SOCKET_FAMILY': '***', 'NCCL_SOCKET_IFNAME': '***', 'RAY_ADDRESS': '***', 'RAY_USE_UVLOOP': '***', 'SKYRL_WORKER_NCCL_TIMEOUT_IN_S': '***', 'TORCH_FR_BUFFER_SIZE': '***', 'TORCH_NCCL_ASYNC_ERROR_HANDLING': '***', 'TORCH_NCCL_DEBUG_INFO_TEMP_FILE': '***', 'TORCH_NCCL_DUMP_ON_TIMEOUT': '***', 'TORCH_NCCL_TRACE_BUFFER_SIZE': '***', 'VLLM_ALLOW_INSECURE_SERIALIZATION': '***', 'VLLM_ALLOW_RUNTIME_LORA_UPDATING': '***', 'VLLM_DISABLE_COMPILE_CACHE': '***', 'WANDB_API_KEY': '***'}} [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) INFO 06-14 04:06:32 [scheduler.py:224] Chunked prefill is enabled with max_num_batched_tokens=65536. [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) INFO 06-14 04:06:32 [vllm.py:690] Asynchronous scheduling is enabled. [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) WARNING 06-14 04:06:32 [vllm.py:728] Enforce eager set, overriding optimization level to -O0 [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) INFO 06-14 04:06:32 [vllm.py:846] Cudagraph is disabled under eager mode [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) WARNING 06-14 04:06:33 [serial_utils.py:57] Allowing insecure serialization using pickle due to VLLM_ALLOW_INSECURE_SERIALIZATION=1 [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) WARNING 06-14 04:06:33 [system_utils.py:140] We must use the `spawn` multiprocessing start method. Overriding VLLM_WORKER_MULTIPROC_METHOD to 'spawn'. See https://docs.vllm.ai/en/latest/usage/troubleshooting.html#python-multiprocessing for more information. Reasons: In a Ray actor and can only be spawned [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) (EngineCore_DP0 pid=153931) INFO 06-14 04:06:35 [core.py:97] Initializing a V1 LLM engine (vdev) with config: model='/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', speculative_config=None, tokenizer='/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=32768, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, data_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=cuda, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_fallback=False, disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='', reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_metrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False, enable_mfu_metrics=False, enable_mm_processor_stats=False, enable_logging_iteration_details=False), seed=57, served_model_name=0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6, enable_prefix_caching=True, enable_chunked_prefill=True, pooler_config=None, compilation_config={'level': None, 'mode': , 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'splitting_ops': [], 'compile_mm_encoder': False, 'compile_sizes': [], 'compile_ranges_split_points': [65536], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'combo_kernels': True, 'benchmark_combo_kernel': True}, 'inductor_passes': {}, 'cudagraph_mode': , 'cudagraph_num_of_warmups': 0, 'cudagraph_capture_sizes': [], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': False, 'fuse_act_quant': False, 'fuse_attn_quant': False, 'eliminate_noops': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False, 'fuse_act_padding': False}, 'max_cudagraph_capture_size': 0, 'dynamic_shapes_config': {'type': , 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': True, 'static_all_moe_layers': []} +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) WARNING 06-14 04:06:37 [arg_utils.py:1256] The global random seed is set to 62. Since VLLM_ENABLE_V1_MULTIPROCESSING is set to False, this may affect the random state of the Python process that launched vLLM. [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) INFO 06-14 04:06:37 [model.py:529] Resolved architecture: Qwen3ForCausalLM [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) INFO 06-14 04:06:37 [model.py:1549] Using max model len 32768 [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) INFO 06-14 04:06:37 [arg_utils.py:1469] Using ray runtime env (env vars redacted): {'env_vars': {'NCCL_CUMEM_ENABLE': '***', 'NCCL_DEBUG': '***', 'NCCL_DEBUG_SUBSYS': '***', 'NCCL_SOCKET_FAMILY': '***', 'NCCL_SOCKET_IFNAME': '***', 'RAY_ADDRESS': '***', 'RAY_USE_UVLOOP': '***', 'SKYRL_WORKER_NCCL_TIMEOUT_IN_S': '***', 'TORCH_FR_BUFFER_SIZE': '***', 'TORCH_NCCL_ASYNC_ERROR_HANDLING': '***', 'TORCH_NCCL_DEBUG_INFO_TEMP_FILE': '***', 'TORCH_NCCL_DUMP_ON_TIMEOUT': '***', 'TORCH_NCCL_TRACE_BUFFER_SIZE': '***', 'VLLM_ALLOW_INSECURE_SERIALIZATION': '***', 'VLLM_ALLOW_RUNTIME_LORA_UPDATING': '***', 'VLLM_DISABLE_COMPILE_CACHE': '***', 'WANDB_API_KEY': '***'}} [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) INFO 06-14 04:06:37 [scheduler.py:224] Chunked prefill is enabled with max_num_batched_tokens=65536. [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) INFO 06-14 04:06:37 [vllm.py:690] Asynchronous scheduling is enabled. [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) WARNING 06-14 04:06:37 [vllm.py:728] Enforce eager set, overriding optimization level to -O0 [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) INFO 06-14 04:06:37 [vllm.py:846] Cudagraph is disabled under eager mode [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) WARNING 06-14 04:06:38 [serial_utils.py:57] Allowing insecure serialization using pickle due to VLLM_ALLOW_INSECURE_SERIALIZATION=1 [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) WARNING 06-14 04:06:38 [system_utils.py:140] We must use the `spawn` multiprocessing start method. Overriding VLLM_WORKER_MULTIPROC_METHOD to 'spawn'. See https://docs.vllm.ai/en/latest/usage/troubleshooting.html#python-multiprocessing for more information. Reasons: In a Ray actor and can only be spawned [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) (EngineCore_DP0 pid=153931) INFO 06-14 04:06:39 [worker_base.py:289] Injected into for extended collective_rpc calls ['_apply_fp8_weight_loader_patches', '_is_fp8_model', '_quantize_weights_for_fp8', '_restore_param_subclasses', '_undo_param_subclasses', 'begin_weight_update', 'destroy_weights_update_group', 'end_weight_update', 'init_weight_update_communicator', 'load_weights', 'read_named_weights', 'set_numa_affinity', 'test_rpc'] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) (EngineCore_DP0 pid=1507560) INFO 06-14 04:06:40 [core.py:97] Initializing a V1 LLM engine (vdev) with config: model='/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', speculative_config=None, tokenizer='/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=32768, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, data_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=cuda, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_fallback=False, disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='', reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_metrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False, enable_mfu_metrics=False, enable_mm_processor_stats=False, enable_logging_iteration_details=False), seed=43, served_model_name=0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6, enable_prefix_caching=True, enable_chunked_prefill=True, pooler_config=None, compilation_config={'level': None, 'mode': , 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'splitting_ops': [], 'compile_mm_encoder': False, 'compile_sizes': [], 'compile_ranges_split_points': [65536], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'combo_kernels': True, 'benchmark_combo_kernel': True}, 'inductor_passes': {}, 'cudagraph_mode': , 'cudagraph_num_of_warmups': 0, 'cudagraph_capture_sizes': [], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': False, 'fuse_act_quant': False, 'fuse_attn_quant': False, 'eliminate_noops': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False, 'fuse_act_padding': False}, 'max_cudagraph_capture_size': 0, 'dynamic_shapes_config': {'type': , 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': True, 'static_all_moe_layers': []} [repeated 7x across cluster] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) (EngineCore_DP0 pid=153955) INFO 06-14 04:06:42 [parallel_state.py:1234] world_size=1 rank=0 local_rank=0 distributed_init_method=tcp://10.128.56.65:53647 backend=nccl +(AsyncVLLMInferenceEngine pid=153669, ip=10.128.56.65) (EngineCore_DP0 pid=153939) INFO 06-14 04:06:42 [parallel_state.py:1445] rank 0 in world size 1 is assigned as DP rank 0, PP rank 0, PCP rank 0, TP rank 0, EP rank N/A +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) (EngineCore_DP0 pid=153955) INFO 06-14 04:06:42 [gpu_model_runner.py:4125] Starting to load model /e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6... +(pid=3949363, ip=10.128.56.78) ⚙️ Running in WANDB offline mode +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) WARNING 06-14 04:06:41 [arg_utils.py:1256] The global random seed is set to 69. Since VLLM_ENABLE_V1_MULTIPROCESSING is set to False, this may affect the random state of the Python process that launched vLLM. [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) INFO 06-14 04:06:41 [model.py:529] Resolved architecture: Qwen3ForCausalLM [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) INFO 06-14 04:06:41 [model.py:1549] Using max model len 32768 [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) INFO 06-14 04:06:41 [arg_utils.py:1469] Using ray runtime env (env vars redacted): {'env_vars': {'NCCL_CUMEM_ENABLE': '***', 'NCCL_DEBUG': '***', 'NCCL_DEBUG_SUBSYS': '***', 'NCCL_SOCKET_FAMILY': '***', 'NCCL_SOCKET_IFNAME': '***', 'RAY_ADDRESS': '***', 'RAY_USE_UVLOOP': '***', 'SKYRL_WORKER_NCCL_TIMEOUT_IN_S': '***', 'TORCH_FR_BUFFER_SIZE': '***', 'TORCH_NCCL_ASYNC_ERROR_HANDLING': '***', 'TORCH_NCCL_DEBUG_INFO_TEMP_FILE': '***', 'TORCH_NCCL_DUMP_ON_TIMEOUT': '***', 'TORCH_NCCL_TRACE_BUFFER_SIZE': '***', 'VLLM_ALLOW_INSECURE_SERIALIZATION': '***', 'VLLM_ALLOW_RUNTIME_LORA_UPDATING': '***', 'VLLM_DISABLE_COMPILE_CACHE': '***', 'WANDB_API_KEY': '***'}} [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) INFO 06-14 04:06:41 [scheduler.py:224] Chunked prefill is enabled with max_num_batched_tokens=65536. [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) INFO 06-14 04:06:41 [vllm.py:690] Asynchronous scheduling is enabled. [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) WARNING 06-14 04:06:41 [vllm.py:728] Enforce eager set, overriding optimization level to -O0 [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) INFO 06-14 04:06:41 [vllm.py:846] Cudagraph is disabled under eager mode [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) WARNING 06-14 04:06:41 [serial_utils.py:57] Allowing insecure serialization using pickle due to VLLM_ALLOW_INSECURE_SERIALIZATION=1 [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) WARNING 06-14 04:06:41 [system_utils.py:140] We must use the `spawn` multiprocessing start method. Overriding VLLM_WORKER_MULTIPROC_METHOD to 'spawn'. See https://docs.vllm.ai/en/latest/usage/troubleshooting.html#python-multiprocessing for more information. Reasons: In a Ray actor and can only be spawned [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) (EngineCore_DP0 pid=153955) INFO 06-14 04:06:43 [cuda.py:367] Using FLASH_ATTN attention backend out of potential backends: ['FLASH_ATTN', 'FLASHINFER', 'TRITON_ATTN', 'FLEX_ATTENTION']. +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) (EngineCore_DP0 pid=1507551) INFO 06-14 04:06:43 [worker_base.py:289] Injected into for extended collective_rpc calls ['_apply_fp8_weight_loader_patches', '_is_fp8_model', '_quantize_weights_for_fp8', '_restore_param_subclasses', '_undo_param_subclasses', 'begin_weight_update', 'destroy_weights_update_group', 'end_weight_update', 'init_weight_update_communicator', 'load_weights', 'read_named_weights', 'set_numa_affinity', 'test_rpc'] [repeated 7x across cluster] +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) (EngineCore_DP0 pid=3942493) INFO 06-14 04:06:46 [core.py:97] Initializing a V1 LLM engine (vdev) with config: model='/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', speculative_config=None, tokenizer='/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=32768, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, data_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=cuda, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_fallback=False, disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='', reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_metrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False, enable_mfu_metrics=False, enable_mm_processor_stats=False, enable_logging_iteration_details=False), seed=65, served_model_name=0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6, enable_prefix_caching=True, enable_chunked_prefill=True, pooler_config=None, compilation_config={'level': None, 'mode': , 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'splitting_ops': [], 'compile_mm_encoder': False, 'compile_sizes': [], 'compile_ranges_split_points': [65536], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'combo_kernels': True, 'benchmark_combo_kernel': True}, 'inductor_passes': {}, 'cudagraph_mode': , 'cudagraph_num_of_warmups': 0, 'cudagraph_capture_sizes': [], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': False, 'fuse_act_quant': False, 'fuse_attn_quant': False, 'eliminate_noops': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False, 'fuse_act_padding': False}, 'max_cudagraph_capture_size': 0, 'dynamic_shapes_config': {'type': , 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': True, 'static_all_moe_layers': []} [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) (EngineCore_DP0 pid=1496316) INFO 06-14 04:06:47 [parallel_state.py:1234] world_size=1 rank=0 local_rank=0 distributed_init_method=tcp://10.128.34.183:46747 backend=nccl [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) (EngineCore_DP0 pid=1496316) INFO 06-14 04:06:47 [parallel_state.py:1445] rank 0 in world size 1 is assigned as DP rank 0, PP rank 0, PCP rank 0, TP rank 0, EP rank N/A [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) (EngineCore_DP0 pid=1496308) INFO 06-14 04:06:47 [gpu_model_runner.py:4125] Starting to load model /e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6... [repeated 14x across cluster] +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) WARNING 06-14 04:06:48 [arg_utils.py:1256] The global random seed is set to 88. Since VLLM_ENABLE_V1_MULTIPROCESSING is set to False, this may affect the random state of the Python process that launched vLLM. [repeated 11x across cluster] +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) INFO 06-14 04:06:48 [model.py:529] Resolved architecture: Qwen3ForCausalLM [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) INFO 06-14 04:06:48 [model.py:1549] Using max model len 32768 [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) INFO 06-14 04:06:48 [arg_utils.py:1469] Using ray runtime env (env vars redacted): {'env_vars': {'NCCL_CUMEM_ENABLE': '***', 'NCCL_DEBUG': '***', 'NCCL_DEBUG_SUBSYS': '***', 'NCCL_SOCKET_FAMILY': '***', 'NCCL_SOCKET_IFNAME': '***', 'RAY_ADDRESS': '***', 'RAY_USE_UVLOOP': '***', 'SKYRL_WORKER_NCCL_TIMEOUT_IN_S': '***', 'TORCH_FR_BUFFER_SIZE': '***', 'TORCH_NCCL_ASYNC_ERROR_HANDLING': '***', 'TORCH_NCCL_DEBUG_INFO_TEMP_FILE': '***', 'TORCH_NCCL_DUMP_ON_TIMEOUT': '***', 'TORCH_NCCL_TRACE_BUFFER_SIZE': '***', 'VLLM_ALLOW_INSECURE_SERIALIZATION': '***', 'VLLM_ALLOW_RUNTIME_LORA_UPDATING': '***', 'VLLM_DISABLE_COMPILE_CACHE': '***', 'WANDB_API_KEY': '***'}} [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) INFO 06-14 04:06:48 [scheduler.py:224] Chunked prefill is enabled with max_num_batched_tokens=65536. [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) INFO 06-14 04:06:48 [vllm.py:690] Asynchronous scheduling is enabled. [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) WARNING 06-14 04:06:48 [vllm.py:728] Enforce eager set, overriding optimization level to -O0 [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) INFO 06-14 04:06:48 [vllm.py:846] Cudagraph is disabled under eager mode [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) WARNING 06-14 04:06:46 [serial_utils.py:57] Allowing insecure serialization using pickle due to VLLM_ALLOW_INSECURE_SERIALIZATION=1 [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) WARNING 06-14 04:06:46 [system_utils.py:140] We must use the `spawn` multiprocessing start method. Overriding VLLM_WORKER_MULTIPROC_METHOD to 'spawn'. See https://docs.vllm.ai/en/latest/usage/troubleshooting.html#python-multiprocessing for more information. Reasons: In a Ray actor and can only be spawned [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) (EngineCore_DP0 pid=1496327) INFO 06-14 04:06:48 [cuda.py:367] Using FLASH_ATTN attention backend out of potential backends: ['FLASH_ATTN', 'FLASHINFER', 'TRITON_ATTN', 'FLEX_ATTENTION']. [repeated 15x across cluster] +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) (EngineCore_DP0 pid=3942493) INFO 06-14 04:06:48 [worker_base.py:289] Injected into for extended collective_rpc calls ['_apply_fp8_weight_loader_patches', '_is_fp8_model', '_quantize_weights_for_fp8', '_restore_param_subclasses', '_undo_param_subclasses', 'begin_weight_update', 'destroy_weights_update_group', 'end_weight_update', 'init_weight_update_communicator', 'load_weights', 'read_named_weights', 'set_numa_affinity', 'test_rpc'] [repeated 9x across cluster] +(pid=3949439, ip=10.128.56.78) ⚙️ Running in WANDB offline mode +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) (EngineCore_DP0 pid=323631) INFO 06-14 04:06:50 [core.py:97] Initializing a V1 LLM engine (vdev) with config: model='/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', speculative_config=None, tokenizer='/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=32768, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, data_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=cuda, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_fallback=False, disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='', reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_metrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False, enable_mfu_metrics=False, enable_mm_processor_stats=False, enable_logging_iteration_details=False), seed=67, served_model_name=0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6, enable_prefix_caching=True, enable_chunked_prefill=True, pooler_config=None, compilation_config={'level': None, 'mode': , 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'splitting_ops': [], 'compile_mm_encoder': False, 'compile_sizes': [], 'compile_ranges_split_points': [65536], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'combo_kernels': True, 'benchmark_combo_kernel': True}, 'inductor_passes': {}, 'cudagraph_mode': , 'cudagraph_num_of_warmups': 0, 'cudagraph_capture_sizes': [], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': False, 'fuse_act_quant': False, 'fuse_attn_quant': False, 'eliminate_noops': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False, 'fuse_act_padding': False}, 'max_cudagraph_capture_size': 0, 'dynamic_shapes_config': {'type': , 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': True, 'static_all_moe_layers': []} [repeated 14x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) (EngineCore_DP0 pid=3942507) INFO 06-14 04:06:51 [parallel_state.py:1234] world_size=1 rank=0 local_rank=0 distributed_init_method=tcp://10.128.56.76:60817 backend=nccl [repeated 7x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) (EngineCore_DP0 pid=3942507) INFO 06-14 04:06:51 [parallel_state.py:1445] rank 0 in world size 1 is assigned as DP rank 0, PP rank 0, PCP rank 0, TP rank 0, EP rank N/A [repeated 7x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) (EngineCore_DP0 pid=3942507) INFO 06-14 04:06:52 [gpu_model_runner.py:4125] Starting to load model /e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6... [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) WARNING 06-14 04:06:49 [arg_utils.py:1256] The global random seed is set to 87. Since VLLM_ENABLE_V1_MULTIPROCESSING is set to False, this may affect the random state of the Python process that launched vLLM. [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) INFO 06-14 04:06:49 [model.py:529] Resolved architecture: Qwen3ForCausalLM [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) INFO 06-14 04:06:49 [model.py:1549] Using max model len 32768 [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) INFO 06-14 04:06:49 [arg_utils.py:1469] Using ray runtime env (env vars redacted): {'env_vars': {'NCCL_CUMEM_ENABLE': '***', 'NCCL_DEBUG': '***', 'NCCL_DEBUG_SUBSYS': '***', 'NCCL_SOCKET_FAMILY': '***', 'NCCL_SOCKET_IFNAME': '***', 'RAY_ADDRESS': '***', 'RAY_USE_UVLOOP': '***', 'SKYRL_WORKER_NCCL_TIMEOUT_IN_S': '***', 'TORCH_FR_BUFFER_SIZE': '***', 'TORCH_NCCL_ASYNC_ERROR_HANDLING': '***', 'TORCH_NCCL_DEBUG_INFO_TEMP_FILE': '***', 'TORCH_NCCL_DUMP_ON_TIMEOUT': '***', 'TORCH_NCCL_TRACE_BUFFER_SIZE': '***', 'VLLM_ALLOW_INSECURE_SERIALIZATION': '***', 'VLLM_ALLOW_RUNTIME_LORA_UPDATING': '***', 'VLLM_DISABLE_COMPILE_CACHE': '***', 'WANDB_API_KEY': '***'}} [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) INFO 06-14 04:06:49 [scheduler.py:224] Chunked prefill is enabled with max_num_batched_tokens=65536. [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) INFO 06-14 04:06:49 [vllm.py:690] Asynchronous scheduling is enabled. [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) WARNING 06-14 04:06:49 [vllm.py:728] Enforce eager set, overriding optimization level to -O0 [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) INFO 06-14 04:06:49 [vllm.py:846] Cudagraph is disabled under eager mode [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) WARNING 06-14 04:06:50 [serial_utils.py:57] Allowing insecure serialization using pickle due to VLLM_ALLOW_INSECURE_SERIALIZATION=1 [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) WARNING 06-14 04:06:50 [system_utils.py:140] We must use the `spawn` multiprocessing start method. Overriding VLLM_WORKER_MULTIPROC_METHOD to 'spawn'. See https://docs.vllm.ai/en/latest/usage/troubleshooting.html#python-multiprocessing for more information. Reasons: In a Ray actor and can only be spawned [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) (EngineCore_DP0 pid=3942507) INFO 06-14 04:06:52 [cuda.py:367] Using FLASH_ATTN attention backend out of potential backends: ['FLASH_ATTN', 'FLASHINFER', 'TRITON_ATTN', 'FLEX_ATTENTION']. [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) (EngineCore_DP0 pid=1508221) INFO 06-14 04:06:53 [worker_base.py:289] Injected into for extended collective_rpc calls ['_apply_fp8_weight_loader_patches', '_is_fp8_model', '_quantize_weights_for_fp8', '_restore_param_subclasses', '_undo_param_subclasses', 'begin_weight_update', 'destroy_weights_update_group', 'end_weight_update', 'init_weight_update_communicator', 'load_weights', 'read_named_weights', 'set_numa_affinity', 'test_rpc'] [repeated 10x across cluster] +(pid=1712285) ⚙️ Running in WANDB offline mode [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) (EngineCore_DP0 pid=1508055) INFO 06-14 04:06:55 [core.py:97] Initializing a V1 LLM engine (vdev) with config: model='/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', speculative_config=None, tokenizer='/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=32768, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, data_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=cuda, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_fallback=False, disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='', reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_metrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False, enable_mfu_metrics=False, enable_mm_processor_stats=False, enable_logging_iteration_details=False), seed=76, served_model_name=0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6, enable_prefix_caching=True, enable_chunked_prefill=True, pooler_config=None, compilation_config={'level': None, 'mode': , 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'splitting_ops': [], 'compile_mm_encoder': False, 'compile_sizes': [], 'compile_ranges_split_points': [65536], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'combo_kernels': True, 'benchmark_combo_kernel': True}, 'inductor_passes': {}, 'cudagraph_mode': , 'cudagraph_num_of_warmups': 0, 'cudagraph_capture_sizes': [], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': False, 'fuse_act_quant': False, 'fuse_attn_quant': False, 'eliminate_noops': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False, 'fuse_act_padding': False}, 'max_cudagraph_capture_size': 0, 'dynamic_shapes_config': {'type': , 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': True, 'static_all_moe_layers': []} [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) (EngineCore_DP0 pid=323627) INFO 06-14 04:06:56 [parallel_state.py:1234] world_size=1 rank=0 local_rank=0 distributed_init_method=tcp://10.128.56.67:38757 backend=nccl [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) (EngineCore_DP0 pid=323627) INFO 06-14 04:06:56 [parallel_state.py:1445] rank 0 in world size 1 is assigned as DP rank 0, PP rank 0, PCP rank 0, TP rank 0, EP rank N/A [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) (EngineCore_DP0 pid=323627) INFO 06-14 04:06:56 [gpu_model_runner.py:4125] Starting to load model /e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6... [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) (EngineCore_DP0 pid=323622) INFO 06-14 04:06:57 [cuda.py:367] Using FLASH_ATTN attention backend out of potential backends: ['FLASH_ATTN', 'FLASHINFER', 'TRITON_ATTN', 'FLEX_ATTENTION']. [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) (EngineCore_DP0 pid=3946095) INFO 06-14 04:06:58 [worker_base.py:289] Injected into for extended collective_rpc calls ['_apply_fp8_weight_loader_patches', '_is_fp8_model', '_quantize_weights_for_fp8', '_restore_param_subclasses', '_undo_param_subclasses', 'begin_weight_update', 'destroy_weights_update_group', 'end_weight_update', 'init_weight_update_communicator', 'load_weights', 'read_named_weights', 'set_numa_affinity', 'test_rpc'] [repeated 13x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) (EngineCore_DP0 pid=1496316) INFO 06-14 04:07:00 [default_loader.py:293] Loading weights took 11.87 seconds +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) (EngineCore_DP0 pid=1496303) INFO 06-14 04:07:01 [gpu_model_runner.py:4222] Model loading took 15.27 GiB memory and 12.891212 seconds +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) (EngineCore_DP0 pid=4037857) INFO 06-14 04:06:59 [core.py:97] Initializing a V1 LLM engine (vdev) with config: model='/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', speculative_config=None, tokenizer='/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=32768, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, data_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=cuda, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_fallback=False, disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='', reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_metrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False, enable_mfu_metrics=False, enable_mm_processor_stats=False, enable_logging_iteration_details=False), seed=87, served_model_name=0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6, enable_prefix_caching=True, enable_chunked_prefill=True, pooler_config=None, compilation_config={'level': None, 'mode': , 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'splitting_ops': [], 'compile_mm_encoder': False, 'compile_sizes': [], 'compile_ranges_split_points': [65536], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'combo_kernels': True, 'benchmark_combo_kernel': True}, 'inductor_passes': {}, 'cudagraph_mode': , 'cudagraph_num_of_warmups': 0, 'cudagraph_capture_sizes': [], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': False, 'fuse_act_quant': False, 'fuse_attn_quant': False, 'eliminate_noops': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False, 'fuse_act_padding': False}, 'max_cudagraph_capture_size': 0, 'dynamic_shapes_config': {'type': , 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': True, 'static_all_moe_layers': []} [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) (EngineCore_DP0 pid=3945796) INFO 06-14 04:07:02 [parallel_state.py:1234] world_size=1 rank=0 local_rank=0 distributed_init_method=tcp://10.128.56.66:37669 backend=nccl [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) (EngineCore_DP0 pid=3945796) INFO 06-14 04:07:02 [parallel_state.py:1445] rank 0 in world size 1 is assigned as DP rank 0, PP rank 0, PCP rank 0, TP rank 0, EP rank N/A [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) (EngineCore_DP0 pid=1496327) INFO 06-14 04:07:03 [gpu_worker.py:373] Available KV cache memory: 49.32 GiB +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) (EngineCore_DP0 pid=1496327) INFO 06-14 04:07:03 [kv_cache_utils.py:1307] GPU KV cache size: 359,120 tokens +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) (EngineCore_DP0 pid=1496327) INFO 06-14 04:07:03 [kv_cache_utils.py:1312] Maximum concurrency for 32,768 tokens per request: 10.96x +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) (EngineCore_DP0 pid=3945796) INFO 06-14 04:07:02 [gpu_model_runner.py:4125] Starting to load model /e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6... [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) (EngineCore_DP0 pid=1496327) INFO 06-14 04:07:03 [kernel_warmup.py:44] Skipping FlashInfer autotune because it is disabled. +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) (EngineCore_DP0 pid=1496303) INFO 06-14 04:07:03 [core.py:278] init engine (profile, create kv cache, warmup model) took 2.72 seconds +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) (EngineCore_DP0 pid=3945796) INFO 06-14 04:07:03 [cuda.py:367] Using FLASH_ATTN attention backend out of potential backends: ['FLASH_ATTN', 'FLASHINFER', 'TRITON_ATTN', 'FLEX_ATTENTION']. [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) (EngineCore_DP0 pid=1496303) WARNING 06-14 04:07:04 [serial_utils.py:57] Allowing insecure serialization using pickle due to VLLM_ALLOW_INSECURE_SERIALIZATION=1 +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) (EngineCore_DP0 pid=1496303) INFO 06-14 04:07:04 [vllm.py:690] Asynchronous scheduling is enabled. +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) (EngineCore_DP0 pid=1496303) WARNING 06-14 04:07:04 [vllm.py:735] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored. +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) (EngineCore_DP0 pid=1496303) INFO 06-14 04:07:04 [vllm.py:846] Cudagraph is disabled under eager mode +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) (EngineCore_DP0 pid=4037857) INFO 06-14 04:07:04 [worker_base.py:289] Injected into for extended collective_rpc calls ['_apply_fp8_weight_loader_patches', '_is_fp8_model', '_quantize_weights_for_fp8', '_restore_param_subclasses', '_undo_param_subclasses', 'begin_weight_update', 'destroy_weights_update_group', 'end_weight_update', 'init_weight_update_communicator', 'load_weights', 'read_named_weights', 'set_numa_affinity', 'test_rpc'] [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) WARNING 06-14 04:07:04 [model.py:1350] Default vLLM sampling parameters have been overridden by the model's `generation_config.json`: `{'temperature': 0.6, 'top_k': 20, 'top_p': 0.95}`. If this is not intended, please relaunch vLLM instance with `--generation-config vllm`. +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) (EngineCore_DP0 pid=3942493) INFO 06-14 04:07:05 [default_loader.py:293] Loading weights took 12.59 seconds [repeated 19x across cluster] +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO cudaDriverVersion 13020 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO NCCL version 2.27.7+cuda13.0 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO NET/Plugin: Could not find: libnccl-net.so. +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO NET/IB : Using [0]mlx5_0:1/IB [1]mlx5_1:1/IB [2]mlx5_2:1/IB [3]mlx5_3:1/IB [RO]; OOB ib0:10.128.34.177<0> +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Initialized NET plugin IB +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Assigned NET plugin IB to comm +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Using network IB +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO DMA-BUF is available on GPU device 0 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO ncclCommInitRankConfig comm 0x400e612dd240 rank 5 nranks 8 cudaDev 0 nvmlDev 1 busId 1901000 commId 0x85f66e877ed1b601 - Init START +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO RAS client listening socket at 127.0.0.1<28028> +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO NCCL_NET_GDR_LEVEL set by environment to LOC +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Setting affinity for GPU 1 to 72-143 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO NVLS multicast support is not available on dev 0 (NVLS_NCHANNELS 0) +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO comm 0x400e612dd240 rank 5 nRanks 8 nNodes 2 localRanks 4 localRank 1 MNNVL 0 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Trees [0] 6/-1/-1->5->4 [1] 6/-1/-1->5->1 [2] 7/-1/-1->5->4 [3] -1/-1/-1->5->6 [4] 6/-1/-1->5->4 [5] 6/1/-1->5->-1 [6] 7/-1/-1->5->4 [7] -1/-1/-1->5->6 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO P2P Chunksize set to 131072 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO PROFILER/Plugin: Could not find: libnccl-profiler.so. +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO [Proxy Service] Device 0 CPU core 96 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712617 [0] NCCL INFO [Proxy Service UDS] Device 0 CPU core 141 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO Allocated shareable buffer 0x400f10600000 size 10485760 ipcDesc 0x400f58008b70 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO Allocated shareable buffer 0x400f11000000 size 10485760 ipcDesc 0x400f580099f0 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Channel 01/0 : 5[1] -> 6[2] via P2P/IPC +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO Allocated shareable buffer 0x400f11a00000 size 2097152 ipcDesc 0x400f5800a800 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Channel 05/0 : 5[1] -> 6[2] via P2P/IPC +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO Allocated shareable buffer 0x400f11c00000 size 2097152 ipcDesc 0x400f5800b5f0 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712618 [0] NCCL INFO [Proxy Progress] Device 0 CPU core 143 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Channel 02/0 : 1[1] -> 5[1] [receive] via NET/IB/1 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Channel 06/0 : 1[1] -> 5[1] [receive] via NET/IB/1 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Channel 03/0 : 5[1] -> 1[1] [send] via NET/IB/1 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Channel 07/0 : 5[1] -> 1[1] [send] via NET/IB/1 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO Allocated shareable buffer 0x400f11e00000 size 10485760 ipcDesc 0x400f5800e4a0 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO Allocated shareable buffer 0x400f12800000 size 10485760 ipcDesc 0x400f5800f270 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO Allocated shareable buffer 0x400f13200000 size 10485760 ipcDesc 0x400f58010040 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO Allocated shareable buffer 0x400f13c00000 size 10485760 ipcDesc 0x400f58010e10 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Channel 00/0 : 5[1] -> 4[0] via P2P/IPC +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO Allocated shareable buffer 0x400f14600000 size 2097152 ipcDesc 0x400f58010e10 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Channel 02/0 : 5[1] -> 4[0] via P2P/IPC +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO Allocated shareable buffer 0x400f14800000 size 2097152 ipcDesc 0x400f58010e10 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Channel 04/0 : 5[1] -> 4[0] via P2P/IPC +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO Allocated shareable buffer 0x400f14a00000 size 2097152 ipcDesc 0x400f58010e10 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Channel 06/0 : 5[1] -> 4[0] via P2P/IPC +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO Allocated shareable buffer 0x400f14c00000 size 2097152 ipcDesc 0x400f58010e10 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Imported shareable buffer device 0 size 10485760 ptr 0x400f14e00000 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Imported shareable buffer device 0 size 2097152 ptr 0x400f15800000 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Imported shareable buffer device 0 size 10485760 ptr 0x400f15a00000 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Imported shareable buffer device 0 size 2097152 ptr 0x400f16400000 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Imported shareable buffer device 0 size 2097152 ptr 0x400f16600000 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Imported shareable buffer device 0 size 2097152 ptr 0x400f16800000 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Imported shareable buffer device 0 size 10485760 ptr 0x400f16a00000 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Imported shareable buffer device 0 size 2097152 ptr 0x400f17400000 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Imported shareable buffer device 0 size 10485760 ptr 0x400f17600000 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Imported shareable buffer device 0 size 10485760 ptr 0x400f18000000 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Imported shareable buffer device 0 size 2097152 ptr 0x400f18a00000 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Imported shareable buffer device 0 size 10485760 ptr 0x400f18c00000 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Connected all rings, use ring PXN 0 GDR 0 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO Allocated shareable buffer 0x400f19600000 size 10485760 ipcDesc 0x400f580162f0 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO Allocated shareable buffer 0x400f1a000000 size 10485760 ipcDesc 0x400f580162f0 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO Allocated shareable buffer 0x400f1aa00000 size 10485760 ipcDesc 0x400f580162f0 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO Allocated shareable buffer 0x400f1b400000 size 10485760 ipcDesc 0x400f580162f0 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Channel 00/0 : 5[1] -> 6[2] via P2P/IPC +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO Allocated shareable buffer 0x400f1be00000 size 2097152 ipcDesc 0x400f580162f0 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Channel 03/0 : 5[1] -> 6[2] via P2P/IPC +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO Allocated shareable buffer 0x400f1c000000 size 2097152 ipcDesc 0x400f580162f0 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Channel 04/0 : 5[1] -> 6[2] via P2P/IPC +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO Allocated shareable buffer 0x400f1c200000 size 2097152 ipcDesc 0x400f580162f0 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Channel 07/0 : 5[1] -> 6[2] via P2P/IPC +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO Allocated shareable buffer 0x400f1c400000 size 2097152 ipcDesc 0x400f580162f0 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Channel 02/0 : 5[1] -> 7[3] via P2P/IPC +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO Allocated shareable buffer 0x400f1c600000 size 2097152 ipcDesc 0x400f580162f0 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Channel 06/0 : 5[1] -> 7[3] via P2P/IPC +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO Allocated shareable buffer 0x400f1c800000 size 2097152 ipcDesc 0x400f580162f0 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Channel 01/0 : 1[1] -> 5[1] [receive] via NET/IB/1 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Channel 05/0 : 1[1] -> 5[1] [receive] via NET/IB/1 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Channel 01/0 : 5[1] -> 1[1] [send] via NET/IB/1 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712583 [0] NCCL INFO Channel 05/0 : 5[1] -> 1[1] [send] via NET/IB/1 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO Allocated shareable buffer 0x400f1ca00000 size 10485760 ipcDesc 0x400f5833ed90 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO Allocated shareable buffer 0x400f1d400000 size 10485760 ipcDesc 0x400f5833ed90 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO Allocated shareable buffer 0x400f1de00000 size 10485760 ipcDesc 0x400f5833ed90 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 [0] NCCL INFO Allocated shareable buffer 0x400f1e800000 size 10485760 ipcDesc 0x400f5833ed90 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712615 +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) (EngineCore_DP0 pid=3942483) INFO 06-14 04:07:05 [gpu_model_runner.py:4222] Model loading took 15.27 GiB memory and 13.507060 seconds [repeated 19x across cluster] +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-1 +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712582 [0] NCCL INFO Channel 05/0 : 7[3] -> +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712614 [0] NCCL INFO Allocated shareable buffer 0x400effa00000 si +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949680 [0] NCCL INFO Channel 00/08 : 0 1 2 3 7 6 5 4 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949680 [0] NCCL INFO Channel 01/08 : 0 4 5 6 7 3 2 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949680 [0] NCCL INFO Channel 02/08 : 0 3 1 5 4 7 6 2 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949680 [0] NCCL INFO Channel 03/08 : 0 3 2 6 4 7 5 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949680 [0] NCCL INFO Channel 04/08 : 0 1 2 3 7 6 5 4 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949680 [0] NCCL INFO Channel 05/08 : 0 4 5 6 7 3 2 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949680 [0] NCCL INFO Channel 06/08 : 0 3 1 5 4 7 6 2 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949680 [0] NCCL INFO Channel 07/08 : 0 3 2 6 4 7 5 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949680 [0] NCCL INFO Check P2P Type isAllDirectP2p 1 directMode 0 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949680 [0] NCCL INFO Connected all trees +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949680 [0] NCCL INFO threadThresholds 8/8/64 | 64/8/64 | 512 | 512 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949680 [0] NCCL INFO 8 coll channels, 8 collnet channels, 0 nvls channels, 8 p2p channels, 2 p2p channels per peer +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949680 [0] NCCL INFO CC Off, workFifoBytes 1048576 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949680 [0] NCCL INFO TUNER/Plugin: Could not find: libnccl-tuner.so. Using internal tuner plugin. +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949680 [0] NCCL INFO ncclCommInitRankConfig comm 0x400e166a4a60 rank 0 nranks 8 cudaDev 0 nvmlDev 0 busId 901000 commId 0x85f66e877ed1b601 - Init COMPLETE +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949680 [0] NCCL INFO Init timings - ncclCommInitRankConfig: rank 0 nranks 8 total 2.67 (kernels 0.18, alloc 1.83, bootstrap 0.00, allgathers 0.00, topo 0.02, graphs 0.01, connections 0.63, rest 0.00) +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO Broadcast: opCount 0 sendbuff 0x400ec0000000 recvbuff 0x400ec0000000 count 622329856 datatype 9 op 0 root 0 comm 0x400e612dd240 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:17 +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712623 +(FSDPPolicyWorkerBase pid=1712286) 6[2] via P2P/IPC +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286: +(FSDPPolicyWorkerBase pid=1712285) ze 2097152 ipcDesc 0x400f3827fed0 +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285: +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 00/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 01/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 02/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 03/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 04/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 05/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 06/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 07/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 08/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 09/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 10/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 11/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 12/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 13/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 14/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 15/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 16/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 17/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 18/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 19/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 20/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 21/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 22/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 23/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 24/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 25/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 26/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 27/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 28/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 29/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 30/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 31/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 32/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 33/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 34/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 35/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 36/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 37/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 38/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 39/40 : 0 1 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Check P2P Type isAllDirectP2p 0 directMode 0 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO Channel 39/0 : 1[0] -> 0[0] [re +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) jpbo-102-30:3949441:3949726 [0] NCCL INFO Channel 39/0 : 1[1] -> 0[1] [ +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712623 [0] NCCL INFO Connected binomial trees +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712643 [0] NCCL INFO Allocated share +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) ceive] via NET/IB/0 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949725 [0] NCCL INFO CC Off, workFifoBytes 1048576 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jp +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) receive] via NET/IB/1 +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) [2] [receive] via NET/IB/2 +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) jpbo-102-30:3949440:3949744 [0] NCCL INFO Channel 14 +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949746 [0] NCCL INFO Ch +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712645 [0] NCCL INFO Allocated shareable buffer 0x338200000 size 2 +(FSDPPolicyWorkerBase pid=1712284) able buffer 0x4013fc000000 size 10485760 ipcDesc 0x400fd000df70 +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712643 [0] NCCL INFO Allocated shareable buffer 0x400ebcc +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712641 [0] NCCL INFO Imported shareable buffer device 0 size 1048576 +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) -> 2[2] via P2P/IPC +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) jpbo-102-30:3949441:3949745 [0] NCCL INFO Imported shareable buffer device 0 si +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) /0 : 2[2] -> 3[3] via P2P/IPC +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) jpbo-102-30:3949440:3949744 [0] NCCL INFO Imported shareable buffer device 0 s +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) annel 15/0 : 3[3] -> 0[0] via P2P/IPC +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO Recv: opCount 0 sendbuff (nil) recvbuff 0x400f60000000 count 155582464 datatype 9 op 0 root 0 comm 0x400e116be640 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439: +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) 0x401430a00000 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x4013728c0000 count 155582464 datatype 9 op 0 root 1 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401385180000 count 155582464 datatype 9 op 0 root 2 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401397a40000 count 155582464 datatype 9 op 0 root 3 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401120800000 count 4194304 datatype 9 op 0 root 1 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401121000000 count 4194304 datatype 9 op 0 root 2 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401121800000 count 4194304 datatype 9 op 0 root 3 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401136a00000 count 1048576 datatype 9 op 0 root 1 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401136c00000 count 1048576 datatype 9 op 0 root 2 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401136e00000 count 1048576 datatype 9 op 0 root 3 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401136a00000 count 1048576 datatype 9 op 0 root 1 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401136c00000 count 1048576 datatype 9 op 0 root 2 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401136e00000 count 1048576 datatype 9 op 0 root 3 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401120800000 count 4194304 datatype 9 op 0 root 1 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401121000000 count 4194304 datatype 9 op 0 root 2 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401121800000 count 4194304 datatype 9 op 0 root 3 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa02a40 count 32 datatype 9 op 0 root 1 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa02a80 count 32 datatype 9 op 0 root 2 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa02ac0 count 32 datatype 9 op 0 root 3 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa02a40 count 32 datatype 9 op 0 root 1 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa02a80 count 32 datatype 9 op 0 root 2 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa02ac0 count 32 datatype 9 op 0 root 3 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401129000000 count 12582912 datatype 9 op 0 root 1 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x40112a800000 count 12582912 datatype 9 op 0 root 2 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x40112c000000 count 12582912 datatype 9 op 0 root 3 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401129000000 count 12582912 datatype 9 op 0 root 1 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x40112a800000 count 12582912 datatype 9 op 0 root 2 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x40112c000000 count 12582912 datatype 9 op 0 root 3 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401129000000 count 12582912 datatype 9 op 0 root 1 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x40112a800000 count 12582912 datatype 9 op 0 root 2 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x40112c000000 count 12582912 datatype 9 op 0 root 3 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount a sendbuff 0x400ebfa00000 recvbuff 0x400ebfa00000 count 4096 datatype 9 op 0 root 0 comm 0x400e16974fa0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa00800 count 1024 datatype 9 op 0 root 1 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa01000 count 1024 datatype 9 op 0 root 2 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa01800 count 1024 datatype 9 op 0 root 3 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount b sendbuff 0x400ebfa00000 recvbuff 0x400ebfa00000 count 4096 datatype 9 op 0 root 0 comm 0x400e16974fa0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa00800 count 1024 datatype 9 op 0 root 1 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa01000 count 1024 datatype 9 op 0 root 2 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa01800 count 1024 datatype 9 op 0 root 3 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount c sendbuff 0x401155400000 recvbuff 0x401155400000 count 16777216 datatype 9 op 0 root 0 comm 0x400e16974fa0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401155c00000 count 4194304 datatype 9 op 0 root 1 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401156400000 count 4194304 datatype 9 op 0 root 2 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401156c00000 count 4194304 datatype 9 op 0 root 3 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount d sendbuff 0x401123000000 recvbuff 0x401123000000 count 4194304 datatype 9 op 0 root 0 comm 0x400e16974fa0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401123200000 count 1048576 datatype 9 op 0 root 1 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401123400000 count 1048576 datatype 9 op 0 root 2 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401123600000 count 1048576 datatype 9 op 0 root 3 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount a sendbuff 0x401123000000 recvbuff 0x401123000000 count 4194304 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount e sendbuff 0x401123000000 recvbuff 0x401123000000 count 4194304 datatype 9 op 0 root 0 comm 0x400e16974fa0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401123200000 count 1048576 datatype 9 op 0 root 1 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401123400000 count 1048576 datatype 9 op 0 root 2 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401123600000 count 1048576 datatype 9 op 0 root 3 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount b sendbuff 0x401155400000 recvbuff 0x401155400000 count 16777216 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount f sendbuff 0x401155400000 recvbuff 0x401155400000 count 16777216 datatype 9 op 0 root 0 comm 0x400e16974fa0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401155c00000 count 4194304 datatype 9 op 0 root 1 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401156400000 count 4194304 datatype 9 op 0 root 2 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401156c00000 count 4194304 datatype 9 op 0 root 3 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount c sendbuff 0x400ebfa02a00 recvbuff 0x400ebfa02a00 count 128 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa02a40 count 32 datatype 9 op 0 root 1 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa02a80 count 32 datatype 9 op 0 root 2 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa02ac0 count 32 datatype 9 op 0 root 3 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount c sendbuff 0x400ebfa02a00 recvbuff 0x400ebfa02a00 count 128 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa02a40 count 32 datatype 9 op 0 root 1 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa02a80 count 32 datatype 9 op 0 root 2 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa02ac0 count 32 datatype 9 op 0 root 3 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount c sendbuff 0x401127800000 recvbuff 0x401127800000 count 50331648 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401129000000 count 12582912 datatype 9 op 0 root 1 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x40112a800000 count 12 +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) ze 10485760 ptr 0x401027a00000 +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) jpbo-102-30:3949441:3949665 [0] NCCL INFO Broadcast: opCount a5 sendbuff 0x400e99e14600 recvbuff 0x400e99e14600 count 4096 datatype 9 op 0 +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) ize 2097152 ptr 0x401049c00000 +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) jpbo-102-30:3949440:3949657 [0] NCCL INFO Broadcast: opCount aa sendbuff 0x400eb9e12600 recvbuff 0x400eb9e12600 count 128 datatype 9 op 0 root 0 comm 0x400e2d5a7c40 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) jpbo-102-30:3949440:3949657 [0] NCCL INFO Broadcast: opCount ab sendbuff 0x400eb9e12a00 recvbuff 0x400eb9e12a00 count 128 datatype 9 op 0 root 0 comm 0x400e2d5a7c40 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) jpbo-102-30:3949440:3949657 [0] NCCL INFO Broadcast: opCount ac sendbuff 0x40106ac00000 recvbuff 0x40106ac00000 count 50331648 datatype 9 op 0 root 0 comm 0x400e2d5a7c40 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) jpbo-102-30:3949440:3949657 [0] NCCL INFO Broadcast: opCount ad sendbuff 0x401076c00000 recvbuff 0x401076c00000 count 50331648 datatype 9 op 0 root 0 comm 0x400e2d5a7c40 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) jpbo-102-30:3949440:3949657 [0] NCCL INFO Broadcast: opCount ae sendbuff 0x40106ac00000 recvbuff 0x40106ac00000 count 50331648 datatype 9 op 0 root 0 comm 0x400e2d5a7c40 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) jpbo-102-30:3949440:3949657 [0] NCCL INFO Broadcast: opCount af sendbuff 0x400eb9e14600 recvbuff 0x400eb9e14600 count 4096 datatype 9 op 0 root 0 comm 0x400e2d5a7c40 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) jpbo-102-30:3949440:3949657 [0] NCCL INFO Broadcast: opCount 74 sendbuff 0x40106ac00000 recvbuff 0 +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO Recv +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) root 0 comm 0x400e055a91a0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) : opCount 0 sendbuff (nil) recvbuff 0x400e99e12800 count 32 datatype 9 op 0 root 0 comm 0x400e116be640 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3 +(FSDPPolicyWorkerBase pid=1712287) 097152 ipcDesc 0x400ff000ed30 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO Broadc +(FSDPPolicyWorkerBase pid=1712284) 00000 size 10485760 ipcDesc 0x400fd000df70 +(FSDPPolicyWorkerBase pid=1712286) 0 ptr 0x332800000 +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO Broadcast: opCount 92 sendbuff 0x401071000000 recvbuff 0x401071000000 count 4194304 datatype 9 op 0 root 0 comm 0 +(FSDPPolicyWorkerBase pid=1712285) jpbo- +(FSDPPolicyWorkerBase pid=1712287) ast: opCount 5b sendbuff 0x401091000000 recvbuff 0x401091000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e612dd240 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount ba sendbuff 0x400ebfa43400 recvbuff 0x400ebfa43400 count 4096 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount bb sendbuff 0x400ebfa45400 recvbuff 0x400ebfa45400 count 4096 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount bc sendbuff 0x401392600000 recvbuff 0x401392600000 count 16777216 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount bd sendbuff 0x401394600000 recvbuff 0x401394600000 count 4194304 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount be sendbuff 0x401392800000 recvbuff 0x401392800000 count 4194304 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount bf sendbuff 0x401393200000 recvbuff 0x401393200000 count 16777216 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401394200000 cou +(FSDPPolicyWorkerBase pid=1712286) x400e152dd8b0 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO Recv: opCount 0 sendbuff (nil) recvbuff 0x400e99e11200 count 32 datatype +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO Recv: opCount 0 sendbuff (nil) recvbuff 0x401038400000 count 12582912 da +(FSDPPolicyWorkerBase pid=1712284) nt 4194304 datatype 9 op 0 root 2 comm 0x400e62a9d6a0 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount ca sendbuff 0x4015e5800000 recvbuff 0x4015e5800000 count 16777216 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount cb sendbuff 0x400ebfa42a00 recvbuff 0x400ebfa42a00 count 128 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount cc sendbuff 0x400ebfa43e00 recvbuff 0x400ebfa43e00 count 128 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount cd sendbuff 0x401635000000 recvbuff 0x401635000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount ce sendbuff 0x4015eb000000 recvbuff 0x4015eb000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount cf sendbuff 0x401635000000 recvbuff 0x401635000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL +(FSDPPolicyWorkerBase pid=1712286) 9 op 0 root 0 comm 0x400e156c49a0 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO Broadcast: opCount af sendbu +(FSDPPolicyWorkerBase pid=1712285) tatype 9 op 0 root 0 comm 0x400e416c4290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO Broadcast: opCount c7 sendbuff 0x400f8000 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO Recv: opCount 0 sendbuff (nil) recvbuff 0x401056600000 count 12582912 +(FSDPPolicyWorkerBase pid=1712284) INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa48c00 count 1024 datatype 9 op 0 root 2 comm 0x400e62a9d6a0 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount da sendbuff 0x401635000000 recvbuff 0x401635000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount db sendbuff 0x400ebfa45c00 recvbuff 0x400ebfa45c00 count 4096 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount dc sendbuff 0x400ebfa48400 recvbuff 0x400ebfa48400 count 4096 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount dd sendbuff 0x4015f1000000 recvbuff 0x4015f1000000 count 16777216 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount de sendbuff 0x4015f3000000 recvbuff 0x4015f3000000 count 4194304 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount df sendbuff 0x4015f1000000 recvbuff 0x4015f1000000 count 4194304 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401636800000 count 12582912 datatype 9 op 0 root 1 comm 0 +(FSDPPolicyWorkerBase pid=1712286) ff 0x400e99e14600 recvbuff 0x400e99e14600 count 4096 datatype 9 op 0 root 0 comm 0x400e155aa040 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL IN +(FSDPPolicyWorkerBase pid=1712285) 0000 recvbuff 0x400f80000000 count 16777216 datatype 9 op 0 root 0 comm 0x400e415a97d0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712287) datatype 9 op 0 root 0 comm 0x400e616c3cb0 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] N +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount ea sendbuff 0x4015f7000000 recvbuff 0x4015f7000000 count 4194304 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount eb sendbuff 0x4015f7800000 recvbuff 0x4015f7800000 count 16777216 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount ec sendbuff 0x400ebfa47600 recvbuff 0x400ebfa47600 count 128 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Send: opCount 0 sendbuff (nil) r +(FSDPPolicyWorkerBase pid=1712286) FO Broadcast: opCount be sendbuff 0x400f90a00000 recvbuff 0x400f90a00000 count 4194304 datatype 9 op 0 root 0 comm 0x400e152dd8b0 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712285) INFO Broadcast: opCount 8a sendbuff 0x400e99e17600 recvbuff 0x400e99e17600 count 128 datatype 9 op 0 root 0 comm 0x400e412dd520 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO Broadcast: opCount e4 sendbuff 0x400f92000000 recvbuff 0x400f92000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e415a97d0 [nranks=2] stream (nil +(FSDPPolicyWorkerBase pid=1712287) CCL INFO Broadcast: opCount 8a sendbuff 0x400eb9e17600 recvbuff 0x400eb9e17600 count 128 datatype 9 op 0 root 0 comm 0x400e612dd240 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO Broadcast: opCount e4 sendbuff 0x400fb2000000 recvbuff 0x400fb2000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e615a91f0 [nranks=2] stream ( +(FSDPPolicyWorkerBase pid=1712284) ecvbuff 0x400ebfa47640 count 32 datatype 9 op 0 root 1 comm 0x400e62a9d6a0 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount ed sendbuff 0x400ebfa47a00 recvbuff 0x400ebfa47a00 count 128 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount ee sendbuff 0x4015f7000000 recvbuff 0x4015f7000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount ef sendbuff 0x4013c0000000 recvbuff 0x4013c0000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712286) +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO Broadcast: opCount db sendbuff 0x400e99e19600 recvbuff 0x400e99e19600 count 4096 datatype 9 op 0 root +(FSDPPolicyWorkerBase pid=1712285) ) +(FSDPPolicyWorkerBase pid=1712284) INFO Send: opCount 0 sendbuff (nil) recvbuff 0x40163aa00000 count 1048576 datatype 9 op 0 root 1 comm 0x400e62a9d6a0 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount fa sendbuff 0x4013c6000000 recvbuff 0x4013c6000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount fb sendbuff 0x4013c0000000 recvbuff 0x4013c0000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount fc sendbuff 0x400ebfa4ac00 recvbuff 0x400ebfa4ac00 count 4096 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount fd sendbuff 0x400ebfa4cc00 recvbuff 0x400ebfa4cc00 count 4096 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount fe sendbuff 0x4013c0000000 recvbuff 0x4013c0000000 count 16777216 datatype 9 op 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-0 +(FSDPPolicyWorkerBase pid=1712286) 0 comm 0x400e152dd8b0 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO Recv: opCount 0 sendbuff (nil) recvbuff 0x400fa3800000 coun +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO Broadcast: opCount ff sendbuff 0x400f97800000 recvbuff 0x400f97800000 count 4194304 datatype 9 op 0 root 0 comm 0x400e415a97d0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO Recv: opCount 0 sendbuff (nil) recvbuff 0x400f9b200000 +(FSDPPolicyWorkerBase pid=1712287) nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount 107 sendbuff 0x400ebfa4ac00 recvbuff 0x400ebfa4ac00 count 4096 datatype 9 o +(FSDPPolicyWorkerBase pid=1712286) t 1048576 datatype 9 op 0 root 0 comm 0x400e156c49a0 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=1712285) count 4194304 datatype 9 op 0 root 0 comm 0x400e416c4290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO Broadcast: opCount +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO Broadcast: opCo +(FSDPPolicyWorkerBase pid=1712284) p 0 root 0 comm 0x400e62982ae0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712285) 110 sendbuff 0x4010a0000000 recvbuff 0x4010a0000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e415a97d0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:17 +(FSDPPolicyWorkerBase pid=1712287) unt 110 sendbuff 0x4010c0000000 recvbuff 0x4010c0000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e615a91f0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17 +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount ba sendbuff 0x4013c0000000 recvbuff 0x4013c0000000 count 16777216 datatype 9 op 0 root 0 comm 0x400e626b23c0 [nranks +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:17 +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO Broadcast: opCount 12d sendbuff 0x4010ae400000 recvbuff 0x4010ae400000 count 16777216 dat +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO Broadcast: opCount 12d sendbuff 0x4010ce400000 recvbuff 0x4010ce400000 count 16777216 +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO Broadcast: opCount 115 sendbuff 0x40108b800000 recvbuff 0x40108b800000 count 4194304 datatype +(FSDPPolicyWorkerBase pid=1712285) atype 9 op 0 root 0 comm 0x400e415a97d0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO Broadcast: opCount ca sendbuff 0x4010b8000000 recvbu +(FSDPPolicyWorkerBase pid=1712287) datatype 9 op 0 root 0 comm 0x400e615a91f0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO Broadcast: opCount ca sendbuff 0x4010d8000000 rec +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount bf sendbuff 0x4013d7800000 recvbuff 0x4013d7800000 count 4194304 datatype 9 +(FSDPPolicyWorkerBase pid=1712286) 9 op 0 root 0 comm 0x400e155aa040 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712285) ff 0x4010b8000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e412dd520 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [ +(FSDPPolicyWorkerBase pid=1712287) vbuff 0x4010d8000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e612dd240 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:171254 +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO Broadcast: opCount 132 sendbuff 0x401092000000 recvbuff 0x401092000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e155aa040 [nranks=2] st +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO Broadcast: opCount dd sendbuff 0x4010c8000000 recvbuff 0x4010c8000000 count 16777216 datatype 9 op 0 root 0 comm 0x400e412d +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO Recv: opCount 0 sendbuff (nil) recvbuff 0x4010a0000000 count 12582912 d +(FSDPPolicyWorkerBase pid=1712286) ream (nil) +(FSDPPolicyWorkerBase pid=1712285) atatype 9 op 0 root 0 comm 0x400e416c4290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO Broadcast: opCount +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO Recv: opCount 0 sendbuff (nil) recvbuff 0x4010c0000000 count 1258291 +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO +(FSDPPolicyWorkerBase pid=1712285) 176 sendbuff 0x400e99e2ce00 recvbuff 0x400e99e2ce00 count 4096 datatype 9 op 0 root 0 comm 0x400e415a97d0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712285) jpbo- +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO Broadcast: opCo +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa35400 coun +(FSDPPolicyWorkerBase pid=1712287) unt 176 sendbuff 0x400eb9e2ce00 recvbuff 0x400eb9e2ce00 count 4096 datatype 9 op 0 root 0 comm 0x400e615a91f0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NC +(FSDPPolicyWorkerBase pid=1712286) Recv: opCount 0 sendbuff (nil) recvbuff 0x400e99e25400 count 32 datatype 9 op 0 root 0 comm 0x400e156c49a0 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO Broadcast: opCount 15e sendbuff 0x401092000000 recvbuff 0x401092000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e152dd8b0 [nra +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO Recv: opCount 0 sendbuff (nil) recvbuff 0x401093800000 co +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount 63 sendbuff 0x400ebfa39c00 recvbu +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) jpbo-102-30:3949441:3949665 [0] NCCL INFO Recv: opCount 0 sendbuff (nil) recvbuff 0x40114a400000 count 155582464 datatype 9 o +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) ] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) CL INFO Broadcast: opCount cb sendbuff 0x401640000000 recvbuff 0x401640000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e626b23c0 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x40165b000000 count 12582912 datatype 9 op 0 ro +(FSDPPolicyWorkerBase pid=1712286) unt 4194304 datatype 9 op 0 root 0 comm 0x400e156c49a0 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO Recv: opCount 0 sendbuff (nil) recvbuff 0x4010ce200000 count 12582912 datatype 9 op 0 root 0 comm 0x400e156c +(FSDPPolicyWorkerBase pid=1712284) ot 2 comm 0x400e62a9d6a0 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa5ec00 count 1024 datatype 9 op 0 r +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) (EngineCore_DP0 pid=4037843) INFO 06-14 04:07:05 [parallel_state.py:1234] world_size=1 rank=0 local_rank=0 distributed_init_method=tcp://10.128.56.68:41615 backend=nccl [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) (EngineCore_DP0 pid=4037843) INFO 06-14 04:07:05 [parallel_state.py:1445] rank 0 in world size 1 is assigned as DP rank 0, PP rank 0, PCP rank 0, TP rank 0, EP rank N/A [repeated 4x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:394 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x40164a800000 count 12582912 datatype 9 op +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa5b400 count 10 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO S +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) (EngineCore_DP0 pid=3942507) INFO 06-14 04:07:08 [gpu_worker.py:373] Available KV cache memory: 49.32 GiB [repeated 19x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) (EngineCore_DP0 pid=3942507) INFO 06-14 04:07:08 [kv_cache_utils.py:1307] GPU KV cache size: 359,120 tokens [repeated 19x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) (EngineCore_DP0 pid=3942507) INFO 06-14 04:07:08 [kv_cache_utils.py:1312] Maximum concurrency for 32,768 tokens per request: 10.96x [repeated 19x across cluster] +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) (EngineCore_DP0 pid=4037843) INFO 06-14 04:07:05 [gpu_model_runner.py:4125] Starting to load model /e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6... [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) (EngineCore_DP0 pid=3942483) INFO 06-14 04:07:08 [kernel_warmup.py:44] Skipping FlashInfer autotune because it is disabled. [repeated 19x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) (EngineCore_DP0 pid=3942507) INFO 06-14 04:07:08 [core.py:278] init engine (profile, create kv cache, warmup model) took 2.82 seconds [repeated 19x across cluster] +(AsyncVLLMInferenceEngine pid=4037604, ip=10.128.56.68) (EngineCore_DP0 pid=4037833) INFO 06-14 04:07:06 [cuda.py:367] Using FLASH_ATTN attention backend out of potential backends: ['FLASH_ATTN', 'FLASHINFER', 'TRITON_ATTN', 'FLEX_ATTENTION']. [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) (EngineCore_DP0 pid=3942507) WARNING 06-14 04:07:09 [serial_utils.py:57] Allowing insecure serialization using pickle due to VLLM_ALLOW_INSECURE_SERIALIZATION=1 [repeated 19x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) (EngineCore_DP0 pid=3942507) INFO 06-14 04:07:09 [vllm.py:690] Asynchronous scheduling is enabled. [repeated 19x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) (EngineCore_DP0 pid=3942507) WARNING 06-14 04:07:09 [vllm.py:735] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored. [repeated 19x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) (EngineCore_DP0 pid=3942507) INFO 06-14 04:07:09 [vllm.py:846] Cudagraph is disabled under eager mode [repeated 19x across cluster] +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) (EngineCore_DP0 pid=4037843) INFO 06-14 04:07:05 [worker_base.py:289] Injected into for extended collective_rpc calls ['_apply_fp8_weight_loader_patches', '_is_fp8_model', '_quantize_weights_for_fp8', '_restore_param_subclasses', '_undo_param_subclasses', 'begin_weight_update', 'destroy_weights_update_group', 'end_weight_update', 'init_weight_update_communicator', 'load_weights', 'read_named_weights', 'set_numa_affinity', 'test_rpc'] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) WARNING 06-14 04:07:09 [model.py:1350] Default vLLM sampling parameters have been overridden by the model's `generation_config.json`: `{'temperature': 0.6, 'top_k': 20, 'top_p': 0.95}`. If this is not intended, please relaunch vLLM instance with `--generation-config vllm`. [repeated 19x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) (EngineCore_DP0 pid=323631) INFO 06-14 04:07:11 [default_loader.py:293] Loading weights took 13.26 seconds [repeated 9x across cluster] +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO cudaDriverVersion 13020 [repeated 7x across cluster] +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO NCCL version 2.27.7+cuda13.0 [repeated 7x across cluster] +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949683 [0] NCCL INFO NET/Plugin: Could not find: libnccl-net.so.  [repeated 7x across cluster] +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949683 [0] NCCL INFO NET/IB : Using [0]mlx5_0:1/IB [1]mlx5_1:1/IB [2]mlx5_2:1/IB [3]mlx5_3:1/IB [RO]; OOB ib0:10.128.56.78<0> [repeated 7x across cluster] +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949683 [0] NCCL INFO Initialized NET plugin IB [repeated 7x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712640 [0] NCCL INFO Assigned NET plugin IB to comm [repeated 23x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712640 [0] NCCL INFO Using network IB [repeated 23x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712640 [0] NCCL INFO DMA-BUF is available on GPU device 0 [repeated 23x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712640 [0] NCCL INFO ncclCommInitRankConfig comm 0x400e416c4290 rank 2 nranks 4 cudaDev 0 nvmlDev 2 busId 2901000 commId 0x3e1cfc6da1ad3a2a - Init START [repeated 23x across cluster] +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949683 [0] NCCL INFO RAS client listening socket at 127.0.0.1<28028> [repeated 7x across cluster] +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949683 [0] NCCL INFO NCCL_NET_GDR_LEVEL set by environment to LOC [repeated 7x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712640 [0] NCCL INFO Setting affinity for GPU 2 to 144-215 [repeated 23x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712640 [0] NCCL INFO NVLS multicast support is not available on dev 0 (NVLS_NCHANNELS 0) [repeated 15x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712640 [0] NCCL INFO comm 0x400e416c4290 rank 2 nRanks 4 nNodes 1 localRanks 4 localRank 2 MNNVL 0 [repeated 23x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712640 [0] NCCL INFO Trees [0] 3/-1/-1->2->1 [1] 3/-1/-1->2->1 [2] 3/-1/-1->2->1 [3] 3/-1/-1->2->1 [4] 1/-1/-1->2->0 [5] 1/-1/-1->2->0 [6] 1/-1/-1->2->0 [7] 1/-1/-1->2->0 [8] -1/-1/-1->2->3 [9] -1/-1/-1->2->3 [10] -1/-1/-1->2->3 [11] -1/-1/-1->2->3 [12] 3/-1/-1->2->1 [13] 3/-1/-1->2->1 [14] 3/-1/-1->2->1 [15] 3/-1/-1->2->1 [16] 1/-1/-1->2->0 [17] 1/-1/-1->2->0 [18] 1/-1/-1->2->0 [19] 1/-1/-1->2->0 [20] -1/-1/-1->2->3 [21] -1/-1/-1->2->3 [22] -1/-1/-1->2->3 [23] -1/-1/-1->2->3 [repeated 23x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712640 [0] NCCL INFO P2P Chunksize set to 524288 [repeated 23x across cluster] +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949683 [0] NCCL INFO PROFILER/Plugin: Could not find: libnccl-profiler.so.  [repeated 7x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712647 [0] NCCL INFO [Proxy Service] Device 0 CPU core 164 [repeated 23x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712650 [0] NCCL INFO [Proxy Service UDS] Device 0 CPU core 165 [repeated 23x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712647 [0] NCCL INFO Allocated shareable buffer 0x401028200000 size 10485760 ipcDesc 0x400fd000ed30 [repeated 1169x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712640 [0] NCCL INFO Channel 19/0 : 2[2] -> 1[1] via P2P/IPC [repeated 584x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712653 [0] NCCL INFO [Proxy Progress] Device 0 CPU core 170 [repeated 23x across cluster] +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949727 [0] NCCL INFO Channel 38/0 : 1[3] -> 0[3] [receive] via NET/IB/3 [repeated 340x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712622 [0] NCCL INFO Channel 39/0 : 1[2] -> 0[2] [send] via NET/IB/2 [repeated 344x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712656 [0] NCCL INFO Imported shareable buffer device 0 size 2097152 ptr 0x40102aa00000 [repeated 1185x across cluster] +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949746 [0] NCCL INFO Connected all rings, use ring PXN 0 GDR 1 [repeated 23x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) (EngineCore_DP0 pid=323631) INFO 06-14 04:07:11 [gpu_model_runner.py:4222] Model loading took 15.27 GiB memory and 14.362618 seconds [repeated 12x across cluster] +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949727 [0] NCCL INFO Channel 39/0 : 1[3] -> 0 [repeated 2x across cluster] +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) jpbo-102-30:3949441:3949745 [0] NCCL INFO Channel 16/0 : 1[1] [repeated 169x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949743 [0] NCCL INFO Check P2P Type isAllDirectP2p 1 directMode 0 [repeated 5x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712640 [0] NCCL INFO Connected all trees [repeated 23x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712640 [0] NCCL INFO threadThresholds 8/8/64 | 32/8/64 | 512 | 512 [repeated 23x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712640 [0] NCCL INFO 24 coll channels, 24 collnet channels, 0 nvls channels, 32 p2p channels, 16 p2p channels per peer [repeated 23x across cluster] +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712639 [0] NCCL INFO CC Off, workFifoBytes 1048576 [repeated 5x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712584 [0] NCCL INFO TUNER/Plugin: Could not find: libnccl-tuner.so. Using internal tuner plugin. [repeated 7x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712640 [0] NCCL INFO ncclCommInitRankConfig comm 0x400e416c4290 rank 2 nranks 4 cudaDev 0 nvmlDev 2 busId 2901000 commId 0x3e1cfc6da1ad3a2a - Init COMPLETE [repeated 23x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712640 [0] NCCL INFO Init timings - ncclCommInitRankConfig: rank 2 nranks 4 total 0.17 (kernels 0.00, alloc 0.00, bootstrap 0.00, allgathers 0.00, topo 0.03, graphs 0.01, connections 0.14, rest 0.00) [repeated 23x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount 18a sendbuff 0x401660000000 recvbuff 0x401660000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e16974fa0 [nranks=2] stream (nil) [repeated 5484x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712622 [0] NCCL INFO Connected binomial trees [repeated 7x across cluster] +(FSDPPolicyWorkerBase pid=1712287) jp [repeated 2x across cluster] +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) [3] [receive] via NET/IB/3 +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712647 [0] NCCL INFO Allocated shareable buffer 0x339a00000 size 2097152 +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO Recv: opCount 0 sendbuff (nil) recvbuff 0x4010cca00000 count 12582912 datatype 9 op 0 root 0 comm 0x400e156c49a0 [nranks=4] stream (nil) [repeated 2345x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401661800000 count 12582912 datatype 9 op 0 root 1 comm 0x400e16a90290 [nranks=4] stream (nil) [repeated 2305x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO Broadcast: opCount a sendbuff 0x40106fe00000 recvbuff 0x40106fe00000 count 4194304 datatype 9 op 0 root 0 comm 0x400e412dd520 [nranks=8] stream (nil) [repeated 14x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO Broadcast: opCount b sendbuff 0x400ea3800000 recvbuff 0x400ea3800000 count 16777216 datatype 9 op 0 root 0 comm 0x400e412dd520 [nranks=8] stream (nil) [repeated 14x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO Broadcast: opCount c sendbuff 0x400ea8000000 recvbuff 0x400ea8000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e412dd520 [nranks=8] stream (nil) [repeated 24x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount d sendbuff 0x401127800000 recvbuff 0x401127800000 count 50331648 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 15x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount e sendbuff 0x401127800000 recvbuff 0x401127800000 count 50331648 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 15x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount f sendbuff 0x401127800000 recvbuff 0x401127800000 count 16777216 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 27x across cluster] +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO Broadcast: opCount 185 sendbuff 0x4010eca00000 recvbuff 0x4010eca00000 count 16777216 datatype 9 op 0 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount aa sendbuff 0x4013c0000000 recvbuff 0x4013c0000000 count 4194304 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 15x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount ab sendbuff 0x4013c0000000 recvbuff 0x4013c0000000 count 4194304 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 15x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount ac sendbuff 0x4013c0000000 recvbuff 0x4013c0000000 count 16777216 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 15x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount ad sendbuff 0x4013c6000000 recvbuff 0x4013c6000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 27x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount ae sendbuff 0x4013c6000000 recvbuff 0x4013c6000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 15x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount af sendbuff 0x4013c6000000 recvbuff 0x4013c6000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 14x across cluster] +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount 110 sendbuff 0x4013d2000000 recvbuff 0x40 [repeated 2x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) 0 root 3 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) : opCount 0 sendbuff (nil) recvbuff 0x4015eca00000 count 4194304 datatype 9 op 0 root 2 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=1712285) ipcDesc 0x400fd000ed30 +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) jpbo-102-30:3949440:3949657 [0] NCCL INFO Broadcast: opCount f6 sendbuff 0x400eb9e2ae00 recvbuff 0x400eb9e2ae00 count 4096 datatype 9 op 0 root 0 comm 0x400e2d2db290 [nranks=8 [repeated 5x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount ba sendbuff 0x4013cc000000 recvbuff 0x4013cc000000 count 16777216 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 14x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount bb sendbuff 0x4013cc000000 recvbuff 0x4013cc000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 27x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount bc sendbuff 0x4013cc000000 recvbuff 0x4013cc000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 15x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount bd sendbuff 0x4013cc000000 recvbuff 0x4013cc000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 15x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount be sendbuff 0x4013cc000000 recvbuff 0x4013cc000000 count 16777216 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 26x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount bf sendbuff 0x4013cc000000 recvbuff 0x4013cc000000 count 4194304 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 14x across cluster] +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) stream (nil) [repeated 9x across cluster] +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) jpbo-102-30:3949440:3949657 [0] NCCL INFO Recv: opCount 0 sendbuff (nil) recvbuff 0x40116a400000 count 155582464 datatype 9 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount ca sendbuff 0x4013d5000000 recvbuff 0x4013d5000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 13x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount cb sendbuff 0x4013d5000000 recvbuff 0x4013d5000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 14x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount cc sendbuff 0x4013d5000000 recvbuff 0x4013d5000000 count 16777216 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 27x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount cd sendbuff 0x4013d5000000 recvbuff 0x4013d5000000 count 4194304 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 15x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount ce sendbuff 0x4013d5000000 recvbuff 0x4013d5000000 count 4194304 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 15x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount cf sendbuff 0x4013d5c00000 recvbuff 0x4013d5c00000 count 16777216 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 15x across cluster] +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL  [repeated 2x across cluster] +(FSDPPolicyWorkerBase pid=1712284) op 0 root 0 comm 0x400e626b23c0 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount 5c sendbuff 0x401390400000 [repeated 4x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount da sendbuff 0x401640000000 recvbuff 0x401640000000 count 16777216 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 27x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount db sendbuff 0x4013e6800000 recvbuff 0x4013e6800000 count 4194304 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 14x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount dc sendbuff 0x4013e6800000 recvbuff 0x4013e6800000 count 4194304 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 15x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount dd sendbuff 0x401640400000 recvbuff 0x401640400000 count 16777216 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 13x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount de sendbuff 0x401646000000 recvbuff 0x401646000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 27x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount df sendbuff 0x401646000000 recvbuff 0x401646000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 15x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) recvbuff 0x401390400000 count 16777216 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 5x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) 24 datatype 9 op 0 root 2 comm 0x400e16a90290 [nranks=4] stream (nil) [repeated 4x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount ea sendbuff 0x401646000000 recvbuff 0x401646000000 count 4194304 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 15x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount eb sendbuff 0x401648800000 recvbuff 0x401648800000 count 16777216 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 15x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount ec sendbuff 0x401650800000 recvbuff 0x401650800000 count 50331648 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 27x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount ed sendbuff 0x401650800000 recvbuff 0x401650800000 count 50331648 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 15x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount ee sendbuff 0x401650800000 recvbuff 0x401650800000 count 50331648 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 15x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount ef sendbuff 0x401650800000 recvbuff 0x401650800000 count 16777216 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 27x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount fa sendbuff 0x401660000000 recvbuff 0x401660000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 21x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount fb sendbuff 0x401660000000 recvbuff 0x401660000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 13x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount fc sendbuff 0x401660000000 recvbuff 0x401660000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 13x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount fd sendbuff 0x400ebfa4b400 recvbuff 0x400ebfa4b400 count 4096 datatype 9 op 0 root 0 comm 0x400e16974fa0 [nranks=2] stream (nil) [repeated 20x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount fe sendbuff 0x4015f1a00000 recvbuff 0x4015f1a00000 count 16777216 datatype 9 op 0 root 0 comm 0x400e16974fa0 [nranks=2] stream (nil) [repeated 9x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount ff sendbuff 0x4015f1a00000 recvbuff 0x4015f1a00000 count 4194304 datatype 9 op 0 root 0 comm 0x400e16974fa0 [nranks=2] stream (nil) [repeated 9x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) t 1024 datatype 9 op 0 root 1 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) 0x4013c1800000 count 12582912 datatype 9 op 0 root 1 comm 0x400e16a90290 [nranks=4] stream (nil) [repeated 5x across cluster] +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO Broadcast: opCount 141 sendbuff 0x4010ab800000 recvbuff 0x4010ab800000 count 419430 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) ff 0x400ebfa39c00 count 4096 datatype 9 op 0 root 0 comm 0x400e16974fa0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO Broadcast: opCount dd sendbuff 0x4010e8000000 recvbuff 0x4010e8000000 count 16777216 datatype 9 op 0 root 0 comm 0x400e6 +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) (EngineCore_DP0 pid=323627) INFO 06-14 04:07:13 [gpu_worker.py:373] Available KV cache memory: 49.32 GiB [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) (EngineCore_DP0 pid=323627) INFO 06-14 04:07:13 [kv_cache_utils.py:1307] GPU KV cache size: 359,120 tokens [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) (EngineCore_DP0 pid=323627) INFO 06-14 04:07:13 [kv_cache_utils.py:1312] Maximum concurrency for 32,768 tokens per request: 10.96x [repeated 9x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] Started monitoring (every 120s) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:07:13] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:07:13] OK: RSS 0.78 GiB | node mem 388.5/858.0 GiB used (45.3%), avail 469.4 GiB +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) (EngineCore_DP0 pid=1508209) INFO 06-14 04:07:12 [kernel_warmup.py:44] Skipping FlashInfer autotune because it is disabled. [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) (EngineCore_DP0 pid=1508221) INFO 06-14 04:07:12 [core.py:278] init engine (profile, create kv cache, warmup model) took 2.77 seconds [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) (EngineCore_DP0 pid=1508201) WARNING 06-14 04:07:13 [serial_utils.py:57] Allowing insecure serialization using pickle due to VLLM_ALLOW_INSECURE_SERIALIZATION=1 [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) (EngineCore_DP0 pid=1508201) INFO 06-14 04:07:13 [vllm.py:690] Asynchronous scheduling is enabled. [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) (EngineCore_DP0 pid=1508201) WARNING 06-14 04:07:13 [vllm.py:735] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored. [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) (EngineCore_DP0 pid=1508201) INFO 06-14 04:07:13 [vllm.py:846] Cudagraph is disabled under eager mode [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) WARNING 06-14 04:07:13 [model.py:1350] Default vLLM sampling parameters have been overridden by the model's `generation_config.json`: `{'temperature': 0.6, 'top_k': 20, 'top_p': 0.95}`. If this is not intended, please relaunch vLLM instance with `--generation-config vllm`. [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) (EngineCore_DP0 pid=3946082) INFO 06-14 04:07:14 [default_loader.py:293] Loading weights took 13.62 seconds [repeated 11x across cluster] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) (EngineCore_DP0 pid=1508031) INFO 06-14 04:07:14 [gpu_model_runner.py:4222] Model loading took 15.27 GiB memory and 15.132246 seconds [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) (EngineCore_DP0 pid=3945782) INFO 06-14 04:07:20 [gpu_worker.py:373] Available KV cache memory: 49.32 GiB [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) (EngineCore_DP0 pid=3945782) INFO 06-14 04:07:20 [kv_cache_utils.py:1307] GPU KV cache size: 359,120 tokens [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) (EngineCore_DP0 pid=3945782) INFO 06-14 04:07:20 [kv_cache_utils.py:1312] Maximum concurrency for 32,768 tokens per request: 10.96x [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) (EngineCore_DP0 pid=1508031) INFO 06-14 04:07:17 [kernel_warmup.py:44] Skipping FlashInfer autotune because it is disabled. [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) (EngineCore_DP0 pid=3946082) INFO 06-14 04:07:17 [core.py:278] init engine (profile, create kv cache, warmup model) took 2.85 seconds [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) (EngineCore_DP0 pid=3946082) WARNING 06-14 04:07:17 [serial_utils.py:57] Allowing insecure serialization using pickle due to VLLM_ALLOW_INSECURE_SERIALIZATION=1 [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) (EngineCore_DP0 pid=3946082) INFO 06-14 04:07:17 [vllm.py:690] Asynchronous scheduling is enabled. [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) (EngineCore_DP0 pid=3946082) WARNING 06-14 04:07:17 [vllm.py:735] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored. [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) (EngineCore_DP0 pid=3946082) INFO 06-14 04:07:17 [vllm.py:846] Cudagraph is disabled under eager mode [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) WARNING 06-14 04:07:18 [model.py:1350] Default vLLM sampling parameters have been overridden by the model's `generation_config.json`: `{'temperature': 0.6, 'top_k': 20, 'top_p': 0.95}`. If this is not intended, please relaunch vLLM instance with `--generation-config vllm`. [repeated 12x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] Started monitoring (every 120s) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:07:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:07:21] OK: RSS 0.78 GiB | node mem 376.9/858.0 GiB used (43.9%), avail 481.1 GiB +(AsyncVLLMInferenceEngine pid=4037604, ip=10.128.56.68) (EngineCore_DP0 pid=4037833) INFO 06-14 04:07:20 [default_loader.py:293] Loading weights took 13.93 seconds [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=4037604, ip=10.128.56.68) (EngineCore_DP0 pid=4037833) INFO 06-14 04:07:21 [gpu_model_runner.py:4222] Model loading took 15.27 GiB memory and 15.162962 seconds [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) (EngineCore_DP0 pid=4037843) INFO 06-14 04:07:23 [gpu_worker.py:373] Available KV cache memory: 49.32 GiB [repeated 7x across cluster] +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) (EngineCore_DP0 pid=4037843) INFO 06-14 04:07:23 [kv_cache_utils.py:1307] GPU KV cache size: 359,120 tokens [repeated 7x across cluster] +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) (EngineCore_DP0 pid=4037843) INFO 06-14 04:07:23 [kv_cache_utils.py:1312] Maximum concurrency for 32,768 tokens per request: 10.96x [repeated 7x across cluster] +(AsyncVLLMInferenceEngine pid=4037604, ip=10.128.56.68) (EngineCore_DP0 pid=4037833) INFO 06-14 04:07:24 [kernel_warmup.py:44] Skipping FlashInfer autotune because it is disabled. [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=4037604, ip=10.128.56.68) (EngineCore_DP0 pid=4037833) INFO 06-14 04:07:24 [core.py:278] init engine (profile, create kv cache, warmup model) took 2.80 seconds [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=4037604, ip=10.128.56.68) (EngineCore_DP0 pid=4037833) WARNING 06-14 04:07:24 [serial_utils.py:57] Allowing insecure serialization using pickle due to VLLM_ALLOW_INSECURE_SERIALIZATION=1 [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=4037604, ip=10.128.56.68) (EngineCore_DP0 pid=4037833) INFO 06-14 04:07:24 [vllm.py:690] Asynchronous scheduling is enabled. [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=4037604, ip=10.128.56.68) (EngineCore_DP0 pid=4037833) WARNING 06-14 04:07:24 [vllm.py:735] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored. [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=4037604, ip=10.128.56.68) (EngineCore_DP0 pid=4037833) INFO 06-14 04:07:24 [vllm.py:846] Cudagraph is disabled under eager mode [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) WARNING 06-14 04:07:24 [model.py:1350] Default vLLM sampling parameters have been overridden by the model's `generation_config.json`: `{'temperature': 0.6, 'top_k': 20, 'top_p': 0.95}`. If this is not intended, please relaunch vLLM instance with `--generation-config vllm`. [repeated 8x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] Started monitoring (every 120s) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:07:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:07:29] OK: RSS 0.78 GiB | node mem 383.8/858.0 GiB used (44.7%), avail 474.1 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] Started monitoring (every 120s) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:07:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:07:38] OK: RSS 0.78 GiB | node mem 372.7/858.0 GiB used (43.4%), avail 485.2 GiB +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) [rank-0]: Loading model from /e/data1/datasets/playground/ot-baf/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/checkpoints/global_step_78/policy/model_world_size_8_rank_0.pt +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) [rank-0]: Loading extra_state from /e/data1/datasets/playground/ot-baf/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/checkpoints/global_step_78/policy/extra_state_world_size_8_rank_0.pt +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) [rank-0]: Loading optim from /e/data1/datasets/playground/ot-baf/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/checkpoints/global_step_78/policy/optim_world_size_8_rank_0.pt +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) [rank-0]: Successfully loaded model state dict +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) [rank-0]: Successfully loaded optimizer state +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) [rank-0]: Successfully loaded scheduler state +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) [rank-0]: Checkpoint loaded successfully from /e/data1/datasets/playground/ot-baf/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/checkpoints/global_step_78/policy +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:07:58] OK: 104 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:07:58] OK: RSS 1.70 GiB | node mem 256.0/858.0 GiB used (29.8%), avail 601.9 GiB +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) end: opCount 0 sendbuff (nil) recvbuff 0x401663000000 count 12582912 datatype 9 op 0 root 2 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x401664800000 count 12582912 datatype 9 op 0 root 3 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount fd sendbuff 0x400ebfa5a400 recvbuff 0x400ebfa5a400 count 4096 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount 18b sendbuff 0x400ebfa5a400 recvbuff 0x400ebfa5a400 count 4096 datatype 9 op 0 root 0 comm 0x400e16974fa0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa5ac00 count 1024 datatype 9 op 0 root 1 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa5b400 count 1024 datatype 9 op 0 root 2 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa5bc00 count 1024 datatype 9 op 0 root 3 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount fd sendbuff 0x400ebfa5a400 recvbuff 0x400ebfa5a400 count 4096 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount 18c sendbuff 0x400ebfa5a400 recvbuff 0x400ebfa5a400 count 4096 datatype 9 op 0 root 0 comm 0x400e16974fa0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa5ac00 count 1024 datatype 9 op 0 root 1 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa5b400 count 1024 datatype 9 op 0 root 2 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa5bc00 count 1024 datatype 9 op 0 root 3 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount fd sendbuff 0x400ebfa5a400 recvbuff 0x400ebfa5a400 count 4096 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount 18d sendbuff 0x400ebfa5a400 recvbuff 0x400ebfa5a400 count 4096 datatype 9 op 0 root 0 comm 0x400e16974fa0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa5ac00 count 1024 datatype 9 op 0 root 1 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa5b400 count 1024 datatype 9 op 0 root 2 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x400ebfa5bc00 count 1024 datatype 9 op 0 root 3 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount fd sendbuff 0x401680000000 recvbuff 0x401680000000 count 622329856 datatype 9 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Broadcast: opCount 18e sendbuff 0x401680000000 recvbuff 0x401680000000 count 622329856 datatype 9 op 0 root 0 comm 0x400e16974fa0 [nranks=2] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x4016928c0000 count 155582464 datatype 9 op 0 root 1 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x4016a5180000 count 155582464 datatype 9 op 0 root 2 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x4016b7a40000 count 155582464 datatype 9 op 0 root 3 comm 0x400e16a90290 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO AllReduce: opCount fe sendbuff 0x400ebfa88e00 recvbuff 0x400ebfa88e00 count 1 datatype 7 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507560 [0] NCCL INFO cudaDriverVersion 13020 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507560 [0] NCCL INFO NCCL version 2.27.7+cuda13.0 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO NET/Plugin: Could not find: libnccl-net.so. +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO NET/IB : Using [0]mlx5_0:1/IB [1]mlx5_1:1/IB [2]mlx5_2:1/IB [3]mlx5_3:1/IB [RO]; OOB ib0:10.128.34.185<0> +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Initialized NET plugin IB +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Assigned NET plugin IB to comm +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Using network IB +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO DMA-BUF is available on GPU device 0 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO ncclCommInitRankConfig comm 0xaaaafa114e20 rank 2 nranks 49 cudaDev 0 nvmlDev 0 busId 901000 commId 0xe5e1db1392935c5f - Init START +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO RAS client listening socket at 127.0.0.1<28028> +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO NCCL_NET_GDR_LEVEL set by environment to LOC +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Setting affinity for GPU 0 to 0-71 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO NVLS multicast support is not available on dev 0 (NVLS_NCHANNELS 0) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO comm 0xaaaafa114e20 rank 2 nRanks 49 nNodes 13 localRanks 4 localRank 0 MNNVL 0 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Trees [0] 3/1/5->2->9 [1] -1/-1/-1->2->13 [2] 3/-1/-1->2->4 [3] 4/-1/-1->2->13 [4] 3/-1/-1->2->5 [5] -1/-1/-1->2->13 [6] 3/-1/-1->2->4 [7] 4/-1/-1->2->13 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO P2P Chunksize set to 131072 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO PROFILER/Plugin: Could not find: libnccl-profiler.so. +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507841 [0] NCCL INFO [Proxy Service] Device 0 CPU core 9 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507842 [0] NCCL INFO [Proxy Service UDS] Device 0 CPU core 10 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507843 [0] NCCL INFO [Proxy Progress] Device 0 CPU core 11 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Channel 00/0 : 1[0] -> 2[0] [receive] via NET/IB/0 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Channel 04/0 : 1[0] -> 2[0] [receive] via NET/IB/0 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Channel 00/0 : 2[0] -> 3[1] via P2P/IPC +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507841 [0] NCCL INFO Allocated shareable buffer 0x4017b0800000 size 2097152 ipcDesc 0x40097400a120 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Channel 04/0 : 2[0] -> 3[1] via P2P/IPC +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507841 [0] NCCL INFO Allocated shareable buffer 0x4017b0a00000 size 2097152 ipcDesc 0x40097400af80 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Channel 01/0 : 2[0] -> 5[0] [send] via NET/IB/0 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Channel 05/0 : 2[0] -> 5[0] [send] via NET/IB/0 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Channel 02/0 : 2[0] -> 13[3] via P2P/IPC +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507841 [0] NCCL INFO Allocated shareable buffer 0x4017b0c00000 size 2097152 ipcDesc 0x40097400ca30 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Channel 03/0 : 2[0] -> 13[3] via P2P/IPC +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507841 [0] NCCL INFO Allocated shareable buffer 0x4017b0e00000 size 2097152 ipcDesc 0x40097400d800 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Channel 06/0 : 2[0] -> 13[3] via P2P/IPC +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507841 [0] NCCL INFO Allocated shareable buffer 0x4017b1000000 size 2097152 ipcDesc 0x40097400e5d0 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Channel 07/0 : 2[0] -> 13[3] via P2P/IPC +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507841 [0] NCCL INFO Allocated shareable buffer 0x4017b1200000 size 2097152 ipcDesc 0x40097400f3a0 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507841 [0] NCCL INFO Allocated shareable buffer 0x4017b1400000 size 10485760 ipcDesc 0x400974010170 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507841 [0] NCCL INFO Allocated shareable buffer 0x4017b1e00000 size 10485760 ipcDesc 0x400974010f40 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507841 [0] NCCL INFO Allocated shareable buffer 0x4017b2800000 size 10485760 ipcDesc 0x400974010f40 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507841 [0] NCCL INFO Allocated shareable buffer 0x4017b3200000 size 10485760 ipcDesc 0x400974010f40 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507841 [0] NCCL INFO Allocated shareable buffer 0x4017b3c00000 size 10485760 ipcDesc 0x400974010f40 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507841 [0] NCCL INFO Allocated shareable buffer 0x4017b4600000 size 10485760 ipcDesc 0x400974010f40 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Imported shareable buffer device 0 size 10485760 ptr 0x4017b5000000 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Imported shareable buffer device 0 size 10485760 ptr 0x4017b5a00000 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Imported shareable buffer device 0 size 10485760 ptr 0x4017b6400000 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Imported shareable buffer device 0 size 10485760 ptr 0x4017b6e00000 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Imported shareable buffer device 0 size 10485760 ptr 0x4017b7800000 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Imported shareable buffer device 0 size 10485760 ptr 0x4017b8200000 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Imported shareable buffer device 0 size 2097152 ptr 0x4017b8c00000 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Imported shareable buffer device 0 size 2097152 ptr 0x4017b8e00000 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Imported shareable buffer device 0 size 2097152 ptr 0x4017b9000000 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Imported shareable buffer device 0 size 2097152 ptr 0x4017b9200000 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Imported shareable buffer device 0 size 2097152 ptr 0x4017b9400000 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Imported shareable buffer device 0 size 2097152 ptr 0x4017b9600000 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Connected all rings, use ring PXN 0 GDR 0 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Channel 02/0 : 2[0] -> 3[1] via P2P/IPC +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507841 [0] NCCL INFO Allocated shareable buffer 0x4017b9800000 size 2097152 ipcDesc 0x4009742dfe10 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Channel 06/0 : 2[0] -> 3[1] via P2P/IPC +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507841 [0] NCCL INFO Allocated shareable buffer 0x4017b9a00000 size 2097152 ipcDesc 0x4009742dfe10 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Channel 02/0 : 2[0] -> 4[2] via P2P/IPC +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507841 [0] NCCL INFO Allocated shareable buffer 0x4017b9c00000 size 2097152 ipcDesc 0x4009742dfe10 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Channel 03/0 : 2[0] -> 4[2] via P2P/IPC +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507841 [0] NCCL INFO Allocated shareable buffer 0x4017b9e00000 size 2097152 ipcDesc 0x4009742dfe10 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Channel 06/0 : 2[0] -> 4[2] via P2P/IPC +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507841 [0] NCCL INFO Allocated shareable buffer 0x4017ba000000 size 2097152 ipcDesc 0x4009742dfe10 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Channel 07/0 : 2[0] -> 4[2] via P2P/IPC +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507841 [0] NCCL INFO Allocated shareable buffer 0x4017ba200000 size 2097152 ipcDesc 0x4009742dfe10 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Channel 00/0 : 2[0] -> 5[0] [send] via NET/IB/0 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Channel 04/0 : 2[0] -> 5[0] [send] via NET/IB/0 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Channel 00/0 : 2[0] -> 9[0] [send] via NET/IB/0 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Channel 01/0 : 2[0] -> 13[3] via P2P/IPC +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507841 [0] NCCL INFO Allocated shareable buffer 0x4017ba400000 size 2097152 ipcDesc 0x40097433b9b0 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Channel 05/0 : 2[0] -> 13[3] via P2P/IPC +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507841 [0] NCCL INFO Allocated shareable buffer 0x4017ba600000 size 2097152 ipcDesc 0x40097433b9b0 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507841 [0] NCCL INFO Allocated shareable buffer 0x4017ba800000 size 10485760 ipcDesc 0x40097433b9b0 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507841 [0] NCCL INFO Allocated shareable buffer 0x4017bb200000 size 10485760 ipcDesc 0x40097433b9b0 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507841 [0] NCCL INFO Allocated shareable buffer 0x4017bbc00000 size 10485760 ipcDesc 0x40097433b9b0 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507841 [0] NCCL INFO Allocated shareable buffer 0x4017bc600000 size 10485760 ipcDesc 0x40097433b9b0 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Channel 00/0 : 9[0] -> 2[0] [receive] via NET/IB/0 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507809 [0] NCCL INFO Channel 00/0 : 5[0] -> 2[0] [receive] via NET/IB/0 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1 +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) jpbo-055-25:1507551:1 +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) jpbo-055-25 +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) jpbo-055-25:1507543:1507808 [0] NCCL INFO Ch +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) jpbo-102-18:3945770:3946090 [0 +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) jpbo-102-18:3945782:3946123 [0] NCCL INFO Allocated shareable buffer 0x401 +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) jpbo-102-18:3945778:3946120 [0] NCCL INFO Allocated shareable buffer 0x40177f000000 size +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) jpbo-102-18:3945796:3946091 [0] NCC +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) jpbo-102-20:403785 +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) jpbo-102-20:4037837:4038153 [0] NCCL +(AsyncVLLMInferenceEngine pid=4037604, ip=10.128.56.68) jpbo-102-20:40378 +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) jpbo-102- +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) jpbo-102-28:3942493:3942807 [0] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) jpbo-055-22:1497142:1497424 [0] NCCL INFO Allocated shareable buffer 0x40177b600000 si +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) jpbo-055-22:1497158:1497426 [0] NCCL INFO Allocated shareable buffer 0x40179f000000 s +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) jpbo-055-22:1497134:1497397 [0] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) jpbo-102-17:153955:15 +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) jpbo-102-17:153 +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) jpbo- +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) jpbo-055-21:1508031:1508292 [0] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) jpbo-055-19:1508201:1508594 [0] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) jpbo-055-19:1508221:1508592 [0] NC +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) jpbo-055-18:1507832:1508248 +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) jpbo-055-18:150 +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) jpb +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) jpbo-102-19:323631:323965 [ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) jpbo-102-1 +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) jpbo-102-19:323622:323933 [0] NCCL INFO Channel 07/0 : 40[3] -> 37[3] [receive] via NE +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) jpbo-102-25:3946090:3946471 [0 +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) jpbo-055-23:1496316:1496664 [0] NCCL INFO Allocate +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) jpbo-055-23:1496327:1496636 [0] NCCL INFO Connected all trees +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) jpbo-055-23:1496327:1496636 [0] NCCL INFO threadThresholds 8/8/64 | 392/8/64 | 512 | 512 +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) jpbo-055-23:1496327:1496636 [0] NCCL INFO 8 coll channels, 8 collnet channels, 0 nvls channels, 8 p2p channels, 1 p2p channels per peer +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) jpbo-055-23:1496327:1496636 [0] NCCL INFO TUNER/Plugin: Could not find: libnccl-tuner.so. Using internal tuner plugin. +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) jpbo-055-23:1496327:1496636 [0] NCCL INFO ncclCommInitRankConfig comm 0xaaab05dc59f0 rank 11 nranks 49 cudaDev 0 nvmlDev 2 busId 2901000 commId 0xe5e1db1392935c5f - Init COMPLETE +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) jpbo-055-23:1496327:1496636 [0] NCCL INFO Init timings - ncclCommInitRankConfig: rank 11 nranks 49 total 3.24 (kernels 0.19, alloc 2.13, bootstrap 0.23, allgathers 0.01, topo 0.03, graphs 0.01, connections 0.64, rest 0.00) +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) d shareable buffer 0x40177bc00000 size 10485760 ipcDesc 0x40094c33fc00 +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) annel 03/0 : 16[3] -> 13[3] [receive] via NET/IB/3 +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ] NCCL INFO Channel 04/0 : 41[0] -> 33[0] [send] via NET/IB/0 +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) 79cc00000 size 10485760 ipcDesc 0x40095833fc10 +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) 10485760 ipcDesc 0x40095033fd70 +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) L INFO Channel 06/0 : 44[3] -> 42[1] via P2P/IPC +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) INFO Channel 00/0 : 47[2] -> 46[1] via P2P/IPC +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ze 10485760 ipcDesc 0x400940016170 +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ize 10485760 ipcDesc 0x40095c33f280 +(AsyncVLLMInferenceEngine pid=153669, ip=10.128.56.65) 0x40097c1d4530 +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) CL INFO Channel 06/0 : 20[3] -> 18[1] via P2P/IPC +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) 40 +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) T/IB/3 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO AllReduce: opCount ff sendbuff 0x400ebfa88c00 recvbuff 0x400ebfa88c00 count 1 datatype 7 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x401840000000 recvbuff 0x401680000000 count 155582464 datatype 9 op 0 root 0 comm 0x400e16a90290 [nranks=4] stream 0x400e167b8cb0 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949846 [0] NCCL INFO Channel 00/08 : 0 16 15 14 1 2 3 4 13 8 7 6 5 9 10 11 12 20 19 18 17 21 22 23 24 40 39 38 25 26 27 28 37 32 31 30 ... +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949846 [0] NCCL INFO Channel 01/08 : 0 1 14 15 16 13 4 3 2 5 6 7 8 12 11 10 9 17 18 19 20 24 23 22 21 25 38 39 40 37 28 27 26 29 30 31 ... +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949846 [0] NCCL INFO Channel 02/08 : 0 14 1 16 15 4 2 13 3 6 5 8 7 11 9 12 10 18 17 20 19 23 21 24 22 38 25 40 39 28 26 37 27 30 29 32 ... +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949846 [0] NCCL INFO Channel 03/08 : 0 15 1 16 14 3 2 13 4 7 5 8 6 10 9 12 11 19 17 20 18 22 21 24 23 39 25 40 38 27 26 37 28 31 29 32 ... +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949846 [0] NCCL INFO Channel 04/08 : 0 16 15 14 1 2 3 4 13 8 7 6 5 9 10 11 12 20 19 18 17 21 22 23 24 40 39 38 25 26 27 28 37 32 31 30 ... +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949846 [0] NCCL INFO Channel 05/08 : 0 1 14 15 16 13 4 3 2 5 6 7 8 12 11 10 9 17 18 19 20 24 23 22 21 25 38 39 40 37 28 27 26 29 30 31 ... +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949846 [0] NCCL INFO Channel 06/08 : 0 14 1 16 15 4 2 13 3 6 5 8 7 11 9 12 10 18 17 20 19 23 21 24 22 38 25 40 39 28 26 37 27 30 29 32 ... +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949846 [0] NCCL INFO Channel 07/08 : 0 15 1 16 14 3 2 13 4 7 5 8 6 10 9 12 11 19 17 20 18 22 21 24 23 39 25 40 38 27 26 37 28 31 29 32 ... +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949846 [0] NCCL INFO Check P2P Type isAllDirectP2p 0 directMode 0 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949846 [0] NCCL INFO CC Off, workFifoBytes 1048576 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount 0 sendbuff 0x401680000000 recvbuff 0x401680000000 count 622329856 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO AllReduce: opCount 100 sendbuff 0x400ebfa88e00 recvbuff 0x400ebfa88e00 count 1 datatype 7 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x401655c00000 recvbuff 0x401933c00000 count 4194304 datatype 9 op 0 root 0 comm 0x400e16a90290 [nranks=4] stream 0x400e167b8cb0 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount 1 sendbuff 0x401933c00000 recvbuff 0x401933c00000 count 16777216 data +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) root 0 comm 0x400e112d7f80 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO Recv: opCount 0 sendbuff (nil) recvbuff 0x4010ec200000 count 4194304 datatype 9 op 0 root 0 comm 0x400e116be640 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO Recv: opCount 0 sendbuff (nil) recvbuff 0x400e99e2b800 count 32 datatype 9 op 0 root 0 comm 0x400e116be640 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO Recv: opCount 0 sendbuff (nil) recvbuff 0x400e99e2b600 count 32 datatype 9 op 0 root 0 comm 0x400e116be640 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO Recv: opCount 0 sendbuff (nil) recvbuff 0x4010eca00000 count 12582912 datatype 9 op 0 root 0 comm 0x400e116be640 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO Recv: opCount 0 sendbuff (nil) recvbuff 0x4010ee200000 count 12582912 datatype 9 op 0 root 0 comm 0x400e116be640 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO Recv: opCount 0 sendbuff (nil) recvbuff 0x4010efa00000 count 12582912 datatype 9 op 0 root 0 comm 0x400e116be640 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO Recv: opCount 0 sendbuff (nil) recvbuff 0x400e99e2ba00 count 1024 datatype 9 op 0 root 0 comm 0x400e116be640 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO Recv: opCount 0 sendbuff (nil) recvbuff 0x400e99e2c200 count 1024 datatype 9 op 0 root 0 comm 0x400e116be640 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO Recv: opCount 0 sendbuff (nil) recvbuff 0x400e99e2f600 count 1024 datatype 9 op 0 root 0 comm 0x400e116be640 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO Recv: opCount 0 sendbuff (nil) recvbuff 0x40114a400000 count 155582464 datatype 9 op 0 root 0 comm 0x400e116be640 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO Broadcast: opCount fa sendbuff 0x400eb9e2b600 recvbuff 0x400eb9e2b600 count 128 datatype 9 op 0 root 0 comm 0x400e612dd240 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO Broadcast: opCount fa sendbuff 0x400eb9e2ba00 recvbuff 0x400eb9e2ba00 count 128 datatype 9 op 0 root 0 comm 0x400e612dd240 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO Broadcast: opCount fa sendbuff 0x401100000000 recvbuff 0x401100000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e612dd240 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO Broadcast: opCount fb sendbuff 0x401106000000 recvbuff 0x401106000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e612dd240 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO Broadcast: opCount fc sendbuff 0x401100000000 recvbuff 0x401100000000 count 50331648 datatype 9 op 0 root 0 comm 0x400e612dd240 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO AllReduce: opCount fe send +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO AllReduce: opCount fe sendbuf +(FSDPPolicyWorkerBase pid=1712284) oot 1 comm 0x400e62a9d6a0 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO AllReduce: opCount 110 sendbuff 0x40 +(FSDPPolicyWorkerBase pid=1712286) 49a0 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO AllReduce: opCount 18f sendbuff 0x400e99e88c00 recvbuff 0x400e99e88c00 coun +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) type 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount a sendbuff 0x400ebfa88e00 recvbuff 0x400ebfa88e00 count 4096 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount b sendbuff 0x400ebfa8b000 recvbuff 0x400ebfa8b000 count 4096 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount c sendbuff 0x401933c00000 recvbuff 0x401933c00000 count 16777216 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount d sendbuff 0x4013a9580000 recvbuff 0x4013a9580000 count 4194304 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount e sendbuff 0x401933c00000 recvbuff 0x401933c00000 count 4194304 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount f sendbuff 0x401680000000 recvbuff 0x401680000000 count 16777216 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) j +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) p 0 root 0 comm 0x400e056c3fa0 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) jpbo-102-30:3949441:39 +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) op 0 root 0 comm 0x400e2d6c2c50 [nranks=4] stream (nil) +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) jpbo-102-30:3949440:3 +(FSDPPolicyWorkerBase pid=1712287) buff 0x400eb9e88c00 recvbuff 0x400eb9e88c00 count 1 datatype 7 op 0 root 0 comm 0x400e612dd240 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO AllReduce: opCount fe sendbuff 0x400eb9e88e00 recvbuff 0x400eb9e88e00 count 1 datatype 7 op +(FSDPPolicyWorkerBase pid=1712285) f 0x400e99e88c00 recvbuff 0x400e99e88c00 count 1 datatype 7 op 0 root 0 comm 0x400e412dd520 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO AllReduce: opCount 11d send +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO AllGath +(FSDPPolicyWorkerBase pid=1712284) 0ebfa88c00 recvbuff 0x400ebfa88c00 count 1 datatype 7 op 0 root 0 comm 0x400e626b23c0 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO AllReduce: opCount 125 sendbuff 0x400ebfa88e00 recvbuff 0x400ebfa88e00 count 1 d +(FSDPPolicyWorkerBase pid=1712286) t 1 datatype 7 op 0 root 0 comm 0x400e152dd8b0 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO AllReduce: opCount 18f sendbuff 0x400e99e88e00 recvbuff 0x400e99e88e00 count 1 datatype 7 op 0 root 0 comm 0x400e152dd8b0 [n +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507560 [0] NCCL INFO Broadcast: opCount 2a sendbuff 0x401760000000 r +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) jpbo-055-25:1507551:1507551 [0] NCCL INFO Broadcast: opCount 1c sendbuff 0x401760000000 recvbuff +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) jpbo-102-30:3949441:3949665 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x40109e800000 recvbu +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) jpbo-102-30:3949440:3949657 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x4010be800000 recvb +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) jpbo-102-17:153955:153955 [0] NCCL INFO Broadcast: opCount 2a sendbuff 0x401760000000 recvbuff 0x401760000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaab09c15390 [nran +(AsyncVLLMInferenceEngine pid=153669, ip=10.128.56.65) jpbo-102-17:153939:153939 [0] NCCL INFO Broadcast: opCount 1c sendbuff 0x401760000000 recvbuff 0x401760000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaab068b8e80 [nranks=49] s +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712 +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO AllReduce: opCount 12b sendbuff 0x400ebfa88c00 recvbuff 0x400ebfa88c00 count 1 da +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) er: opCount 0 sendbuff 0x400e99e2f200 recvbuff 0x400e99e88e00 count 32 datatype 9 op 0 root 0 comm 0x400e116be640 [nranks=4] stream 0x400e113eb590 +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x4010f9400000 recvbuff 0x +(FSDPPolicyWorkerBase pid=1712284) atatype 7 op 0 root 0 comm 0x400e626b23c0 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO AllReduce: opCount 13a sendbuff 0x400ebfa88c00 recvbuff 0x400ebfa88c00 count 1 datatype 7 op 0 root 0 comm 0x400e626b23c0 [nranks +(FSDPPolicyWorkerBase pid=1712286) ranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) tatype 7 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO AllReduce: opCount 139 sendbuff 0x400ebfa88e00 recvbuff 0x400ebfa88e00 count 1 datatype 7 op 0 root 0 comm 0x400e166a4a60 [nranks=8] strea +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) ff 0x401766000000 count 12582912 datatype 9 op 0 root 0 comm 0x400e056c3fa0 [nranks=4] stream 0x400e053f0910 +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) jpbo-102-30:3949441:3949665 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x4012e4400000 recvbuff 0x401760000000 count 12582912 datatype 9 op 0 root 0 comm 0x400e056c +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) uff 0x401786000000 count 12582912 datatype 9 op 0 root 0 comm 0x400e2d6c2c50 [nranks=4] stream 0x400e2d3eeae0 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x401304000000 +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Send: opCount 0 sendbuff (nil) recvbuff 0x4016b7a40000 count 155582464 datatype 9 op 0 root 3 comm 0x400e62a9d6a0 [nranks=4] stream (nil) [repeated 5x across cluster] +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO Broadcast: opCount fd sendbuff 0x401680000000 recvbuff 0x401680000000 count 622329856 datatype 9 op 0 root 0 comm 0x400e626b23c0 [nranks=8] stream (nil) [repeated 9x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount 39 sendbuff 0x4013a9580000 recvbuff 0x4013a9580000 count 4194304 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) [repeated 1730x across cluster] +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO AllReduce: opCount fe sendbuff 0x400eb9e88e00 recvbuff 0x400eb9e88e00 count 1 datatype 7 op 0 root 0 comm 0x400e612dd240 [nranks=8] stream (nil) [repeated 246x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x4012e5800000 re +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) 401740000000 count 4194304 datatype 9 op 0 root 0 comm 0x400e116be640 [nranks=4] stream 0x400e113eb590 +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x4010df000000 recvbuff 0x40178a400000 count 1048576 datatype 9 op 0 root 0 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) m (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO AllGather: +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO AllGather: opCount 0 sendbuf +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) jpbo-102-17:153955:153955 [0] NCCL INFO Broadcast: opCount 55 sendbuff 0x401760000000 recvbuff 0x401760000000 count 50331648 datatype 9 op 0 root +(AsyncVLLMInferenceEngine pid=153669, ip=10.128.56.65) tream (nil) +(AsyncVLLMInferenceEngine pid=153669, ip=10.128.56.65) jpbo-102-17:153939:153939 [0] NCCL INFO Broadcast: opCount 37 sendbuff 0x401760000000 recvbuff 0x401760000000 count 50331648 datatype 9 op 0 root 0 comm 0 +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ecvbuff 0x401760000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaaaf312a400 [nranks=49] stream (nil) +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) jpbo-055-21:1508039:1508039 [0] NCCL INFO Broadcast: opCount 54 sendbuff 0x401760000000 recvbuff 0x401760000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaaaf312a400 [ +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) 0x401760000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaab1887c9d0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) opCount 0 sendbuff 0x400ebfa62c00 recvbuff 0x400ebfa88c00 count 32 datatype 9 op 0 root 0 comm 0x400e16a90290 [nranks=4] stream 0x400e167b8cb0 +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) 3fa0 [nranks=4] stream 0x400e053f0910 +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) jpbo-102-30:3949441:3949665 [0] N +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) jpbo-102-30:3949440:3949657 [0] +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) comm 0x400e116be640 [nranks=4] stream 0x400e113eb590 +(FSDPPolicyWorkerBase pid=1712287) recvbuff 0x4017ca400000 count 1048576 datatype 9 op 0 root 0 comm 0x400e616c3cb0 [nranks=4] stream 0x400e613f0a20 +(FSDPPolicyWorkerBase pid=1712285) cvbuff 0x4017aa400000 count 1048576 datatype 9 op 0 root 0 comm 0x400e416c4290 [nranks=4] stream 0x400e413f0cf0 +(FSDPPolicyWorkerBase pid=1712286) f 0x400e99e35600 recvbuff 0x400e99e88e00 count 1024 datatype 9 op 0 root 0 comm 0x400e156c49a0 [nranks=4] stream 0x400e153f1090 +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x4012ce800000 recvbuff 0x401740000000 count 125 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x401879000000 recvbuff 0x401933c00000 count 4194304 datatype 9 op 0 root 0 comm 0x400e16a90290 [nr +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) CCL INFO AllReduce: opCount fe sendbuff 0x400e99e89000 recvbuff 0x400e99e89000 count 1 datatype 7 op 0 root 0 comm 0x400e052dd0c0 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) jpbo-102-30:3949441:3949665 [0] NCCL INFO AllReduce: opCount fe sendbuff 0x400e99e88c00 recvbuff 0 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:17125 +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3 +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) b590 +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO Al +(FSDPPolicyWorkerBase pid=1712286) 82912 datatype 9 op 0 root 0 comm 0x400e156c49a0 [nranks=4] stream 0x400e153f1090 +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x4012d8800000 recvbuff 0x401746000000 count 12582912 datatype 9 op 0 root 0 comm 0x400e156c49a0 [ +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x401862000000 recvbuff 0x401912a00000 count 4194304 datat +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) jpbo-102-30:3949441:3949665 [0] NCCL INFO AllReduce: opCount fe sendbuff 0x400e99e88e00 recvbuff 0x400e99e88e00 count 1 datatype 7 op 0 root 0 comm 0x400e052dd0c0 +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) jpbo-102-20:4037843:4037843 [0] NCCL INFO Broadcast: +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) jpbo-102-20:4037857:4037857 [0] NCCL INFO Broadcast: opCount +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) 0 comm 0xaaab09c15390 [nranks=49] stream (nil) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) jpbo-102-17:153955:153955 [0] NCCL INFO Broadcast: opCount 80 sendbuff 0x401760000000 recvbuff 0x401760000000 count 503 +(AsyncVLLMInferenceEngine pid=153669, ip=10.128.56.65) jpbo-102-17:153939:153939 [0] NCCL INFO Broadcast: opCount 52 sendbuff 0x401760000000 recvbuff 0x401760000000 count 50331648 da +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO AllReduce: opCount fe sendbuff 0x400eb9e88e00 recvbuf +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) lReduce: opCount 18f sendbuff 0x400e99e88c00 recvbuff 0x400e99e88c00 count 1 datatype 7 op 0 root 0 comm 0x400e112d7f80 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO AllReduce: opCount 18f sendbuff 0x400e99e88e00 recv +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:171228 +(FSDPPolicyWorkerBase pid=1712284) ype 9 op 0 root 0 comm 0x400e62a9d6a0 [nranks=4] stream 0x400e627c66b0 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount 8e sendbuff 0x400ebfa88e00 recvbuff 0x400ebfa88e00 count 4096 datatype 9 op 0 +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) jpbo-102-30:3949441:3949665 [0] NCCL INFO AllG +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) jpbo-102-30:3949440:3949657 [0] NCCL INFO All +(FSDPPolicyWorkerBase pid=1712287) f 0x400eb9e88e00 count 1 datatype 7 op 0 root 0 comm 0x400e612dd240 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO AllReduce: opCount fe sendbuff 0x400e99e88c00 recvbuff 0x400e99e88c00 count 1 datatype 7 op 0 root 0 comm 0x400e412dd520 [n +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) buff 0x400e99e88e00 count 1 datatype 7 op 0 root 0 comm 0x400e112d7f80 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO AllReduce: opCount 18f sendbuff 0x400e99e88c00 recvbuff 0x400e99e88c00 count 1 datatype 7 op 0 ro +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO AllReduce: opCount 18f sen +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) opCount 7f sendbuff 0x4003bdd82400 recvbuff 0x4003bdd82400 count 128 datatype 9 op 0 root 0 comm 0xaaab1fb03cf0 [nranks=49] stream (nil) +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) jpbo-055-19:1508201:1508201 [0] NCCL INFO Broadcast: opCount a9 sendbuff 0x4016b9800000 recvbuff 0x4016b9800000 count 16777216 dat +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) 52 sendbuff 0x4003ddd82400 recvbuff 0x4003ddd82400 count 128 datatype 9 op 0 root 0 comm 0xaaab0db3e300 [nranks=49] stream (nil) +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) jpbo-055-19:1508217:1508217 [0] NCCL INFO Broadcast: opCount 6d sendbuff 0x4016f9800000 recvbuff 0x4016f9800000 count 16777216 datatype 9 +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount aa sendbuff 0x400ebfa88e00 recvbuff 0x400ebfa88e00 count 128 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO AllReduce: opCount 1aa +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) ather: opCount 0 sendbuff 0x401310000000 recvbuff 0x401760000000 count 4194304 datatype 9 op 0 root 0 comm 0x400e056c3fa0 [nranks=4] stream 0x400e053f0910 +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) Gather: opCount 0 sendbuff 0x401332c00000 recvbuff 0x401780000000 count 4194304 datatype 9 op 0 root 0 comm 0x400e2d6c2c50 [nranks=4] stream 0x400e2d3eeae0 +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) jpbo-102-30:3949440:3949657 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x401339800000 recvbuff 0x4017ca400000 coun +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) 31648 datatype 9 op 0 root 0 comm 0xaaab09c15390 [nranks=49] stream (nil) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) jpbo-102-17:153955:153955 [0] NCCL INFO Broadcast: opCount ab sendbuff 0x4003ddd82400 r +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO +(FSDPPolicyWorkerBase pid=1712286) dbuff 0x400e99e89000 recvbuff 0x400e99e89000 count 1 datatype 7 op 0 root 0 comm 0x400e152dd8b0 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO AllReduce: opCount 18f sendbuff 0x400e99e88c00 recvbuff 0x400e99e88c00 +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) ot 0 comm 0x400e112d7f80 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO AllReduce: opCount 18f sendbuff 0x400e99e88e00 recvbuff 0x400e99e88e00 count 1 datatype 7 op 0 root 0 comm 0x400e112d7f80 [nranks=8] stream (ni +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount ab sendbuff 0x400ebfa88c00 recvbuff 0x400ebfa88c00 count 128 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount ac sendbuff 0x401680000000 recvbuff 0x401680000000 count 50331648 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount ad sendbuff 0x401686000000 recvbuff 0x401686000000 count 50331648 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount ae sendbuff 0x401680000000 recvbuff 0x401680000000 count 50331648 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount af sendbuff 0x400ebfa88e00 recvbuff 0x400ebfa88e00 count 4096 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) t 1048576 datatype 9 op 0 root 0 comm 0x400e2d6c2c50 [nranks=4] stream 0x400e2d3eeae0 +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO AllReduce: opCount 1b9 sendb +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount ba sendbuff 0x400ebfa88e00 recvbuff 0x400ebfa88e00 count 4096 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount bb sendbuff 0x400ebfa8b000 recvbuff 0x400ebfa8b000 count 4096 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount bc sendbuff 0x401933c00000 recvbuff 0x401933c00000 count 16777216 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount bd sendbuff 0x4013a9580000 recvbuff 0x4013a9580000 count 4194304 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount be sendbuff 0x401933c00000 recvbuff 0x401933c00000 count 4194304 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount bf sendbuff 0x401680000000 recvbuff 0x401680000000 count 16777216 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO AllReduce: opCount 1c6 sendbuff 0x400ebfa88e00 recvbuff 0x400ebfa88e00 count 1 datatype 7 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (n +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) l) +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO AllGa +(FSDPPolicyWorkerBase pid=1712287) AllGather: opCount 0 sendbuff 0x400eb9e40a00 recvbuff 0x400eb9e88e00 count 1024 datatype 9 op 0 root 0 comm 0x400e616c3cb0 [nranks=4] stream 0x400e613f0a20 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x40134b800000 recvbuff 0x401780000000 co +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO AllReduce: opCount 18f sendbuff 0x400e99e88e00 recvbuff 0x400e99e88e00 count 1 datatype 7 op 0 root 0 comm 0x400e1 +(FSDPPolicyWorkerBase pid=1712284) uff 0x400ebfa88e00 recvbuff 0x400ebfa88e00 count 1 datatype 7 op 0 root 0 comm 0x400e626b23c0 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO AllReduce: opCount 1ce sendbuff 0x400ebfa88c00 recvbuff 0x400ebfa88c00 count 1 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) atype 9 op 0 root 0 comm 0xaaaafa114e20 [nranks=49] stream (nil) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507560 [0] NCCL INFO Broadcast: opCount ca sendbuff 0x4016f9800000 recvbuff 0x4016f9800000 count 16777216 datatype 9 op 0 root 0 comm 0xaaaafa114e20 [nranks=49] stream (nil) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507560 [0] NCCL INFO Broadcast: opCount cb sendbuff 0x4003ddd82400 recvbuff 0x4003ddd82400 count 128 datatype 9 op 0 root 0 comm 0xaaaafa114e20 [nranks=49] stream (nil) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507560 [0] NCCL INFO Broadcast: opCount cc sendbuff 0x4003ddd82400 recvbuff 0x4003ddd82400 count 128 datatype 9 op 0 root 0 comm 0xaaaafa114e20 [nranks=49] stream (nil) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507560 [0] NCCL INFO Broadcast: opCount cd sendbuff 0x401760000000 recvbuff 0x401760000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaaafa114e20 [nranks=49] stream (nil) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507560 [0] NCCL INFO Broadcast: opCount ce sendbuff 0x401760000000 recvbuff 0x401760000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaaafa114e20 [nranks=49] stream (nil) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507560:1507560 [0] NCCL INFO Broadcast: opCount cf sendbuff 0x401760000000 recvbuff 0x401760000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaaafa114e20 [nranks=49] stream (nil) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:1507 +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) jpbo-055-25:1507551:1507 +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) jpbo-055-25:1507555:1507 +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) jpbo-055-25:1507 +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) jpbo-102-18:3945 +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) jpbo-102-18:3945782:3945 +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) jpbo-102-18:3945778:3945 +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) jpbo-102-18:3945 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) il) +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) 0x400e053f0910 +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) jpbo-102-30:3949441:3949665 [0] NCCL INFO AllReduce: op +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) 0x400e2d3eeae0 +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) jpbo-102-30:3949440:3949657 [0] NCCL INFO AllReduce: o +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) jpbo-102-20:4037 +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) jpbo-102-28:3942 +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) jpbo-102-20:4037857:4037 +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) jpbo-102-28:3942487:3942 +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) jpbo-102-20:4037837:4037 +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) jpbo-102-28:3942483:3942 +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) jpbo-102-28:3942 +(AsyncVLLMInferenceEngine pid=4037604, ip=10.128.56.68) jpbo-102-20:4037833:4037 +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) jpbo-055-22:1497 +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) jpbo-055-22:1497158:1497 +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) jpbo-055-22:1497138:1497 +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) jpbo-055-22:1497 +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) jpbo-102-17:153955:153955 [0] NCCL INFO Broadcast: opCo +(AsyncVLLMInferenceEngine pid=153669, ip=10.128.56.65) jpbo-102-17:153939:153939 [0] NCCL INFO Broadcast: opCount 8a s +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) jpbo-055-21:1508 +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) jpbo-055-21:1508043:1508 +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) jpbo-055-21:1508055:1508 +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) jpbo-055-21:1508 +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) jpbo-055-19:1508 +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) jpbo-055-19:1508217:1508 +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) jpbo-055-19:1508209:1508 +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) jpbo-055-19:1508 +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) jpbo-055-18:1507 +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) jpbo-055-18:1507832:1507 +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) jpbo-055-18:1507836:1507 +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) jpbo-055-18:1507 +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) jpbo-055-23:1496 +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) jpbo-055-23:1496327:1496 +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) jpbo-055-23:1496303:1496 +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) jpbo-055-23:1496 +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) jpbo-102-25:3946 +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) jpbo-102-25:3946 +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) jpbo-102-25:3946095:3946 +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) jpbo-102-25:3946082:3946 +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) ther: opCount 0 sendbuff 0x401320000000 recvbuff 0x401740000000 count 12582912 datatype 9 op 0 root 0 comm 0x400e116be640 [nranks=4] stream 0x400e113eb590 +(FSDPPolicyWorkerBase pid=1712287) unt 12582912 datatype 9 op 0 root 0 comm 0x400e616c3cb0 [nranks=4] stream 0x400e613f0a20 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x401355800000 recvbuff 0x401786000000 count 12582912 datatype 9 op 0 root 0 comm 0x400e616c3cb0 [nranks=4] stre +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO AllReduce: opCount 1e3 sendbuff 0x400ebfa88e00 recvbuff 0x400ebfa88e00 count 1 datatype 7 op 0 root 0 comm 0x400e626b23c0 [nrank +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:17122 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount da sendbuff 0x401680000000 recvbuff 0x401680000000 count 50331648 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount db sendbuff 0x400ebfa88e00 recvbuff 0x400ebfa88e00 count 4096 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount dc sendbuff 0x400ebfa8b000 recvbuff 0x400ebfa8b000 count 4096 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount dd sendbuff 0x401933c00000 recvbuff 0x401933c00000 count 16777216 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount de sendbuff 0x4013a9580000 recvbuff 0x4013a9580000 count 4194304 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount df sendbuff 0x401933c00000 recvbuff 0x401933c00000 count 4194304 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) Count fe sendbuff 0x400e99e88c00 recvbuff 0x400e99e88c00 count 1 datatype 7 op 0 root 0 comm 0x400e052dd0c0 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) jpbo-102-30:3949441:3949665 [0] NCCL INFO AllReduce: opCount fe sendbuff 0x400e99e88e00 recvbuff 0x400e99e88e00 count 1 datat +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) pCount fe sendbuff 0x400eb9e88c00 recvbuff 0x400eb9e88c00 count 1 datatype 7 op 0 root 0 comm 0x400e2d2db290 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) jpbo-102-30:3949440:3949657 [0] NCCL INFO AllReduce: opCount fe sendbuff 0x400eb9e88e00 recvbuff 0x400eb9e88e00 count 1 data +(FSDPPolicyWorkerBase pid=1712287) am 0x400e613f0a20 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO AllReduce: +(FSDPPolicyWorkerBase pid=1712285) 0x400e413f0cf0 +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO AllReduce: opC +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x401334000000 recvbuff 0x401740000000 count 12582912 datatype 9 op 0 root +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount ea sendbuff 0x401933c00000 recvbuff 0x401933c00000 count 4194304 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount eb sendbuff 0x401680000000 recvbuff 0x401680000000 count 16777216 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount ec sendbuff 0x400ebfa88e00 recvbuff 0x400ebfa88e00 count 128 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount ed sendbuff 0x400ebfa88c00 recvbuff 0x400ebfa88c00 count 128 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount ee sendbuff 0x401680000000 recvbuff 0x401680000000 count 50331648 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount ef sendbuff 0x401686000000 recvbuff 0x401686000000 count 50331648 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO AllGather: opCount 0 sen +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) ype 7 op 0 root 0 comm 0x400e052dd0c0 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) jpbo +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) jpbo-102-28:3942507:3942507 [0] NCCL INFO Broadcast: opCount fe sendbuff 0x4016d9800000 recvbuff +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount fe sendbuff 0x401933c00000 recvbuff 0x401933c00000 count 16777216 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949 +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) 0 comm 0x400e116be640 [nranks=4] stream 0x400e113eb590 +(FSDPPolicyWorkerBase pid=1712287) opCount fe sendbuff 0x400eb9e88e00 recvbuff 0x400eb9e88e00 count 1 datatype 7 op 0 root 0 comm 0x400e612dd240 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712285) ount fe sendbuff 0x400e99e88e00 recvbuff 0x400e99e88e00 count 1 datatype 7 op 0 root 0 comm 0x400e412dd520 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO AllReduce: opCount fe sendbuff 0x400e99e89000 recvbuff 0x400e99e89000 count 1 datatyp +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) unt d6 sendbuff 0x4003ddd82400 recvbuff 0x4003ddd82400 count 128 datatype 9 op 0 root 0 comm 0xaaab09c15390 [nranks=49] stream (nil) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) jpbo-102-17:153955:153955 [0] NCCL INFO Broadcast: opCount ff sendbuff 0x401759200000 recvbuff 0x401759200000 count 4194304 datatype 9 op 0 root 0 comm 0xaaab09c15390 [nranks=49] stream (nil) +(AsyncVLLMInferenceEngine pid=153669, ip=10.128.56.65) endbuff 0x4003ddd82400 recvbuff 0x4003ddd82400 count 128 datatype 9 op 0 root 0 comm 0xaaab068b8e80 [nranks=49] stream (nil) +(AsyncVLLMInferenceEngine pid=153669, ip=10.128.56.65) jpbo-102-17:153939:153939 [0] NCCL I +(FSDPPolicyWorkerBase pid=1712286) dbuff 0x401316c00000 recvbuff 0x40178a400000 count 1048576 datatype 9 op 0 root 0 comm 0x400e156c49a0 [nranks=4] stream 0x400e153f1090 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount 10d se +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) b590 +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL IN +(FSDPPolicyWorkerBase pid=1712287) jp +(FSDPPolicyWorkerBase pid=1712285) e 7 op 0 root 0 comm 0x400e412dd520 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) ndbuff 0x400ebfa88e00 recvbuff 0x400ebfa88e00 count 128 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount 11b sendbuff 0x401686000000 recvbuff 0x401686000000 co +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) jpbo-055-23:1496316:1496316 [0] NCCL INFO Broadcast: opCount 128 sendbuff 0x40075203c400 recvbuff 0x40075203c400 count 4096 datatyp +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) jpbo-055-23:1496327:1496327 [0] NCCL INFO Broadcast: opCount be sendbuff 0x40075203c400 recvbuff 0x40075203c400 count 4096 datatype 9 op 0 root 0 comm 0xaaab05dc59f0 [nranks=49] s +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) unt 50331648 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) jpbo-102-30:3949441:3949665 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x401360000000 recvbuff 0x401760000000 count 12582912 datatype 9 op 0 r +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) jpbo-102-30:3949440:3949657 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x401383000000 recvbuff 0x401780000000 count 12582912 datatype 9 op 0 +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) jpbo-102-17:153955:153955 [0] NCCL INFO Broadcast: opCount 12b sendbuff 0x401759200000 recvbuff 0x401759200000 count 4194304 datatype 9 op 0 root 0 c +(AsyncVLLMInferenceEngine pid=153669, ip=10.128.56.65) NFO Broadcast: opCount a5 sendbuff 0x4016f9800000 recvbuff 0x4016f9800000 count 16777216 datatype 9 op 0 root 0 comm 0xaaab068b8e80 [nranks=49] stream (nil) +(AsyncVLLMInferenceEngine pid=153669, ip=10.128.56.65) jpbo-102 +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) jpbo-102 +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) jpbo-055-23:1496308:1496308 [0] NCCL INFO cudaDriverVersion 13020 [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) jpbo-055-23:1496308:1496308 [0] NCCL INFO NCCL version 2.27.7+cuda13.0 [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) jpbo-055-23:1496308:1496638 [0] NCCL INFO NET/Plugin: Could not find: libnccl-net.so.  [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) jpbo-055-23:1496308:1496638 [0] NCCL INFO NET/IB : Using [0]mlx5_0:1/IB [1]mlx5_1:1/IB [2]mlx5_2:1/IB [3]mlx5_3:1/IB [RO]; OOB ib0:10.128.34.183<0> [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) jpbo-055-23:1496308:1496638 [0] NCCL INFO Initialized NET plugin IB [repeated 47x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949846 [0] NCCL INFO Assigned NET plugin IB to comm [repeated 48x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949846 [0] NCCL INFO Using network IB [repeated 48x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949846 [0] NCCL INFO DMA-BUF is available on GPU device 0 [repeated 48x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949846 [0] NCCL INFO ncclCommInitRankConfig comm 0x400f144ecbc0 rank 0 nranks 49 cudaDev 0 nvmlDev 0 busId 901000 commId 0xe5e1db1392935c5f - Init START [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) jpbo-055-23:1496308:1496638 [0] NCCL INFO RAS client listening socket at 127.0.0.1<28028> [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) jpbo-055-23:1496308:1496638 [0] NCCL INFO NCCL_NET_GDR_LEVEL set by environment to LOC [repeated 47x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949846 [0] NCCL INFO Setting affinity for GPU 0 to 0-71 [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) jpbo-055-23:1496308:1496638 [0] NCCL INFO NVLS multicast support is not available on dev 0 (NVLS_NCHANNELS 0) [repeated 47x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949846 [0] NCCL INFO comm 0x400f144ecbc0 rank 0 nRanks 49 nNodes 13 localRanks 1 localRank 0 MNNVL 0 [repeated 48x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949846 [0] NCCL INFO Trees [0] 26/-1/-1->0->-1 [1] 27/-1/-1->0->-1 [2] 28/-1/-1->0->-1 [3] 37/-1/-1->0->-1 [4] 41/-1/-1->0->29 [5] 42/-1/-1->0->30 [6] 43/-1/-1->0->31 [7] 44/-1/-1->0->32 [repeated 48x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949846 [0] NCCL INFO P2P Chunksize set to 131072 [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) jpbo-055-23:1496308:1496638 [0] NCCL INFO PROFILER/Plugin: Could not find: libnccl-profiler.so.  [repeated 47x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949849 [0] NCCL INFO [Proxy Service] Device 0 CPU core 2 [repeated 48x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949850 [0] NCCL INFO [Proxy Service UDS] Device 0 CPU core 4 [repeated 48x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949851 [0] NCCL INFO [Proxy Progress] Device 0 CPU core 5 [repeated 48x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949846 [0] NCCL INFO Channel 00/0 : 26[0] -> 0[0] [receive] via NET/IB/0 [repeated 278x across cluster] +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) jpbo-102-25:3946082:3946472 [0] NCCL INFO Channel 07/0 : 31[2] -> 30[1] via P2P/IPC [repeated 654x across cluster] +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) jpbo-102-25:3946082:3946500 [0] NCCL INFO Allocated shareable buffer 0x40171fe00000 size 2097152 ipcDesc 0x40094433fc10 [repeated 1303x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949846 [0] NCCL INFO Channel 07/0 : 0[0] -> 44[3] [send] via NET/IB/0 [repeated 277x across cluster] +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) jpbo-102-25:3946082:3946472 [0] NCCL INFO Imported shareable buffer device 0 size 10485760 ptr 0x401659a00000 [repeated 1332x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949846 [0] NCCL INFO Connected all rings, use ring PXN 0 GDR 0 [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) jpbo-102 +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102 +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) jpbo-102-25:3946095:3946501 [0] NCCL INFO Allocated shareable buffer 0x401 [repeated 6x across cluster] +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO AllGather: opCount 0 send +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) jpbo-102-25:3946082:3946500 [0] NCCL INFO Allocated shareable buffer 0x40177f000000 size  [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) jpbo-102-25:3946102:3946470 [0] NCC +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) FO AllReduce: opCount 18f sendbuff 0x400e99e88c00 recvbuff 0x400e99e88c00 count 1 datatype 7 op 0 root 0 comm 0x400e112d7f80 [nranks=8] stream (nil) +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) jpbo-102-17:153931:154295 [0] NCCL INFO Allocated shareable buffer 0x4017be200000 si +(FSDPPolicyWorkerBase pid=1712285) jpbo- [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) jpbo-102-19:323622:323622 [ [repeated 4x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949846 [0] NCCL INFO Connected all trees [repeated 48x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949846 [0] NCCL INFO threadThresholds 8/8/64 | 392/8/64 | 512 | 512 [repeated 48x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949846 [0] NCCL INFO 8 coll channels, 8 collnet channels, 0 nvls channels, 8 p2p channels, 1 p2p channels per peer [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) jpbo-102-25:3946082:3946472 [0] NCCL INFO TUNER/Plugin: Could not find: libnccl-tuner.so. Using internal tuner plugin. [repeated 47x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949846 [0] NCCL INFO ncclCommInitRankConfig comm 0x400f144ecbc0 rank 0 nranks 49 cudaDev 0 nvmlDev 0 busId 901000 commId 0xe5e1db1392935c5f - Init COMPLETE [repeated 48x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949846 [0] NCCL INFO Init timings - ncclCommInitRankConfig: rank 0 nranks 49 total 3.26 (kernels 0.00, alloc 0.00, bootstrap 2.56, allgathers 0.04, topo 0.01, graphs 0.00, connections 0.64, rest 0.00) [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) ] NCCL INFO Channel 04/0 : 29[0] -> 17[0] [send] via NET/IB/0 +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) 7bcc00000 size 10485760 ipcDesc 0x40097c33fc20 [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) 10485760 ipcDesc 0x40094433fc10 [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) L INFO Channel 06/0 : 32[3] -> 30[1] via P2P/IPC +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ze 2097152 ipcDesc 0x400984015eb0 +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO AllReduce: opCount ff sendbuff 0x400ebfa88c00 recvbuff 0x400ebfa88c00 count 1 datatype 7 op 0 root 0 comm 0x400e626b23c0 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x4018bf600000 recvbuff 0x4013a9980000 count 1048576 datatype 9 op 0 root 0 comm 0x400e62a9d6a0 [nranks=4] stream 0x400e627c66b0 [repeated 2350x across cluster] +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO AllReduce: opCount 237 sendbuff 0x400ebfa88c00 recvbuff 0x400ebfa88c00 count 1 datatype 7 op 0 root 0 comm 0x400e626b23c0 [nranks=8] stream (nil) [repeated 1178x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) [repeated 3x across cluster] +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO Recv: opCount 0 sendbuff (nil) recvbuff 0x40112a400000 count 155582464 datatype 9 op 0 root 0 comm 0x400e156c49a0 [nranks=4] stream (nil) [repeated 25x across cluster] +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17: +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) jpbo-102-19:323622:323622 [0] NCCL INFO Broadcast: opCount fa sendbuff 0x401720000000 recvbuff 0x401720000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaab14464bc0 [nranks=49] stream (nil) [repeated 27x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) jpbo-102-19:323622:323622 [0] NCCL INFO Broadcast: opCount fb sendbuff 0x401720000000 recvbuff 0x401720000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaab14464bc0 [nranks=49] stream (nil) [repeated 25x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) jpbo-102-19:323622:323622 [0] NCCL INFO Broadcast: opCount fc sendbuff 0x40075203c400 recvbuff 0x40075203c400 count 4096 datatype 9 op 0 root 0 comm 0xaaab14464bc0 [nranks=49] stream (nil) [repeated 25x across cluster] +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) oot 0 comm 0x400e056c3fa0 [nranks=4] stream 0x400e053f0910 +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) jpbo-102-30: +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO AllReduce: opCount 18f sendbuff 0x400e99e +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) 44ecbc0 [nranks=49] stream (nil) [repeated 56x across cluster] +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) root 0 comm 0x400e2d6c2c50 [nranks=4] stream 0x400e2d3eeae0 +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) jpbo-102-30 +(FSDPPolicyWorkerBase pid=1712287) buff 0x400eb9e4f600 recvbuff 0x400eb9e88e00 count 32 datatype 9 op 0 root 0 comm 0x400e616c3cb0 [nranks=4] stream 0x400e613f0a20 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x40138d000000 recvbuff 0x401780000000 count 4194304 datatype 9 o +(FSDPPolicyWorkerBase pid=1712287) type 7 op 0 root 0 comm 0x400e612dd240 [nranks=8] stream (nil) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) jpbo-102-25:3946082:3946082 [0] NCCL INFO Broadcast: opCount a sendbuff 0x401719200000 recvbuff 0x401719200000 count 4194304 datatype 9 op 0 root 0 comm 0xaaab19a39f40 [nranks=49] stream (nil) [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) jpbo-102-25:3946082:3946082 [0] NCCL INFO Broadcast: opCount b sendbuff 0x4016b9800000 recvbuff 0x4016b9800000 count 16777216 datatype 9 op 0 root 0 comm 0xaaab19a39f40 [nranks=49] stream (nil) [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) jpbo-102-25:3946082:3946082 [0] NCCL INFO Broadcast: opCount c sendbuff 0x401720000000 recvbuff 0x401720000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaab19a39f40 [nranks=49] stream (nil) [repeated 98x across cluster] +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) jpbo-102-25:3946082:3946082 [0] NCCL INFO Broadcast: opCount d sendbuff 0x401720000000 recvbuff 0x401720000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaab19a39f40 [nranks=49] stream (nil) [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) jpbo-102-25:3946082:3946082 [0] NCCL INFO Broadcast: opCount e sendbuff 0x401720000000 recvbuff 0x401720000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaab19a39f40 [nranks=49] stream (nil) [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) jpbo-102-25:3946082:3946082 [0] NCCL INFO Broadcast: opCount f sendbuff 0x4016b9800000 recvbuff 0x4016b9800000 count 16777216 datatype 9 op 0 root 0 comm 0xaaab19a39f40 [nranks=49] stream (nil) [repeated 98x across cluster] +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) op 0 root 0 comm 0xaaab19a39f40 [nranks=49] stream (nil) [repeated 21x across cluster] +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO AllReduce: opCount 18f sendbuff 0x400e99e88c00 recvbuff 0x400e99e88c00 count 1 datatype 7 +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO AllReduce: opCou +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) buff 0x400ebfa88e00 recvbuff 0x400ebfa88e00 count 1 datatype 7 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO AllReduce: opCount fe sendbuff 0x400e99e88e00 recvbuff 0x400e99e88e00 count 1 datatype 7 op 0 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO AllReduce: opCoun +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:17122 +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) 88e00 recvbuff 0x400e99e88e00 count 1 datatype 7 op 0 root 0 comm 0x400e112d7f80 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO AllReduce: opCount 1b8 sendbuff 0x400ebfa88c00 recvbuff 0x400ebfa88c00 count 1 d +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount 80 sendbuff 0x401680000000 r [repeated 19x across cluster] +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) jpbo-102-18:3945778:3945778 [0] NCCL INFO Broadcast: opCount a2 sendbuff 0x4016b9800000 recvbuff 0x4016b9 [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) jpbo-102-19:323622:323622 [0] NCCL INFO Broadcast: opCount 2a sendbuff 0x401720000000 recvbuff 0x401720000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaab14464bc0 [nran [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount 1c sendbuff 0x401740000000 recvbuff 0x401740000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] s [repeated 3x across cluster] +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x40132a000000 recvbuff 0 [repeated 2x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) t 245 sendbuff 0x400ebfa89000 recvbuff 0x400ebfa89000 count 1 datatype 7 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO AllReduce: opCount 253 sendbuff 0x400ebfa88e00 re +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) jpbo-102-30:3949441:3949665 [0] NCCL INFO AllReduce: opCount fe sendbuff 0x400e99e8 +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) omm 0xaaab09c15390 [nranks=49] stream (nil) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) jpbo-102-17:153955:153955 [0] NCCL INFO Broadcast: opCount 156 sendbuff 0x4016f +(AsyncVLLMInferenceEngine pid=153669, ip=10.128.56.65) jpbo-102-17:153939:153939 [0] NCCL INFO Broadcast: opCount da sendbuff 0x4016f9800000 recvbuff 0x4016f9800000 count 16777216 datatype 9 op 0 root 0 comm 0xaaab068b8e80 [nran +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) atatype 7 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO AllReduce: opCount 18f sendbuff 0x400e99e88e00 recvbuff 0x400e99e88e00 count 1 datatype 7 op 0 root 0 comm 0x400e112d7f80 [nranks=8] stream +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) tatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 4x across cluster] +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x40132d800000 recvbuff 0x40178a400000 count 4194304 datatype 9 op 0 root 0 comm 0x400e156c4 [repeated 6x across cluster] +(FSDPPolicyWorkerBase pid=1712287) p 0 root 0 comm 0x400e616c3cb0 [nranks=4] stream 0x400e613f0a20 +(FSDPPolicyWorkerBase pid=1712287) jpbo-0 +(FSDPPolicyWorkerBase pid=1712285) jpbo-055- +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO AllReduce: opCount 262 s +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) jpbo-102-30:3949440:3949657 [0] NCCL INFO AllGather: opCount 0 sendbuff [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) jpbo-102-19:323622:323622 [0] NCCL INFO Broadcast: opCount fd sendbuff 0x40075203c400 recvbuff 0x40075203c400 count 4096 datatype 9 op 0 root 0 comm 0xaaab14464bc0 [nranks=49] stream (nil) [repeated 24x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) jpbo-102-19:323622:323622 [0] NCCL INFO Broadcast: opCount 155 sendbuff 0x40075203c400 recvbuff 0x40075203c400 count 4096 datatype 9 op 0 root 0 comm 0xaaab14464bc0 [nranks=49] stream (nil) [repeated 12772x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO AllReduce: opCount fe sendbuff 0x400e99e88e00 recvbuff 0x400e99e88e00 count 1 datatype 7 op 0 root 0 comm 0x400e412dd520 [nranks=8] stream (nil) [repeated 1104x across cluster] +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) x401746000000 count 12582912 datatype 9 op 0 root 0 comm 0x400e116be640 [nranks=4] stream 0x400e113eb590 [repeated 2x across cluster] +(FSDPPolicyWorkerBase pid=1712286) nt 18f sendbuff 0x400e99e88c00 recvbuff 0x400e99e88c00 count 1 datatype 7 op 0 root 0 comm 0x400e152dd8b0 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO AllReduce: opCount 18f sendbuff 0x400e99e88e00 recvbuff 0x400e +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) cvbuff 0x400ebfa88e00 count 1 datatype 7 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO AllReduce: opCount 261 sendbuff 0x400ebfa88c00 recvbuff 0x400ebfa88c00 count 1 datatype 7 op 0 roo +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO AllGather: opCount 0 sendbuf +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) jpbo-102-19:323622:323622 [0] NCCL INFO Broadcast: opCount 55 sendbuff 0x401720000000 recvbuff 0x401720000000 count 50331648 datatype 9 op 0 root  [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) tream (nil) [repeated 24x across cluster] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) jpbo-055-21:1508031:1508031 [0] NCCL INFO Broadcast: opCount 152 sendbuff 0x401740000000 recvbuff 0x401740000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaab31119c60  [repeated 44x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ecvbuff 0x40039dd82400 count 128 datatype 9 op 0 root 0 comm 0xaaab14464bc0 [nranks=49] stream (nil) [repeated 23x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) jpbo-055-22:1497134:1497134 [0] NCCL INFO Broadcast: opCount 54 sendbuff 0x401720000000 recvbuff 0x401720000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaab0533a0a0 [ [repeated 18x across cluster] +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) 0x4016f9800000 count 16777216 datatype 9 op 0 root 0 comm 0xaaab4e1abee0 [nranks=49] stream (nil) [repeated 68x across cluster] +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) 8e00 recvbuff 0x400e99e88e00 count 1 datatype 7 op 0 root 0 comm 0x400e052dd0c0 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712284) nranks=4] stream 0x400e627c66b0 [repeated 9x across cluster] +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) 0x400eb9e4be00 recvbuff 0x400eb9e88e00 count 1024 datatype 9 op 0 root 0 comm 0x400e2d6c2c50 [nranks=4] stream 0x400e2d3eeae0 [repeated 4x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) t 0 comm 0x400e166a4a60 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO AllReduce: opCount 26f sendbuff 0x400ebfa88e00 recvbuff 0x400ebfa88e00 count 1 datatype 7 op 0 root 0 comm 0x400e166a4a60 [nranks=8] st +(FSDPPolicyWorkerBase pid=1712285) f 0x400e99e4f600 recvbuff 0x400e99e88e00 count 32 datatype 9 op 0 root 0 comm 0x400e416c4290 [nranks=4] stream 0x400e413f0cf0 +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x400ebfa7ba00 recvbuff 0x400ebfa88e00 count 32  [repeated 4x across cluster] +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) (nil) +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO AllReduce: opCount 18f sendbuff 0x400e99e88c00 recvbuff 0x400e99e88c00 count 1 datatype 7 op 0 root 0 comm 0x400 +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO AllReduce: opCount fe sendbuff 0x400e99e88e00 recvbuff 0 [repeated 2x across cluster] +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO AllReduce: opCount 277 sendbuff 0x400ebfa88c00 recvbuff 0x400ebfa88c00 co +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) jpbo-055-23:149 +(FSDPPolicyWorkerBase pid=1712284) datatype 9 op 0 root 0 comm 0x400e62a9d6a0 [nranks=4] stream 0x400e627c66b0 [repeated 4x across cluster] +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x4018ca400000 recvbuff 0x401912a00000 count 4194304 datatype 9 op 0 root 0 comm 0x400e62a9d6a0 [ +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) jpbo-102-30:3949440:3949657 [0] NCCL INFO AllReduce: opCount fe sendbuff 0x400eb9e89000 recvbuff 0x400eb9e89000 count 1 datatype 7 op 0 root 0 comm 0x400 [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) jpbo-055-23:149 +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) jpbo-102-25:394 +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) jpbo-102-25:394 +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) jpbo-055-25:150 +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) jpbo-055-25:150 +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) jpbo-102-18:394 +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) jpbo-102-18:3945796:3945796 [0] NCCL INFO Broadcast:  [repeated 18x across cluster] +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) jpbo-102-18:3945778:3945778 [0] NCCL INFO Broadcast: opCount  [repeated 20x across cluster] +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) jpbo-102-18:394 +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) jpbo-102-28:394 +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) 0 comm 0xaaab14464bc0 [nranks=49] stream (nil) [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) jpbo-102-19:323622:323622 [0] NCCL INFO Broadcast: opCount 80 sendbuff 0x401720000000 recvbuff 0x401720000000 count 503 [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount 52 sendbuff 0x401740000000 recvbuff 0x401740000000 count 50331648 da [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) jpbo-102-28:394 +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) jpbo-102-20:403 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) ream (nil) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO A +(FSDPPolicyWorkerBase pid=3949441, ip=10.128.56.78) jpbo-102-30:3949441:3949665 [0] +(FSDPPolicyWorkerBase pid=3949440, ip=10.128.56.78) jpbo-102-30:3949440:3949657 [0] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) jpbo-055-22:149 +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) jpbo-055-22:149 +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) jpbo-055-19:150 +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) jpbo-055-19:150 +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) jpbo-055-18:150 +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) jpbo-055-18:150 +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) jpbo-055-21:150 +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) jpbo-055-21:150 +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO AllReduce: opCount fe sendbuff 0x400eb9e88c00 recvbuff 0x400eb9e88c00 count 1 datatype 7 op 0 root 0 com +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x40137ec00000 recv +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712 +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO All +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) llGather: opCount 0 sendbuff 0x401912c00000 recvbuff 0x401686000000 count 12582912 datatype 9 op 0 root 0 comm 0x400e16a90290 [nranks=4] stream 0x400e167b8cb0 +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) (EngineCore_DP0 pid=153955) INFO 06-14 04:08:14 [block_pool.py:452] Successfully reset prefix cache +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) opCount 7f sendbuff 0x4003bdd82400 recvbuff 0x4003bdd82400 count 128 datatype 9 op 0 root 0 comm 0xaaab31119c60 [nranks=49] stream (nil) [repeated 18x across cluster] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) jpbo-055-21:1508031:1508031 [0] NCCL INFO Broadcast: opCount a9 sendbuff 0x4016d9800000 recvbuff 0x4016d9800000 count 16777216 dat [repeated 18x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) sendbuff 0x400ebfa88c00 recvbuff 0x400ebfa88c00 count 1 datatype 7 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 21x across cluster] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) jpbo-055-21:1508055:1508055 [0] NCCL INFO Broadcast: opCount 6d sendbuff 0x4016d9800000 recvbuff 0x4016d9800000 count 16777216 datatype 9  [repeated 20x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount aa sendbuff 0x401739200000 recvbuff 0x401739200000 count 4194304 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 48x across cluster] +(FSDPPolicyWorkerBase pid=1712285) Gather: opCount 0 sendbuff 0x400e99e40a00 recvbuff 0x400e99e88e00 count 1024 datatype 9 op 0 root 0 comm 0x400e416c4290 [nranks=4] stream 0x400e413f0cf0 +(FSDPPolicyWorkerBase pid=1712286) jpbo-055-17:1712286:1712544 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x40131ca00000 recvbuff 0x4016fa400000 coun +(FSDPPolicyWorkerBase pid=1712284) datatype 7 op 0 root 0 comm 0x400e626b23c0 [nranks=8] stream (nil) [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) jpbo-102-19:323622:323622 [0] NCCL INFO Broadcast: opCount ab sendbuff 0x40039dd82400 r [repeated 3x across cluster] +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) jpbo-102-30:3949439:3949649 [0] NCCL INFO +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount ab sendbuff 0x401739200000 recvbuff 0x401739200000 count 4194304 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 44x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount ac sendbuff 0x4016d9800000 recvbuff 0x4016d9800000 count 16777216 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount ad sendbuff 0x401740000000 recvbuff 0x401740000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 98x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount ae sendbuff 0x401740000000 recvbuff 0x401740000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount af sendbuff 0x401740000000 recvbuff 0x401740000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 48x across cluster] +(FSDPPolicyWorkerBase pid=1712286) t 1048576 datatype 9 op 0 root 0 comm 0x400e156c49a0 [nranks=4] stream 0x400e153f1090 +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount ba sendbuff 0x4016d9800000 recvbuff 0x4016d9800000 count 16777216 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount bb sendbuff 0x401740000000 recvbuff 0x401740000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 98x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount bc sendbuff 0x401740000000 recvbuff 0x401740000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount bd sendbuff 0x401740000000 recvbuff 0x401740000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) jpbo-055-18:1507836:1507836 [0] NCCL INFO Broadcast: opCount be sendbuff 0x4016d9800000 recvbuff 0x4016d9800000 count 16777216 datatype 9 op 0 root 0 comm 0xaaab44415330 [nranks=49] stream (nil) [repeated 77x across cluster] +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) jpbo-055-18:1507836:1507836 [0] NCCL INFO Broadcast: opCount bf sendbuff 0x401739200000 recvbuff 0x401739200000 count 4194304 datatype 9 op 0 root 0 comm 0xaaab44415330 [nranks=49] stream (nil) [repeated 48x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO AllGa +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) AllGather: opCount 0 sendbuff 0x40136e200000 recvbuff 0x4016f8c00000 count 1048576 datatype 9 op 0 root 0 comm 0x400e116be640 [nranks=4] stream 0x400e113eb590 +(FSDPPolicyWorkerBase pid=1712284) jpbo-055-17:1712284:1712545 [0] NCCL INFO AllReduce: opCount 28c sendbuff 0x400ebfa88e00 recvbuff 0x400ebfa88e00 count 1 datatype 7 op 0 root 0 comm 0x400e626b23c0 +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) atype 9 op 0 root 0 comm 0xaaab45f8b160 [nranks=49] stream (nil) [repeated 18x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount ca sendbuff 0x401740000000 recvbuff 0x401740000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount cb sendbuff 0x401740000000 recvbuff 0x401740000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount cc sendbuff 0x4016d9800000 recvbuff 0x4016d9800000 count 16777216 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 98x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount cd sendbuff 0x401739200000 recvbuff 0x401739200000 count 4194304 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount ce sendbuff 0x401739200000 recvbuff 0x401739200000 count 4194304 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount cf sendbuff 0x4016d9800000 recvbuff 0x4016d9800000 count 16777216 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) jpbo-102-19:323622:323622 [0] NCCL INFO Broadcast: opCo [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount 8a s [repeated 3x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) ther: opCount 0 sendbuff 0x4018b8800000 recvbuff 0x401680000000 count 4194304 datatype 9 op 0 root 0 comm 0x400e16a90290 [nranks=4] stream 0x400e167b8cb0 +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) jpbo-055-21:1508055:1508055 [0] NCCL INFO Broadcast: opCount da sendbuff 0x4016d9800000 recvbuff 0x4016d9800000 count 16777216 datatype 9 op 0 root 0 comm 0xaaab55eacd10 [nranks=49] stream (nil) [repeated 94x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount db sendbuff 0x401739200000 recvbuff 0x401739200000 count 4194304 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount dc sendbuff 0x401739200000 recvbuff 0x401739200000 count 4194304 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount dd sendbuff 0x4016d9800000 recvbuff 0x4016d9800000 count 16777216 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount de sendbuff 0x401740000000 recvbuff 0x401740000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 98x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount df sendbuff 0x401740000000 recvbuff 0x401740000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 48x across cluster] +(FSDPPolicyWorkerBase pid=1712287) jpbo-055-17:1712287:1712546 [0] NCCL INFO AllReduce: opCount fe sendbuff 0x400eb9e89000 recvbuff 0x400eb9e89000 count 1 data +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount ea sendbuff 0x401739200000 recvbuff 0x401739200000 count 4194304 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount eb sendbuff 0x4016d9800000 recvbuff 0x4016d9800000 count 16777216 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount ec sendbuff 0x401740000000 recvbuff 0x401740000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 98x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount ed sendbuff 0x401740000000 recvbuff 0x401740000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount ee sendbuff 0x401740000000 recvbuff 0x401740000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount ef sendbuff 0x4016d9800000 recvbuff 0x4016d9800000 count 16777216 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 98x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) jpbo-102-18:3945796:3945796 [0] NCCL INFO Broadcast: opCount fe sendbuff 0x4016d9800000 recvbuff  [repeated 18x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) jpbo-102-19:323622:323622 [0] NCCL INFO Broadcast: opCount fe sendbuff 0x4016b9800000 recvbuff 0x4016b9800000 count 16777216 datatype 9 op 0 root 0 comm 0xaaab14464bc0 [nranks=49] stream (nil) [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) unt d6 sendbuff 0x40039dd82400 recvbuff 0x40039dd82400 count 128 datatype 9 op 0 root 0 comm 0xaaab14464bc0 [nranks=49] stream (nil) [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) jpbo-055-18:1507824:1507824 [0] NCCL INFO Broadcast: opCount ff sendbuff 0x401759200000 recvbuff 0x401759200000 count 4194304 datatype 9 op 0 root 0 comm 0xaaab4e1abee0 [nranks=49] stream (nil) [repeated 23x across cluster] +(FSDPPolicyWorkerBase pid=1712284) endbuff 0x400ebfa88e00 recvbuff 0x400ebfa88e00 count 1 datatype 7 op 0 root 0 comm 0x400e626b23c0 [nranks=8] stream (nil) [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL I [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) jpbo-055-18:1507836:1507836 [0] NCCL INFO Broadcast: opCount d9 se [repeated 21x across cluster] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) e 9 op 0 root 0 comm 0xaaab31119c60 [nranks=49] stream (nil) [repeated 19x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ndbuff 0x401740000000 recvbuff 0x401740000000 count 50331648 datatype 9 op 0 root 0 comm 0xaaab55eacd10 [nranks=49] stream (nil) [repeated 21x across cluster] +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) jpbo-055-18:1507824:1507824 [0] NCCL INFO Broadcast: opCount 128 sendbuff 0x40079203c400 recvbuff 0x40079203c400 count 4096 datatyp [repeated 18x across cluster] +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) jpbo-055-18:1507836:1507836 [0] NCCL INFO Broadcast: opCount be sendbuff 0x40077203c400 recvbuff 0x40077203c400 count 4096 datatype 9 op 0 root 0 comm 0xaaab44415330 [nranks=49] s [repeated 20x across cluster] +(FSDPPolicyWorkerBase pid=1712284) unt 1 datatype 7 op 0 root 0 comm 0x400e626b23c0 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x401370000000 recvbuff 0x401760000000 count 4194304 datatype 9 op 0 +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) jpbo-102-19:323622:323622 [0] NCCL INFO Broadcast: opCount 12b sendbuff 0x401719200000 recvbuff 0x401719200000 count 4194304 datatype 9 op 0 root 0 c [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) NFO Broadcast: opCount a5 sendbuff 0x4016d9800000 recvbuff 0x4016d9800000 count 16777216 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nranks=49] stream (nil) [repeated 3x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) jpbo- [repeated 4x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x400ebfa87200 recvbuff 0x400ebfa88e00 count 1024 datatype 9 op 0 root 0 comm 0x400e16a90290 [nranks=4] stream 0x400e167b8cb0 [repeated 703x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO AllReduce: opCount 28b sendbuff 0x400ebfa88c00 recvbuff 0x400ebfa88c00 count 1 datatype 7 op 0 root 0 comm 0x400e166a4a60 [nranks=8] stream (nil) [repeated 362x across cluster] +(FSDPPolicyWorkerBase pid=1712286) e152dd8b0 [nranks=8] stream (nil) [repeated 26x across cluster] +(FSDPPolicyWorkerBase pid=1712285) root 0 comm 0x400e416c4290 [nranks=4] stream 0x400e413f0cf0 +(FSDPPolicyWorkerBase pid=3949439, ip=10.128.56.78) op 0 root 0 comm 0x400e112d7f80 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO AllReduce: opCount fe sendbuff 0x400e [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) omm 0xaaab14464bc0 [nranks=49] stream (nil) [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) jpbo-102-19:323622:323622 [0] NCCL INFO Broadcast: opCount 156 sendbuff 0x4016b [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount da sendbuff 0x4016d9800000 recvbuff 0x4016d9800000 count 16777216 datatype 9 op 0 root 0 comm 0xaaab1d09ade0 [nran [repeated 3x across cluster] +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949434 [0] NCCL INFO AllGather: opCount 0 sendbuff 0x400ebfa87 +(FSDPPolicyWorkerBase pid=3949363, ip=10.128.56.78) jpbo-102-30:3949363:3949838 [0] NCCL INFO Broadcast: opCount 18b sendbuff 0x400ebfa88e00 recvbuff 0x400ebfa88e00 count 4096 datatype 9 op 0 root 0 comm 0x400f144ecbc0 [nranks=49] stream (nil) [repeated 1563x across cluster] +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO AllReduce: opCount fe sendbuff 0x400e99e88e00 recvbuff 0x400e99e88e00 count 1 datatype 7 op 0 root 0 comm 0x400e412dd520 [nranks=8] stream (nil) [repeated 164x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) jpbo-102-19:323614:323614 [0] NCCL INFO Broadcast: opCount f6 sendbuff 0x40075203c400 recvbuff 0x40075203c400 count 4096 datatype 9 op 0 root  [repeated 25x across cluster] +(FSDPPolicyWorkerBase pid=1712286) 99e88e00 count 1 datatype 7 op 0 root 0 comm 0x400e152dd8b0 [nranks=8] stream (nil) +(FSDPPolicyWorkerBase pid=1712285) 99e88e00 recvbuff 0x400e99e88e00 count 1 datatype 7 op 0 root 0 comm 0x400e412dd520 [nranks=8] stream (nil) [repeated 7x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(FSDPPolicyWorkerBase pid=1712285) jpbo-055-17:1712285:1712547 [0] NCCL INFO AllReduce: opCount fe sendbuff 0x400e99e88c00 recvbuff 0x400e99e88c00 count 1 datatype 7 op 0 root 0 comm 0 +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) (EngineCore_DP0 pid=1497134) INFO 06-14 04:08:14 [block_pool.py:452] Successfully reset prefix cache [repeated 47x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 647x across cluster] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) INFO 06-14 04:08:31 [hf.py:318] Detected the chat template content format to be 'string'. You can set `--chat-template-content-format` to override this. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) INFO 06-14 04:08:35 [loggers.py:259] Engine 000: Avg prompt throughput: 11.9 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.3%, Prefix cache hit rate: 0.0% +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) INFO 06-14 04:08:36 [hf.py:318] Detected the chat template content format to be 'string'. You can set `--chat-template-content-format` to override this. [repeated 30x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) INFO 06-14 04:08:41 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 45.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.4%, Prefix cache hit rate: 0.0% [repeated 27x across cluster] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) INFO 06-14 04:08:37 [hf.py:318] Detected the chat template content format to be 'string'. You can set `--chat-template-content-format` to override this. +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:08:46 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 70.0 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.7%, Prefix cache hit rate: 54.3% [repeated 33x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:08:51 [loggers.py:259] Engine 000: Avg prompt throughput: 31.9 tokens/s, Avg generation throughput: 82.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.8%, Prefix cache hit rate: 54.3% [repeated 32x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:08:56 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 83.0 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.9%, Prefix cache hit rate: 54.3% [repeated 32x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:09:01 [loggers.py:259] Engine 000: Avg prompt throughput: 76.9 tokens/s, Avg generation throughput: 68.5 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.1%, Prefix cache hit rate: 65.6% [repeated 30x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:09:06 [loggers.py:259] Engine 000: Avg prompt throughput: 27.2 tokens/s, Avg generation throughput: 68.5 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.2%, Prefix cache hit rate: 74.5% [repeated 32x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:09:11 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 81.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.3%, Prefix cache hit rate: 74.5% [repeated 32x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:09:13] OK: 103 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:09:13] OK: RSS 1.00 GiB | node mem 397.9/858.0 GiB used (46.4%), avail 460.1 GiB +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:09:16 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 80.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.4%, Prefix cache hit rate: 74.5% [repeated 32x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:09:21 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 80.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.6%, Prefix cache hit rate: 74.5% [repeated 31x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:09:21] OK: 149 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:09:21] OK: RSS 1.07 GiB | node mem 385.8/858.0 GiB used (45.0%), avail 472.2 GiB +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:09:26 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 79.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.7%, Prefix cache hit rate: 74.5% [repeated 32x across cluster] +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) INFO 06-14 04:09:29 [hf.py:318] Detected the chat template content format to be 'string'. You can set `--chat-template-content-format` to override this. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:09:29] OK: 161 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:09:29] OK: RSS 1.00 GiB | node mem 392.5/858.0 GiB used (45.7%), avail 465.5 GiB +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:09:31 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 79.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.8%, Prefix cache hit rate: 74.5% [repeated 33x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) INFO 06-14 04:09:33 [hf.py:318] Detected the chat template content format to be 'string'. You can set `--chat-template-content-format` to override this. [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:09:36 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 86.5 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.9%, Prefix cache hit rate: 74.5% [repeated 39x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 2x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:09:38] OK: 187 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:09:38] OK: RSS 1.08 GiB | node mem 382.1/858.0 GiB used (44.5%), avail 475.9 GiB +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) INFO 06-14 04:09:34 [hf.py:318] Detected the chat template content format to be 'string'. You can set `--chat-template-content-format` to override this. +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:09:41 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 88.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.0%, Prefix cache hit rate: 74.5% [repeated 36x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:09:46 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 88.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.1%, Prefix cache hit rate: 74.5% [repeated 32x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:09:51 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 87.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.3%, Prefix cache hit rate: 74.5% [repeated 38x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:09:56 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 87.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.4%, Prefix cache hit rate: 74.5% [repeated 40x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:09:58] OK: 230 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:09:58] OK: RSS 1.80 GiB | node mem 259.9/858.0 GiB used (30.3%), avail 598.1 GiB +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:10:01 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 87.5 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.5%, Prefix cache hit rate: 74.5% [repeated 39x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:10:06 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 87.3 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.6%, Prefix cache hit rate: 74.5% [repeated 38x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:10:11 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 87.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.8%, Prefix cache hit rate: 74.5% [repeated 38x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:10:16 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 87.3 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.9%, Prefix cache hit rate: 74.5% [repeated 38x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:10:21 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 60.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.6%, Prefix cache hit rate: 74.5% [repeated 37x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:10:26 [loggers.py:259] Engine 000: Avg prompt throughput: 216.4 tokens/s, Avg generation throughput: 78.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.4%, Prefix cache hit rate: 71.5% [repeated 37x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:10:31 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 79.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.9%, Prefix cache hit rate: 71.5% [repeated 37x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:10:36 [loggers.py:259] Engine 000: Avg prompt throughput: 35.1 tokens/s, Avg generation throughput: 79.1 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.7%, Prefix cache hit rate: 80.8% [repeated 37x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:10:41 [loggers.py:259] Engine 000: Avg prompt throughput: 51.8 tokens/s, Avg generation throughput: 71.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.8%, Prefix cache hit rate: 85.1% [repeated 37x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:10:46 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 88.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.9%, Prefix cache hit rate: 85.1% [repeated 37x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:10:51 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 85.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.1%, Prefix cache hit rate: 85.1% [repeated 36x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:10:56 [loggers.py:259] Engine 000: Avg prompt throughput: 129.6 tokens/s, Avg generation throughput: 65.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.3%, Prefix cache hit rate: 85.4% [repeated 37x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:11:01 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 76.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.4%, Prefix cache hit rate: 85.4% [repeated 37x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:11:06 [loggers.py:259] Engine 000: Avg prompt throughput: 76.4 tokens/s, Avg generation throughput: 77.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.6%, Prefix cache hit rate: 87.5% [repeated 37x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:11:11 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 87.0 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.8%, Prefix cache hit rate: 87.5% [repeated 37x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:11:13] OK: 110 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:11:13] OK: RSS 1.05 GiB | node mem 397.9/858.0 GiB used (46.4%), avail 460.1 GiB +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:11:16 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 87.0 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.9%, Prefix cache hit rate: 87.5% [repeated 37x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:11:21] OK: 150 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:11:21] OK: RSS 1.10 GiB | node mem 385.9/858.0 GiB used (45.0%), avail 472.0 GiB +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:11:21 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 86.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.0%, Prefix cache hit rate: 87.5% [repeated 37x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:11:26 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 61.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.7%, Prefix cache hit rate: 87.5% [repeated 37x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:11:29] OK: 166 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:11:29] OK: RSS 1.05 GiB | node mem 392.7/858.0 GiB used (45.8%), avail 465.3 GiB +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:11:31 [loggers.py:259] Engine 000: Avg prompt throughput: 48.6 tokens/s, Avg generation throughput: 67.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.3%, Prefix cache hit rate: 91.2% [repeated 36x across cluster] +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) INFO 06-14 04:11:31 [hf.py:318] Detected the chat template content format to be 'string'. You can set `--chat-template-content-format` to override this. +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:11:36 [loggers.py:259] Engine 000: Avg prompt throughput: 13.6 tokens/s, Avg generation throughput: 70.5 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.4%, Prefix cache hit rate: 92.4% [repeated 44x across cluster] +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) INFO 06-14 04:11:35 [hf.py:318] Detected the chat template content format to be 'string'. You can set `--chat-template-content-format` to override this. [repeated 5x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:11:38] OK: 164 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:11:38] OK: RSS 1.16 GiB | node mem 382.3/858.0 GiB used (44.6%), avail 475.7 GiB +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:11:41 [loggers.py:259] Engine 000: Avg prompt throughput: 13.4 tokens/s, Avg generation throughput: 71.5 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.5%, Prefix cache hit rate: 93.3% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) INFO 06-14 04:11:38 [hf.py:318] Detected the chat template content format to be 'string'. You can set `--chat-template-content-format` to override this. +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) INFO 06-14 04:11:47 [loggers.py:259] Engine 000: Avg prompt throughput: 626.1 tokens/s, Avg generation throughput: 235.3 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.7%, Prefix cache hit rate: 85.7% [repeated 46x across cluster] +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) INFO 06-14 04:11:52 [loggers.py:259] Engine 000: Avg prompt throughput: 53.6 tokens/s, Avg generation throughput: 249.5 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 17.0%, Prefix cache hit rate: 87.0% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) INFO 06-14 04:11:57 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 268.0 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 17.4%, Prefix cache hit rate: 87.0% [repeated 45x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:11:58] OK: 272 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:11:58] OK: RSS 1.82 GiB | node mem 259.9/858.0 GiB used (30.3%), avail 598.1 GiB +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) INFO 06-14 04:12:02 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 144.5 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.0%, Prefix cache hit rate: 88.0% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) INFO 06-14 04:12:07 [loggers.py:259] Engine 000: Avg prompt throughput: 108.5 tokens/s, Avg generation throughput: 125.6 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.4%, Prefix cache hit rate: 89.4% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) INFO 06-14 04:12:12 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 142.9 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.6%, Prefix cache hit rate: 89.4% [repeated 46x across cluster] +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) INFO 06-14 04:12:17 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 144.8 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.8%, Prefix cache hit rate: 89.4% [repeated 44x across cluster] +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) INFO 06-14 04:12:22 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 142.0 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.6%, Prefix cache hit rate: 89.4% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) INFO 06-14 04:12:27 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 147.4 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.2%, Prefix cache hit rate: 82.0% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) INFO 06-14 04:12:32 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 147.2 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.4%, Prefix cache hit rate: 82.0% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) INFO 06-14 04:12:37 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 146.7 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.7%, Prefix cache hit rate: 82.0% [repeated 46x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) INFO 06-14 04:12:42 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 145.6 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.9%, Prefix cache hit rate: 82.0% [repeated 44x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) INFO 06-14 04:12:47 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 145.8 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.1%, Prefix cache hit rate: 82.0% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) INFO 06-14 04:12:52 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 146.7 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.3%, Prefix cache hit rate: 82.0% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) INFO 06-14 04:12:57 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 147.3 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.5%, Prefix cache hit rate: 82.0% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) INFO 06-14 04:13:02 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 146.9 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.7%, Prefix cache hit rate: 82.0% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) INFO 06-14 04:13:07 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 145.9 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.9%, Prefix cache hit rate: 82.0% [repeated 44x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) INFO 06-14 04:13:12 [loggers.py:259] Engine 000: Avg prompt throughput: 17.9 tokens/s, Avg generation throughput: 133.8 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.1%, Prefix cache hit rate: 85.1% [repeated 45x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:13:13] OK: 114 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:13:13] OK: RSS 1.07 GiB | node mem 398.0/858.0 GiB used (46.4%), avail 460.0 GiB +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) INFO 06-14 04:13:17 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 145.9 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.3%, Prefix cache hit rate: 85.1% [repeated 45x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:13:21] OK: 186 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:13:21] OK: RSS 1.22 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.8 GiB +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) INFO 06-14 04:13:22 [loggers.py:259] Engine 000: Avg prompt throughput: 86.3 tokens/s, Avg generation throughput: 116.6 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.6%, Prefix cache hit rate: 87.0% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) INFO 06-14 04:13:27 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 145.9 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.8%, Prefix cache hit rate: 87.0% [repeated 45x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:13:29] OK: 114 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:13:29] OK: RSS 1.08 GiB | node mem 392.9/858.0 GiB used (45.8%), avail 465.1 GiB +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) INFO 06-14 04:13:32 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 145.9 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.0%, Prefix cache hit rate: 87.0% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) INFO 06-14 04:13:37 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 113.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.1%, Prefix cache hit rate: 87.0% [repeated 45x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:13:38] OK: 154 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:13:38] OK: RSS 1.30 GiB | node mem 382.5/858.0 GiB used (44.6%), avail 475.5 GiB +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) INFO 06-14 04:13:42 [loggers.py:259] Engine 000: Avg prompt throughput: 232.5 tokens/s, Avg generation throughput: 116.3 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.6%, Prefix cache hit rate: 89.6% [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) INFO 06-14 04:13:47 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 141.7 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.8%, Prefix cache hit rate: 89.6% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) INFO 06-14 04:13:52 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 140.6 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.0%, Prefix cache hit rate: 89.6% [repeated 46x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) INFO 06-14 04:13:57 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 141.6 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.2%, Prefix cache hit rate: 89.6% [repeated 45x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:13:58] OK: 267 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:13:58] OK: RSS 1.83 GiB | node mem 259.9/858.0 GiB used (30.3%), avail 598.0 GiB +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) INFO 06-14 04:14:02 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 141.3 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.4%, Prefix cache hit rate: 89.6% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) INFO 06-14 04:14:07 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 141.7 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.6%, Prefix cache hit rate: 89.6% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) INFO 06-14 04:14:12 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 140.9 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.8%, Prefix cache hit rate: 89.6% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) INFO 06-14 04:14:17 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 142.0 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 15.0%, Prefix cache hit rate: 89.6% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) INFO 06-14 04:14:22 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 141.7 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 15.2%, Prefix cache hit rate: 89.6% [repeated 44x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) INFO 06-14 04:14:27 [loggers.py:259] Engine 000: Avg prompt throughput: 1033.8 tokens/s, Avg generation throughput: 115.8 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 16.8%, Prefix cache hit rate: 87.7% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) INFO 06-14 04:14:32 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 49.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.8%, Prefix cache hit rate: 85.2% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) INFO 06-14 04:14:37 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 49.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.9%, Prefix cache hit rate: 85.2% [repeated 46x across cluster] +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) INFO 06-14 04:14:39 [hf.py:318] Detected the chat template content format to be 'string'. You can set `--chat-template-content-format` to override this. +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) INFO 06-14 04:14:42 [loggers.py:259] Engine 000: Avg prompt throughput: 180.2 tokens/s, Avg generation throughput: 24.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.2%, Prefix cache hit rate: 89.8% [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) INFO 06-14 04:14:47 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 49.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.2%, Prefix cache hit rate: 89.8% [repeated 46x across cluster] +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) INFO 06-14 04:14:52 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 49.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.3%, Prefix cache hit rate: 89.8% [repeated 46x across cluster] +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) INFO 06-14 04:14:57 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 49.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.4%, Prefix cache hit rate: 89.8% [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) INFO 06-14 04:15:02 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 50.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.4%, Prefix cache hit rate: 89.8% [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) INFO 06-14 04:15:07 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 50.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.5%, Prefix cache hit rate: 89.8% [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) INFO 06-14 04:15:12 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 50.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.6%, Prefix cache hit rate: 89.8% [repeated 47x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:15:13] OK: 163 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:15:13] OK: RSS 1.11 GiB | node mem 398.1/858.0 GiB used (46.4%), avail 459.9 GiB +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) INFO 06-14 04:15:17 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 135.5 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.2%, Prefix cache hit rate: 94.3% [repeated 47x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:15:21] OK: 184 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:15:21] OK: RSS 1.34 GiB | node mem 386.3/858.0 GiB used (45.0%), avail 471.6 GiB +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) INFO 06-14 04:15:22 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 135.2 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.4%, Prefix cache hit rate: 94.3% [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) INFO 06-14 04:15:27 [loggers.py:259] Engine 000: Avg prompt throughput: 45.1 tokens/s, Avg generation throughput: 110.2 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.6%, Prefix cache hit rate: 94.7% [repeated 47x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:15:29] OK: 115 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:15:29] OK: RSS 1.10 GiB | node mem 392.9/858.0 GiB used (45.8%), avail 465.1 GiB +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) INFO 06-14 04:15:32 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 122.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.3%, Prefix cache hit rate: 94.7% [repeated 46x across cluster] +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) INFO 06-14 04:15:37 [loggers.py:259] Engine 000: Avg prompt throughput: 99.0 tokens/s, Avg generation throughput: 130.5 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.1%, Prefix cache hit rate: 95.0% [repeated 47x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:15:38] OK: 148 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:15:38] OK: RSS 1.43 GiB | node mem 382.6/858.0 GiB used (44.6%), avail 475.3 GiB +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) INFO 06-14 04:15:42 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 117.0 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.6%, Prefix cache hit rate: 95.0% [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) INFO 06-14 04:15:47 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 49.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.1%, Prefix cache hit rate: 89.8% [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) INFO 06-14 04:15:52 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 49.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.1%, Prefix cache hit rate: 89.8% [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) INFO 06-14 04:15:57 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 49.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.2%, Prefix cache hit rate: 89.8% [repeated 47x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:15:58] OK: 288 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:15:58] OK: RSS 1.84 GiB | node mem 260.0/858.0 GiB used (30.3%), avail 598.0 GiB +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) INFO 06-14 04:16:02 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 108.0 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.1%, Prefix cache hit rate: 95.3% [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) INFO 06-14 04:16:07 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 49.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.4%, Prefix cache hit rate: 89.8% [repeated 46x across cluster] +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) INFO 06-14 04:16:12 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 49.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.4%, Prefix cache hit rate: 89.8% [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) INFO 06-14 04:16:17 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 49.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.5%, Prefix cache hit rate: 89.8% [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) INFO 06-14 04:16:22 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 49.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.6%, Prefix cache hit rate: 89.8% [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=4037605, ip=10.128.56.68) INFO 06-14 04:16:28 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 49.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.6%, Prefix cache hit rate: 89.8% [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) INFO 06-14 04:16:33 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 156.6 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.7%, Prefix cache hit rate: 95.1% [repeated 49x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:16:36 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:16:36 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:16:36 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:16:36 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:16:36 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:16:36 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:16:36 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:16:36 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:16:36 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:16:36 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:16:36 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:16:36 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:16:36 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:16:36 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:16:36 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:16:36 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:16:36 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:16:36 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:16:36 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:16:36 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:16:36 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:16:36 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:16:36 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:16:36 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:16:36 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:16:36 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) INFO 06-14 04:16:38 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 156.2 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 15.0%, Prefix cache hit rate: 95.1% [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) INFO 06-14 04:16:43 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 157.7 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 15.2%, Prefix cache hit rate: 95.1% [repeated 49x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) INFO 06-14 04:16:48 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 137.0 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.3%, Prefix cache hit rate: 95.1% [repeated 47x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 04:16:49 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 04:16:49 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 04:16:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 04:16:49 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 04:16:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 04:16:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 04:16:49 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 04:16:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 04:16:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 04:16:49 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 04:16:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 04:16:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 04:16:49 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 04:16:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 04:16:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 04:16:49 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 04:16:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 04:16:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 04:16:49 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 04:16:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 04:16:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 04:16:49 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 04:16:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 04:16:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 04:16:49 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 04:16:49 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=3946333, ip=10.128.56.73) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) INFO 06-14 04:16:53 [loggers.py:259] Engine 000: Avg prompt throughput: 74.3 tokens/s, Avg generation throughput: 144.1 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 15.7%, Prefix cache hit rate: 95.6% [repeated 46x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) INFO 06-14 04:16:58 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 155.6 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 15.9%, Prefix cache hit rate: 95.6% [repeated 45x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) INFO 06-14 04:17:03 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 155.4 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 16.1%, Prefix cache hit rate: 95.6% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) INFO 06-14 04:17:08 [loggers.py:259] Engine 000: Avg prompt throughput: 334.3 tokens/s, Avg generation throughput: 135.1 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 22.3%, Prefix cache hit rate: 95.3% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) INFO 06-14 04:17:13 [loggers.py:259] Engine 000: Avg prompt throughput: 70.1 tokens/s, Avg generation throughput: 135.9 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 16.6%, Prefix cache hit rate: 95.7% [repeated 44x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:17:13] OK: 163 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:17:13] OK: RSS 1.20 GiB | node mem 398.2/858.0 GiB used (46.4%), avail 459.8 GiB +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:17:18 [loggers.py:259] Engine 000: Avg prompt throughput: 192.1 tokens/s, Avg generation throughput: 104.0 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 15.5%, Prefix cache hit rate: 95.5% [repeated 45x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:17:21] OK: 171 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:17:21] OK: RSS 1.49 GiB | node mem 386.5/858.0 GiB used (45.1%), avail 471.4 GiB +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:17:23 [loggers.py:259] Engine 000: Avg prompt throughput: 21.6 tokens/s, Avg generation throughput: 112.8 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 15.7%, Prefix cache hit rate: 95.6% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:17:28 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 112.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.3%, Prefix cache hit rate: 95.6% [repeated 45x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:17:29] OK: 113 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:17:29] OK: RSS 1.11 GiB | node mem 393.0/858.0 GiB used (45.8%), avail 465.0 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:17:33 [loggers.py:259] Engine 000: Avg prompt throughput: 36.9 tokens/s, Avg generation throughput: 91.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.6%, Prefix cache hit rate: 95.7% [repeated 45x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:17:38] OK: 124 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:17:38] OK: RSS 1.65 GiB | node mem 382.9/858.0 GiB used (44.6%), avail 475.1 GiB +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:17:38 [loggers.py:259] Engine 000: Avg prompt throughput: 79.7 tokens/s, Avg generation throughput: 108.8 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.7%, Prefix cache hit rate: 95.8% [repeated 44x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:17:43 [loggers.py:259] Engine 000: Avg prompt throughput: 75.8 tokens/s, Avg generation throughput: 74.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.8%, Prefix cache hit rate: 95.8% [repeated 44x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:17:45 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:17:45 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:17:45 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:17:45 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:17:45 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:17:45 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:17:45 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:17:45 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:17:45 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:17:45 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:17:45 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:17:45 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:17:45 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:17:45 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:17:45 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:17:45 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:17:45 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:17:45 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:17:45 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:17:45 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:17:45 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:17:45 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:17:45 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:17:45 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:17:45 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:17:45 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:17:48 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 77.8 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.9%, Prefix cache hit rate: 95.8% [repeated 43x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=3946333, ip=10.128.56.73) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:17:48 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:17:48 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:17:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:17:48 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:17:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:17:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:17:48 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:17:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:17:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:17:48 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:17:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:17:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:17:48 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:17:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:17:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:17:48 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:17:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:17:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:17:48 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:17:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:17:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:17:48 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:17:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:17:48 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:17:48 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 3x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:17:53 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 53.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.2%, Prefix cache hit rate: 95.8% [repeated 44x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:17:58 [loggers.py:259] Engine 000: Avg prompt throughput: 82.0 tokens/s, Avg generation throughput: 72.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.2%, Prefix cache hit rate: 95.9% [repeated 44x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:17:58] OK: 266 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:17:58] OK: RSS 1.85 GiB | node mem 260.0/858.0 GiB used (30.3%), avail 598.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:18:03 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:18:03 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:18:03 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:18:03 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:18:03 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:18:03 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:18:03 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:18:03 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:18:03 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:18:03 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:18:03 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:18:03 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:18:03 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:18:03 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:18:03 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:18:03 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:18:03 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:18:03 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:18:03 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:18:03 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:18:03 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:18:03 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:18:03 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:18:03 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:18:03 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:18:03 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=3946333, ip=10.128.56.73) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:18:03 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 78.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.3%, Prefix cache hit rate: 95.9% [repeated 45x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=3946333, ip=10.128.56.73) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:18:05 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:18:05 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:18:05 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:18:05 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:18:05 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:18:05 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:18:05 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:18:05 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:18:05 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:18:05 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:18:05 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:18:05 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:18:05 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:18:05 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:18:05 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:18:05 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:18:05 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:18:05 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:18:05 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:18:05 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:18:05 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:18:05 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:18:05 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:18:05 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:18:05 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:18:08 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 79.3 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.4%, Prefix cache hit rate: 95.9% [repeated 44x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:18:12 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:18:12 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:18:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:18:12 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:18:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:18:12 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:18:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:18:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:18:12 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:18:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:18:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:18:12 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:18:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:18:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:18:12 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:18:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:18:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:18:12 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:18:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:18:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:18:12 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:18:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:18:12 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:18:12 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=3946333, ip=10.128.56.73) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:18:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:18:13 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 60.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.4%, Prefix cache hit rate: 95.9% [repeated 45x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:18:16 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:18:16 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:18:16 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:18:16 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:18:16 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:18:16 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:18:16 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:18:16 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:18:16 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:18:16 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:18:16 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:18:16 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:18:16 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:18:16 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:18:16 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:18:16 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:18:16 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:18:16 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:18:16 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:18:16 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:18:16 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:18:16 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:18:16 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:18:16 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:18:16 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) INFO 06-14 04:18:18 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 136.3 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.5%, Prefix cache hit rate: 95.4% [repeated 42x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:18:23 [loggers.py:259] Engine 000: Avg prompt throughput: 45.3 tokens/s, Avg generation throughput: 66.0 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.8%, Prefix cache hit rate: 96.0% [repeated 45x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:18:28 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 78.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.9%, Prefix cache hit rate: 96.0% [repeated 42x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) INFO 06-14 04:18:33 [loggers.py:259] Engine 000: Avg prompt throughput: 74.2 tokens/s, Avg generation throughput: 152.1 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 17.6%, Prefix cache hit rate: 95.7% [repeated 45x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) INFO 06-14 04:18:34 [hf.py:318] Detected the chat template content format to be 'string'. You can set `--chat-template-content-format` to override this. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) INFO 06-14 04:18:38 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 192.2 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 17.8%, Prefix cache hit rate: 95.7% [repeated 47x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) INFO 06-14 04:18:43 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 193.5 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.9%, Prefix cache hit rate: 95.7% [repeated 47x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 3x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) INFO 06-14 04:18:48 [loggers.py:259] Engine 000: Avg prompt throughput: 33.3 tokens/s, Avg generation throughput: 291.6 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.0%, Prefix cache hit rate: 95.6% [repeated 46x across cluster] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:18:48 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:18:48 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:18:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:18:48 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:18:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:18:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:18:48 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:18:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:18:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:18:48 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:18:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:18:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:18:48 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:18:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:18:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:18:48 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:18:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:18:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:18:48 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:18:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:18:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:18:48 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:18:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:18:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:18:48 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:18:48 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=3946333, ip=10.128.56.73) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 17x across cluster] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) INFO 06-14 04:18:53 [loggers.py:259] Engine 000: Avg prompt throughput: 33.3 tokens/s, Avg generation throughput: 183.9 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.1%, Prefix cache hit rate: 95.6% [repeated 49x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) INFO 06-14 04:18:58 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 195.4 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.4%, Prefix cache hit rate: 95.6% [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) INFO 06-14 04:19:03 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 135.3 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.7%, Prefix cache hit rate: 95.7% [repeated 49x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) INFO 06-14 04:19:08 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 135.1 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.9%, Prefix cache hit rate: 95.7% [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) INFO 06-14 04:19:13 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 135.0 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.0%, Prefix cache hit rate: 95.7% [repeated 48x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:19:13] OK: 175 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:19:13] OK: RSS 1.29 GiB | node mem 398.3/858.0 GiB used (46.4%), avail 459.7 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) INFO 06-14 04:19:18 [loggers.py:259] Engine 000: Avg prompt throughput: 107.3 tokens/s, Avg generation throughput: 115.9 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.3%, Prefix cache hit rate: 95.6% [repeated 47x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 3x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:19:21] OK: 164 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:19:21] OK: RSS 1.62 GiB | node mem 386.8/858.0 GiB used (45.1%), avail 471.2 GiB +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:19:22 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:19:22 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:19:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:19:22 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:19:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:19:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:19:22 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:19:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:19:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:19:22 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:19:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:19:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:19:22 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:19:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:19:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:19:22 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:19:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:19:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:19:22 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:19:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:19:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:19:22 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:19:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:19:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:19:22 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:19:22 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) INFO 06-14 04:19:23 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 133.9 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.5%, Prefix cache hit rate: 95.6% [repeated 48x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 7x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:19:26 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:19:26 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:19:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:19:26 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:19:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:19:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:19:26 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:19:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:19:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:19:26 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:19:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:19:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:19:26 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:19:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:19:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:19:26 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:19:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:19:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:19:26 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:19:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:19:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:19:26 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:19:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:19:26 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:19:26 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=3946333, ip=10.128.56.73) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) INFO 06-14 04:19:28 [loggers.py:259] Engine 000: Avg prompt throughput: 62.5 tokens/s, Avg generation throughput: 118.9 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.8%, Prefix cache hit rate: 95.7% [repeated 48x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:19:29] OK: 193 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:19:29] OK: RSS 1.17 GiB | node mem 393.0/858.0 GiB used (45.8%), avail 465.0 GiB +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) INFO 06-14 04:19:33 [loggers.py:259] Engine 000: Avg prompt throughput: 170.5 tokens/s, Avg generation throughput: 90.7 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.1%, Prefix cache hit rate: 95.7% [repeated 48x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:19:38] OK: 133 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:19:38] OK: RSS 1.78 GiB | node mem 383.0/858.0 GiB used (44.6%), avail 475.0 GiB +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) INFO 06-14 04:19:38 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 135.5 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.3%, Prefix cache hit rate: 95.7% [repeated 48x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) INFO 06-14 04:19:44 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 50.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.3%, Prefix cache hit rate: 75.8% [repeated 49x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) INFO 06-14 04:19:49 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 50.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.4%, Prefix cache hit rate: 75.8% [repeated 48x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 13x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) INFO 06-14 04:19:54 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 50.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.4%, Prefix cache hit rate: 75.8% [repeated 47x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 2x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:19:58] OK: 329 / 131,072 FDs open (0.3% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:19:58] OK: RSS 1.86 GiB | node mem 260.0/858.0 GiB used (30.3%), avail 598.0 GiB +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) INFO 06-14 04:19:59 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 49.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.5%, Prefix cache hit rate: 75.8% [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) INFO 06-14 04:20:04 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 49.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.6%, Prefix cache hit rate: 75.8% [repeated 48x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) INFO 06-14 04:20:09 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 49.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.6%, Prefix cache hit rate: 75.8% [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:20:12 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:20:12 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:20:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:20:12 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:20:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:20:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:20:12 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:20:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:20:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:20:12 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:20:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:20:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:20:12 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:20:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:20:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:20:12 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:20:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:20:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:20:12 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:20:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:20:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:20:12 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:20:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:20:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:20:12 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:20:12 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=3946333, ip=10.128.56.73) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) INFO 06-14 04:20:13 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 135.1 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.9%, Prefix cache hit rate: 95.7% [repeated 47x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) INFO 06-14 04:20:19 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 50.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.8%, Prefix cache hit rate: 75.8% [repeated 48x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) INFO 06-14 04:20:24 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 50.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.9%, Prefix cache hit rate: 75.8% [repeated 49x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:20:27 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:20:27 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:20:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:20:27 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:20:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:20:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:20:27 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:20:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:20:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:20:27 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:20:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:20:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:20:27 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:20:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:20:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:20:27 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:20:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:20:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:20:27 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:20:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:20:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:20:27 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:20:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:20:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:20:27 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:20:27 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 04:20:29 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 287.9 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 21.7%, Prefix cache hit rate: 93.8% [repeated 48x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=4037604, ip=10.128.56.68) INFO 06-14 04:20:34 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 51.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.3%, Prefix cache hit rate: 95.3% [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=4037604, ip=10.128.56.68) INFO 06-14 04:20:39 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 51.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.4%, Prefix cache hit rate: 95.3% [repeated 48x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:20:43 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:20:43 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:20:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:20:43 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:20:43 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:20:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:20:43 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:20:43 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:20:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:20:43 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:20:43 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:20:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:20:43 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:20:43 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:20:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:20:43 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:20:43 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:20:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:20:43 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:20:43 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:20:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:20:43 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:20:43 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:20:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:20:43 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:20:43 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:20:44 [loggers.py:259] Engine 000: Avg prompt throughput: 188.7 tokens/s, Avg generation throughput: 245.4 tokens/s, Running: 7 reqs, Waiting: 0 reqs, GPU KV cache usage: 39.8%, Prefix cache hit rate: 96.3% [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:20:49 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 286.3 tokens/s, Running: 7 reqs, Waiting: 0 reqs, GPU KV cache usage: 40.2%, Prefix cache hit rate: 96.3% [repeated 48x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:20:52 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:20:52 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:20:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:20:52 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:20:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:20:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:20:52 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:20:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:20:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:20:52 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:20:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:20:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:20:52 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:20:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:20:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:20:52 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:20:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:20:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:20:52 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:20:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:20:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:20:52 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:20:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:20:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:20:52 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:20:52 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:20:54 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 262.6 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 31.7%, Prefix cache hit rate: 96.3% [repeated 48x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 7x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:20:55 [serving.py:315] Error in preprocessing prompt inputs [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:20:55 [serving.py:315] Traceback (most recent call last): [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:20:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:20:55 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:20:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:20:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:20:55 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:20:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:20:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:20:55 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:20:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:20:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:20:55 [serving.py:315] return await asyncio.gather( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:20:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:20:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:20:55 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:20:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:20:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:20:55 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:20:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:20:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:20:55 [serving.py:315] tokens = validator(tokenizer, tokens) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:20:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:20:55 [serving.py:315] raise VLLMValidationError( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:20:55 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) [repeated 2x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new [repeated 2x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:20:59 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 239.7 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 32.1%, Prefix cache hit rate: 96.3% [repeated 48x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:21:01 [serving.py:315] Error in preprocessing prompt inputs [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:21:01 [serving.py:315] Traceback (most recent call last): [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:21:01 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:21:01 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:21:01 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:21:01 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:21:01 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:21:01 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:21:01 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:21:01 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:21:01 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:21:01 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:21:01 [serving.py:315] return await asyncio.gather( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:21:01 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:21:01 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:21:01 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:21:01 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:21:01 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:21:01 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:21:01 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:21:01 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:21:01 [serving.py:315] tokens = validator(tokenizer, tokens) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:21:01 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:21:01 [serving.py:315] raise VLLMValidationError( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:21:01 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) [repeated 2x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new [repeated 2x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:21:04 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 241.0 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 32.4%, Prefix cache hit rate: 96.3% [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:21:09 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 241.9 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 32.7%, Prefix cache hit rate: 96.3% [repeated 48x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:21:13] OK: 174 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:21:13] OK: RSS 1.39 GiB | node mem 399.1/858.0 GiB used (46.5%), avail 458.8 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:21:14 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 242.9 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 33.1%, Prefix cache hit rate: 96.3% [repeated 47x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:21:15 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:21:15 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:21:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:21:15 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:21:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:21:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:21:15 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:21:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:21:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:21:15 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:21:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:21:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:21:15 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:21:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:21:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:21:15 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:21:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:21:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:21:15 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:21:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:21:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:21:15 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:21:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:21:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:21:15 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:21:15 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:21:19 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 242.8 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 33.4%, Prefix cache hit rate: 96.3% [repeated 46x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:21:21] OK: 151 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:21:21] OK: RSS 1.76 GiB | node mem 387.0/858.0 GiB used (45.1%), avail 471.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:21:24 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 243.4 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 33.8%, Prefix cache hit rate: 96.3% [repeated 46x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:21:24 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:21:24 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:21:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:21:24 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:21:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:21:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:21:24 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:21:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:21:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:21:24 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:21:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:21:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:21:24 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:21:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:21:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:21:24 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:21:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:21:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:21:24 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:21:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:21:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:21:24 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:21:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:21:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:21:24 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:21:24 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:21:29 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 246.5 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 34.1%, Prefix cache hit rate: 96.3% [repeated 46x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:21:29] OK: 193 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:21:29] OK: RSS 1.20 GiB | node mem 393.0/858.0 GiB used (45.8%), avail 465.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) INFO 06-14 04:21:34 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 326.6 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 31.0%, Prefix cache hit rate: 94.0% [repeated 47x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:21:38 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:21:38 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:21:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:21:38 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:21:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:21:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:21:38 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:21:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:21:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:21:38 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:21:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:21:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:21:38 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:21:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:21:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:21:38 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:21:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:21:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:21:38 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:21:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:21:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:21:38 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:21:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:21:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:21:38 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:21:38 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:21:38] OK: 135 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:21:38] OK: RSS 1.88 GiB | node mem 383.2/858.0 GiB used (44.7%), avail 474.7 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) INFO 06-14 04:21:39 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 326.8 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 31.4%, Prefix cache hit rate: 94.0% [repeated 46x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new [repeated 2x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. [repeated 2x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:21:38 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:21:38 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:21:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:21:38 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:21:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:21:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:21:38 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:21:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:21:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:21:38 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:21:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:21:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:21:38 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:21:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:21:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:21:38 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:21:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:21:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:21:38 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:21:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:21:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:21:38 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:21:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:21:38 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:21:38 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) INFO 06-14 04:21:44 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 327.3 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 31.9%, Prefix cache hit rate: 94.0% [repeated 46x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) INFO 06-14 04:21:49 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 324.8 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 32.3%, Prefix cache hit rate: 94.0% [repeated 46x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) INFO 06-14 04:21:54 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 324.4 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 32.8%, Prefix cache hit rate: 94.0% [repeated 46x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:21:58] OK: 317 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:21:58] OK: RSS 1.87 GiB | node mem 260.0/858.0 GiB used (30.3%), avail 597.9 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 7x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:21:59 [loggers.py:259] Engine 000: Avg prompt throughput: 150.3 tokens/s, Avg generation throughput: 92.6 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.8%, Prefix cache hit rate: 94.9% [repeated 47x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 13x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:22:04 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 131.9 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.9%, Prefix cache hit rate: 94.9% [repeated 46x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:07 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:07 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:07 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:07 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:07 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:07 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:07 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:07 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:07 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:07 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:07 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:07 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:07 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:07 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:07 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:07 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:07 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:07 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:22:09 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 132.1 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.1%, Prefix cache hit rate: 94.9% [repeated 45x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:13 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:13 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:13 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:13 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:13 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:13 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:13 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:13 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:13 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:13 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:22:13 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:22:14 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 131.9 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.3%, Prefix cache hit rate: 94.9% [repeated 47x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:22:19 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 131.8 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.5%, Prefix cache hit rate: 94.9% [repeated 47x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:22:19 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:22:19 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:22:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:22:19 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:22:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:22:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:22:19 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:22:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:22:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:22:19 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:22:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:22:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:22:19 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:22:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:22:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:22:19 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:22:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:22:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:22:19 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:22:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:22:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:22:19 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:22:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:22:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:22:19 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:22:19 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:22:24 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 132.1 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.7%, Prefix cache hit rate: 94.9% [repeated 47x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:22:27 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:22:27 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:22:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:22:27 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:22:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:22:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:22:27 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:22:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:22:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:22:27 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:22:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:22:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:22:27 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:22:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:22:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:22:27 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:22:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:22:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:22:27 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:22:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:22:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:22:27 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:22:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:22:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:22:27 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:22:27 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:22:29 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 132.1 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.9%, Prefix cache hit rate: 94.9% [repeated 48x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:22:34 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 132.0 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.0%, Prefix cache hit rate: 94.9% [repeated 48x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:22:39 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 131.9 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.2%, Prefix cache hit rate: 94.9% [repeated 48x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 13x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:22:44 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 132.0 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.4%, Prefix cache hit rate: 94.9% [repeated 48x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:22:49 [loggers.py:259] Engine 000: Avg prompt throughput: 276.5 tokens/s, Avg generation throughput: 114.5 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.0%, Prefix cache hit rate: 94.7% [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:22:54 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 132.0 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.1%, Prefix cache hit rate: 94.7% [repeated 46x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:22:59 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 132.2 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.3%, Prefix cache hit rate: 94.7% [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:23:00 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:23:00 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:23:00 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:23:00 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:23:00 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:23:00 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:23:00 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:23:00 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:23:00 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:23:00 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:23:00 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:23:00 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:23:00 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:23:00 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:23:00 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:23:00 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:23:00 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:23:00 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:23:00 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:23:00 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:23:00 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:23:00 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:23:00 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:23:00 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:23:00 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:23:00 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:23:04 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 132.0 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.5%, Prefix cache hit rate: 94.7% [repeated 46x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:23:04 [serving.py:315] Error in preprocessing prompt inputs [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:23:04 [serving.py:315] Traceback (most recent call last): [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:23:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:23:04 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:23:04 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:23:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:23:04 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:23:04 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:23:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:23:04 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:23:04 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:23:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:23:04 [serving.py:315] return await asyncio.gather( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:23:04 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:23:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:23:04 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:23:04 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:23:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:23:04 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:23:04 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:23:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:23:04 [serving.py:315] tokens = validator(tokenizer, tokens) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:23:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:23:04 [serving.py:315] raise VLLMValidationError( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:23:04 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) [repeated 2x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new [repeated 2x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. [repeated 2x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:23:09 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 131.9 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.7%, Prefix cache hit rate: 94.7% [repeated 46x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:23:13] OK: 162 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:23:13] OK: RSS 1.51 GiB | node mem 399.3/858.0 GiB used (46.5%), avail 458.7 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) INFO 06-14 04:23:14 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 131.1 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.9%, Prefix cache hit rate: 94.7% [repeated 46x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) INFO 06-14 04:23:19 [loggers.py:259] Engine 000: Avg prompt throughput: 77.2 tokens/s, Avg generation throughput: 63.1 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.1%, Prefix cache hit rate: 96.0% [repeated 47x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:23:21] OK: 152 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:23:21] OK: RSS 1.86 GiB | node mem 387.1/858.0 GiB used (45.1%), avail 470.9 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 8x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) INFO 06-14 04:23:25 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 42.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.0%, Prefix cache hit rate: 95.0% [repeated 47x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 7x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:23:29] OK: 185 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:23:29] OK: RSS 1.28 GiB | node mem 393.1/858.0 GiB used (45.8%), avail 464.9 GiB +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) INFO 06-14 04:23:30 [loggers.py:259] Engine 000: Avg prompt throughput: 137.8 tokens/s, Avg generation throughput: 22.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.2%, Prefix cache hit rate: 95.3% [repeated 46x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:23:34 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:23:34 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:23:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:23:34 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:23:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:23:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:23:34 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:23:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:23:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:23:34 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:23:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:23:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:23:34 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:23:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:23:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:23:34 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:23:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:23:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:23:34 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:23:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:23:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:23:34 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:23:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:23:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:23:34 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:23:34 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) INFO 06-14 04:23:35 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 127.1 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.0%, Prefix cache hit rate: 97.0% [repeated 47x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 10x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:23:38] OK: 133 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:23:38] OK: RSS 1.90 GiB | node mem 383.4/858.0 GiB used (44.7%), avail 474.6 GiB +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) INFO 06-14 04:23:40 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 125.8 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.2%, Prefix cache hit rate: 97.0% [repeated 46x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) INFO 06-14 04:23:45 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 131.3 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.4%, Prefix cache hit rate: 97.0% [repeated 46x across cluster] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:23:46 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:23:46 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:23:46 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:23:46 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:23:46 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:23:46 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:23:46 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:23:46 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:23:46 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:23:46 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:23:46 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:23:46 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:23:46 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:23:46 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:23:46 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:23:46 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:23:46 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:23:46 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:23:46 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:23:46 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:23:46 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:23:46 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:23:46 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:23:46 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:23:46 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:23:46 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) INFO 06-14 04:23:50 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 125.1 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.5%, Prefix cache hit rate: 97.0% [repeated 46x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) INFO 06-14 04:23:55 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 126.2 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.7%, Prefix cache hit rate: 97.0% [repeated 46x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:23:58] OK: 319 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:23:58] OK: RSS 1.88 GiB | node mem 260.0/858.0 GiB used (30.3%), avail 597.9 GiB +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) INFO 06-14 04:24:00 [loggers.py:259] Engine 000: Avg prompt throughput: 162.7 tokens/s, Avg generation throughput: 97.5 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.1%, Prefix cache hit rate: 96.9% [repeated 46x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 7x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) INFO 06-14 04:24:05 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 124.2 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.3%, Prefix cache hit rate: 96.9% [repeated 46x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 18x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) INFO 06-14 04:24:10 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 125.8 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.4%, Prefix cache hit rate: 96.9% [repeated 45x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) INFO 06-14 04:24:15 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 100.8 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.0%, Prefix cache hit rate: 94.4% [repeated 47x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:24:16 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:24:16 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:24:16 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:24:16 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:24:16 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:24:16 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:24:16 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:24:16 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:24:16 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:24:16 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:24:16 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:24:16 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:24:16 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:24:16 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:24:16 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:24:16 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:24:16 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:24:16 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:24:16 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:24:16 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:24:16 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:24:16 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:24:16 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:24:16 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:24:16 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:24:16 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) INFO 06-14 04:24:20 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 127.7 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.9%, Prefix cache hit rate: 96.9% [repeated 45x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:24:20 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:24:20 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:24:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:24:20 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:24:20 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:24:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:24:20 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:24:20 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:24:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:24:20 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:24:20 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:24:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:24:20 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:24:20 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:24:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:24:20 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:24:20 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:24:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:24:20 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:24:20 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:24:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:24:20 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:24:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:24:20 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:24:20 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:24:22 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:24:22 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:24:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:24:22 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:24:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:24:22 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:24:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:24:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:24:22 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:24:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:24:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:24:22 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:24:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:24:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:24:22 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:24:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:24:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:24:22 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:24:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:24:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:24:22 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:24:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:24:22 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:24:22 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) INFO 06-14 04:24:25 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 125.4 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.1%, Prefix cache hit rate: 96.9% [repeated 47x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new [repeated 3x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:24:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:24:26 [serving.py:315] Error in preprocessing prompt inputs [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:24:26 [serving.py:315] Traceback (most recent call last): [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:24:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:24:26 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:24:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:24:26 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:24:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:24:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:24:26 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:24:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:24:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:24:26 [serving.py:315] return await asyncio.gather( [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:24:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:24:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:24:26 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:24:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:24:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:24:26 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:24:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:24:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:24:26 [serving.py:315] tokens = validator(tokenizer, tokens) [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:24:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:24:26 [serving.py:315] raise VLLMValidationError( [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:24:26 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) [repeated 3x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) INFO 06-14 04:24:30 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 124.5 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.2%, Prefix cache hit rate: 96.9% [repeated 47x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:24:29 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:24:29 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:24:29 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:24:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:24:29 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:24:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:24:29 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:24:29 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:24:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:24:29 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:24:29 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:24:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:24:29 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:24:29 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:24:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:24:29 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:24:29 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:24:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:24:29 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:24:29 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:24:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:24:29 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:24:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:24:29 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:24:29 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) ERROR 06-14 04:24:35 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) ERROR 06-14 04:24:35 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) ERROR 06-14 04:24:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) ERROR 06-14 04:24:35 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) ERROR 06-14 04:24:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) ERROR 06-14 04:24:35 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) ERROR 06-14 04:24:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) ERROR 06-14 04:24:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) ERROR 06-14 04:24:35 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) ERROR 06-14 04:24:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) ERROR 06-14 04:24:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) ERROR 06-14 04:24:35 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) ERROR 06-14 04:24:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) ERROR 06-14 04:24:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) ERROR 06-14 04:24:35 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) ERROR 06-14 04:24:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) ERROR 06-14 04:24:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) ERROR 06-14 04:24:35 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) ERROR 06-14 04:24:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) ERROR 06-14 04:24:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) ERROR 06-14 04:24:35 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) ERROR 06-14 04:24:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) ERROR 06-14 04:24:35 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) ERROR 06-14 04:24:35 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) INFO 06-14 04:24:35 [loggers.py:259] Engine 000: Avg prompt throughput: 118.8 tokens/s, Avg generation throughput: 92.5 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.5%, Prefix cache hit rate: 96.8% [repeated 47x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) ERROR 06-14 04:24:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:24:40 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:24:40 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:24:40 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:24:40 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:24:40 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:24:40 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:24:40 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:24:40 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:24:40 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:24:40 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:24:40 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:24:40 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:24:40 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:24:40 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:24:40 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:24:40 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:24:40 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:24:40 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:24:40 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:24:40 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:24:40 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:24:40 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:24:40 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:24:40 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) INFO 06-14 04:24:40 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 121.4 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.7%, Prefix cache hit rate: 96.8% [repeated 45x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 7x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:24:40 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) INFO 06-14 04:24:45 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 121.0 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.9%, Prefix cache hit rate: 96.8% [repeated 46x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) INFO 06-14 04:24:50 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 122.9 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.0%, Prefix cache hit rate: 96.8% [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) INFO 06-14 04:24:55 [loggers.py:259] Engine 000: Avg prompt throughput: 14.2 tokens/s, Avg generation throughput: 118.8 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.2%, Prefix cache hit rate: 96.9% [repeated 46x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:25:00 [loggers.py:259] Engine 000: Avg prompt throughput: 142.7 tokens/s, Avg generation throughput: 181.8 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 17.5%, Prefix cache hit rate: 96.4% [repeated 48x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:25:05 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 205.7 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 17.8%, Prefix cache hit rate: 96.4% [repeated 45x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:25:10 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 208.9 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 18.1%, Prefix cache hit rate: 96.4% [repeated 45x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:25:13] OK: 148 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:25:13] OK: RSS 1.70 GiB | node mem 399.4/858.0 GiB used (46.6%), avail 458.5 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:25:15 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 202.9 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 18.4%, Prefix cache hit rate: 96.4% [repeated 45x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:25:20 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 202.3 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 18.7%, Prefix cache hit rate: 96.4% [repeated 45x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:25:21] OK: 158 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:25:21] OK: RSS 1.88 GiB | node mem 387.2/858.0 GiB used (45.1%), avail 470.8 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:25:25 [loggers.py:259] Engine 000: Avg prompt throughput: 153.4 tokens/s, Avg generation throughput: 176.2 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.6%, Prefix cache hit rate: 96.3% [repeated 45x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 18x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:25:29] OK: 178 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:25:29] OK: RSS 1.44 GiB | node mem 393.2/858.0 GiB used (45.8%), avail 464.8 GiB +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:25:30 [loggers.py:259] Engine 000: Avg prompt throughput: 93.1 tokens/s, Avg generation throughput: 149.8 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.9%, Prefix cache hit rate: 96.3% [repeated 45x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 7x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:25:35 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:25:35 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:25:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:25:35 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:25:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:25:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:25:35 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:25:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:25:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:25:35 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:25:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:25:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:25:35 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:25:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:25:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:25:35 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:25:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:25:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:25:35 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:25:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:25:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:25:35 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:25:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:25:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:25:35 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:25:35 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:25:35 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 161.6 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.1%, Prefix cache hit rate: 96.3% [repeated 45x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:25:38] OK: 129 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:25:38] OK: RSS 1.93 GiB | node mem 383.5/858.0 GiB used (44.7%), avail 474.4 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:25:40 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 163.8 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.3%, Prefix cache hit rate: 96.3% [repeated 45x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 15x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:25:45 [loggers.py:259] Engine 000: Avg prompt throughput: 68.8 tokens/s, Avg generation throughput: 172.2 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.8%, Prefix cache hit rate: 96.3% [repeated 45x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:25:50 [loggers.py:259] Engine 000: Avg prompt throughput: 8.8 tokens/s, Avg generation throughput: 196.6 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.0%, Prefix cache hit rate: 96.3% [repeated 46x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:25:54 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:25:54 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:25:54 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:25:54 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:25:54 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:25:54 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:25:54 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:25:54 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:25:54 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:25:54 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:25:54 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:25:54 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:25:54 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:25:54 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:25:54 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:25:54 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:25:54 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:25:54 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:25:54 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:25:54 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:25:54 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:25:54 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:25:54 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:25:54 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:25:54 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:25:54 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:25:55 [loggers.py:259] Engine 000: Avg prompt throughput: 34.0 tokens/s, Avg generation throughput: 243.0 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.6%, Prefix cache hit rate: 96.3% [repeated 47x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:25:58] OK: 310 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:25:58] OK: RSS 1.88 GiB | node mem 260.1/858.0 GiB used (30.3%), avail 597.9 GiB +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:25:56 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:25:56 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:25:56 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:25:56 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:25:56 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:25:56 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:25:56 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:25:56 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:25:56 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:25:56 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:25:56 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:25:56 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:25:56 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:25:56 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:25:56 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:25:56 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:25:56 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:25:56 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:25:56 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:25:56 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:25:56 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:25:56 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:25:56 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:25:56 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:25:56 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:26:00 [loggers.py:259] Engine 000: Avg prompt throughput: 144.8 tokens/s, Avg generation throughput: 216.0 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.1%, Prefix cache hit rate: 96.3% [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:26:05 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 240.6 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.2%, Prefix cache hit rate: 96.3% [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:26:10 [loggers.py:259] Engine 000: Avg prompt throughput: 67.2 tokens/s, Avg generation throughput: 230.2 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.8%, Prefix cache hit rate: 96.2% [repeated 47x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:26:15 [loggers.py:259] Engine 000: Avg prompt throughput: 98.5 tokens/s, Avg generation throughput: 224.6 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.3%, Prefix cache hit rate: 96.2% [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:26:20 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 241.7 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.6%, Prefix cache hit rate: 96.2% [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:26:25 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 224.6 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.3%, Prefix cache hit rate: 96.2% [repeated 47x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:26:30 [loggers.py:259] Engine 000: Avg prompt throughput: 129.5 tokens/s, Avg generation throughput: 234.3 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 15.4%, Prefix cache hit rate: 96.2% [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:26:35 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 243.1 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 15.7%, Prefix cache hit rate: 96.2% [repeated 47x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:26:40 [loggers.py:259] Engine 000: Avg prompt throughput: 10.8 tokens/s, Avg generation throughput: 273.2 tokens/s, Running: 7 reqs, Waiting: 0 reqs, GPU KV cache usage: 16.2%, Prefix cache hit rate: 96.2% [repeated 47x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) INFO 06-14 04:26:46 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 94.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.7%, Prefix cache hit rate: 95.1% [repeated 47x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:26:48 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:26:48 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:26:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:26:48 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:26:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:26:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:26:48 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:26:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:26:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:26:48 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:26:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:26:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:26:48 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:26:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:26:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:26:48 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:26:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:26:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:26:48 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:26:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:26:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:26:48 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:26:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:26:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:26:48 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:26:48 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=3946333, ip=10.128.56.73) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) INFO 06-14 04:26:51 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 94.1 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.8%, Prefix cache hit rate: 95.1% [repeated 46x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) INFO 06-14 04:26:56 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 94.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.0%, Prefix cache hit rate: 95.1% [repeated 46x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:26:57 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:26:57 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:26:57 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:26:57 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:26:57 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:26:57 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:26:57 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:26:57 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:26:57 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:26:57 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:26:57 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:26:57 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:26:57 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:26:57 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:26:57 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:26:57 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:26:57 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:26:57 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:26:57 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:26:57 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:26:57 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:26:57 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:26:57 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:26:57 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:26:57 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:26:57 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) INFO 06-14 04:27:01 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 94.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.1%, Prefix cache hit rate: 95.1% [repeated 46x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new [repeated 2x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:27:01 [serving.py:315] Error in preprocessing prompt inputs [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:27:01 [serving.py:315] Traceback (most recent call last): [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:27:01 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:27:01 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:27:01 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:27:01 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:27:01 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:27:01 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:27:01 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:27:01 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:27:01 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:27:01 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:27:01 [serving.py:315] return await asyncio.gather( [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:27:01 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:27:01 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:27:01 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:27:01 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:27:01 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:27:01 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:27:01 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:27:01 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:27:01 [serving.py:315] tokens = validator(tokenizer, tokens) [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:27:01 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:27:01 [serving.py:315] raise VLLMValidationError( [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:27:01 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) [repeated 3x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:27:06 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 79.5 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.8%, Prefix cache hit rate: 95.6% [repeated 46x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:04 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:04 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:04 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:04 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:04 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:04 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:04 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:04 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:04 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:04 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:04 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:04 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:04 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:04 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:04 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:04 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:04 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:08 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:08 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:08 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:08 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:08 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:08 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:08 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:08 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:08 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:08 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:08 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:08 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:08 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:08 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:08 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:08 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) INFO 06-14 04:27:11 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 137.8 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.6%, Prefix cache hit rate: 95.2% [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:08 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:27:13] OK: 164 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:27:13] OK: RSS 1.75 GiB | node mem 399.6/858.0 GiB used (46.6%), avail 458.4 GiB +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) INFO 06-14 04:27:16 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 137.9 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.8%, Prefix cache hit rate: 95.2% [repeated 46x across cluster] +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) INFO 06-14 04:27:21 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 138.3 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.0%, Prefix cache hit rate: 95.2% [repeated 45x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:27:21] OK: 153 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:27:21] OK: RSS 1.92 GiB | node mem 387.2/858.0 GiB used (45.1%), avail 470.7 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) INFO 06-14 04:27:26 [loggers.py:259] Engine 000: Avg prompt throughput: 159.4 tokens/s, Avg generation throughput: 95.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.8%, Prefix cache hit rate: 95.1% [repeated 46x across cluster] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:27:27 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:27:27 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:27:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:27:27 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:27:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:27:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:27:27 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:27:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:27:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:27:27 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:27:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:27:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:27:27 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:27:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:27:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:27:27 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:27:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:27:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:27:27 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:27:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:27:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:27:27 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:27:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:27:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:27:27 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:27:27 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:27:29] OK: 151 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:27:29] OK: RSS 1.66 GiB | node mem 393.5/858.0 GiB used (45.9%), avail 464.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) INFO 06-14 04:27:31 [loggers.py:259] Engine 000: Avg prompt throughput: 115.3 tokens/s, Avg generation throughput: 107.3 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.7%, Prefix cache hit rate: 95.8% [repeated 47x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:27:30 [serving.py:315] Error in preprocessing prompt inputs [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:27:30 [serving.py:315] Traceback (most recent call last): [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:27:30 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:27:30 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:27:30 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:27:30 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:27:30 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:27:30 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:27:30 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:27:30 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:27:30 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:27:30 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:27:30 [serving.py:315] return await asyncio.gather( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:27:30 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:27:30 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:27:30 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:27:30 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:27:30 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:27:30 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:27:30 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:27:30 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:27:30 [serving.py:315] tokens = validator(tokenizer, tokens) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:27:30 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:27:30 [serving.py:315] raise VLLMValidationError( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:27:30 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) [repeated 2x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new [repeated 2x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. [repeated 2x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) INFO 06-14 04:27:36 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 100.1 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.8%, Prefix cache hit rate: 95.8% [repeated 46x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:27:36 [serving.py:315] Error in preprocessing prompt inputs [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:27:36 [serving.py:315] Traceback (most recent call last): [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:27:36 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:27:36 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:27:36 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:27:36 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:27:36 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:27:36 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:27:36 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:27:36 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:27:36 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:27:36 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:27:36 [serving.py:315] return await asyncio.gather( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:27:36 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:27:36 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:27:36 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:27:36 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:27:36 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:27:36 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:27:36 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:27:36 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:27:36 [serving.py:315] tokens = validator(tokenizer, tokens) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:27:36 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:27:36 [serving.py:315] raise VLLMValidationError( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:27:36 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) [repeated 2x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new [repeated 2x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. [repeated 2x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:27:38] OK: 113 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:27:38] OK: RSS 1.96 GiB | node mem 383.5/858.0 GiB used (44.7%), avail 474.4 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) INFO 06-14 04:27:41 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 100.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.0%, Prefix cache hit rate: 95.8% [repeated 46x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:39 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:39 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:39 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:39 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:39 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:39 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:39 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:39 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:39 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:39 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:39 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:39 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:39 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:39 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:39 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:39 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:27:39 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) INFO 06-14 04:27:46 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 100.1 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.1%, Prefix cache hit rate: 95.8% [repeated 46x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 10x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:27:50 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:27:50 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:27:50 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:27:50 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:27:50 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:27:50 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:27:50 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:27:50 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:27:50 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:27:50 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:27:50 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:27:50 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:27:50 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:27:50 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:27:50 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:27:50 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:27:50 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:27:50 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:27:50 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:27:50 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:27:50 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:27:50 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:27:50 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:27:50 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:27:50 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:27:50 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) INFO 06-14 04:27:51 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 100.3 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.3%, Prefix cache hit rate: 95.8% [repeated 45x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) INFO 06-14 04:27:56 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 99.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.4%, Prefix cache hit rate: 95.8% [repeated 46x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:27:58] OK: 287 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:27:58] OK: RSS 1.89 GiB | node mem 260.1/858.0 GiB used (30.3%), avail 597.8 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) INFO 06-14 04:28:01 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 285.5 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 30.6%, Prefix cache hit rate: 95.5% [repeated 47x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 13x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) INFO 06-14 04:28:06 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 286.1 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 31.0%, Prefix cache hit rate: 95.5% [repeated 48x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:28:06 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:28:06 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:28:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:28:06 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:28:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:28:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:28:06 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:28:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:28:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:28:06 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:28:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:28:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:28:06 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:28:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:28:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:28:06 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:28:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:28:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:28:06 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:28:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:28:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:28:06 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:28:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:28:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:28:06 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:28:06 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 10x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) INFO 06-14 04:28:11 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 284.4 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 31.4%, Prefix cache hit rate: 95.5% [repeated 47x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new [repeated 2x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:07 [serving.py:315] Error in preprocessing prompt inputs [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:07 [serving.py:315] Traceback (most recent call last): [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:07 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:07 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:07 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:07 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:07 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:07 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:07 [serving.py:315] return await asyncio.gather( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:07 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:07 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:07 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:07 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:07 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:07 [serving.py:315] tokens = validator(tokenizer, tokens) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:07 [serving.py:315] raise VLLMValidationError( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:07 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) [repeated 2x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) INFO 06-14 04:28:16 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 284.5 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 31.8%, Prefix cache hit rate: 95.5% [repeated 46x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:28:13 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:28:13 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:28:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:28:13 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:28:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:28:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:28:13 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:28:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:28:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:28:13 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:28:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:28:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:28:13 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:28:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:28:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:28:13 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:28:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:28:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:28:13 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:28:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:28:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:28:13 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:28:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:28:13 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:28:13 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:28:20 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:28:20 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:28:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:28:20 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:28:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:28:20 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:28:20 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:28:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:28:20 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:28:20 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:28:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:28:20 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:28:20 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:28:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:28:20 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:28:20 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:28:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:28:20 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:28:20 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:28:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:28:20 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:28:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:28:20 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:28:20 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) INFO 06-14 04:28:21 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 242.5 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 18.9%, Prefix cache hit rate: 95.5% [repeated 46x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:28:20 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 4x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:28:23 [serving.py:315] Error in preprocessing prompt inputs [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:28:23 [serving.py:315] Traceback (most recent call last): [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:28:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:28:23 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:28:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:28:23 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:28:23 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:28:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:28:23 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:28:23 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:28:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:28:23 [serving.py:315] return await asyncio.gather( [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:28:23 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:28:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:28:23 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:28:23 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:28:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:28:23 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:28:23 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:28:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:28:23 [serving.py:315] tokens = validator(tokenizer, tokens) [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:28:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:28:23 [serving.py:315] raise VLLMValidationError( [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:28:23 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) [repeated 3x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new [repeated 3x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) INFO 06-14 04:28:26 [loggers.py:259] Engine 000: Avg prompt throughput: 186.6 tokens/s, Avg generation throughput: 227.9 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 24.1%, Prefix cache hit rate: 95.5% [repeated 46x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:28:23 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 4x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:28:27 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:28:27 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:28:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:28:27 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:28:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:28:27 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:28:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:28:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:28:27 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:28:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:28:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:28:27 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:28:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:28:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:28:27 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:28:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:28:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:28:27 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:28:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:28:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:28:27 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:28:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:28:27 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:28:27 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=3946333, ip=10.128.56.73) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) INFO 06-14 04:28:31 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 239.6 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 24.4%, Prefix cache hit rate: 95.5% [repeated 46x across cluster] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:28:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:32 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:32 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:32 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:32 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:32 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:32 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:32 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:32 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:32 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:32 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:28:32 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) INFO 06-14 04:28:36 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 223.9 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 15.8%, Prefix cache hit rate: 95.5% [repeated 44x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:28:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:28:37 [serving.py:315] Error in preprocessing prompt inputs [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:28:37 [serving.py:315] Traceback (most recent call last): [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:28:37 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:28:37 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:28:37 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:28:37 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:28:37 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:28:37 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:28:37 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:28:37 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:28:37 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:28:37 [serving.py:315] return await asyncio.gather( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:28:37 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:28:37 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:28:37 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:28:37 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:28:37 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:28:37 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:28:37 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:28:37 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:28:37 [serving.py:315] tokens = validator(tokenizer, tokens) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:28:37 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:28:37 [serving.py:315] raise VLLMValidationError( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:28:37 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) [repeated 2x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 3x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) INFO 06-14 04:28:41 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 187.4 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 16.1%, Prefix cache hit rate: 95.5% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:28:37 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 10x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) INFO 06-14 04:28:46 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 185.5 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 23.1%, Prefix cache hit rate: 95.9% [repeated 44x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 7x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:28:51 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:28:51 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:28:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:28:51 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:28:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:28:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:28:51 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:28:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:28:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:28:51 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:28:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:28:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:28:51 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:28:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:28:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:28:51 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:28:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:28:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:28:51 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:28:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:28:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:28:51 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:28:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:28:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:28:51 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) ERROR 06-14 04:28:51 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) INFO 06-14 04:28:51 [loggers.py:259] Engine 000: Avg prompt throughput: 45.6 tokens/s, Avg generation throughput: 164.5 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 18.5%, Prefix cache hit rate: 90.9% [repeated 46x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) INFO 06-14 04:28:56 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 178.0 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 18.7%, Prefix cache hit rate: 90.9% [repeated 45x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 3x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) INFO 06-14 04:29:01 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 178.2 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 18.9%, Prefix cache hit rate: 90.9% [repeated 45x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 13x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:29:04 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:29:04 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:29:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:29:04 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:29:04 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:29:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:29:04 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:29:04 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:29:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:29:04 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:29:04 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:29:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:29:04 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:29:04 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:29:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:29:04 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:29:04 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:29:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:29:04 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:29:04 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:29:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:29:04 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:29:04 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:29:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:29:04 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:29:04 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) INFO 06-14 04:29:06 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 177.3 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 19.2%, Prefix cache hit rate: 90.9% [repeated 45x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) INFO 06-14 04:29:11 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 146.0 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.5%, Prefix cache hit rate: 90.9% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:29:13 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:29:13 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:29:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:29:13 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:29:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:29:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:29:13 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:29:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:29:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:29:13 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:29:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:29:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:29:13 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:29:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:29:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:29:13 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:29:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:29:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:29:13 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:29:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:29:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:29:13 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:29:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:29:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:29:13 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:29:13 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:29:14] OK: 148 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:29:14] OK: RSS 1.87 GiB | node mem 399.7/858.0 GiB used (46.6%), avail 458.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) INFO 06-14 04:29:16 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 133.9 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.7%, Prefix cache hit rate: 90.9% [repeated 42x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:29:17 [serving.py:315] Error in preprocessing prompt inputs [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:29:17 [serving.py:315] Traceback (most recent call last): [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:29:17 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:29:17 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:29:17 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:29:17 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:29:17 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:29:17 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:29:17 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:29:17 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:29:17 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:29:17 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:29:17 [serving.py:315] return await asyncio.gather( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:29:17 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:29:17 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:29:17 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:29:17 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:29:17 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:29:17 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:29:17 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:29:17 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:29:17 [serving.py:315] tokens = validator(tokenizer, tokens) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:29:17 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:29:17 [serving.py:315] raise VLLMValidationError( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:29:17 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) [repeated 2x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new [repeated 2x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. [repeated 2x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 10x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:29:21] OK: 145 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:29:21] OK: RSS 1.95 GiB | node mem 387.3/858.0 GiB used (45.1%), avail 470.6 GiB +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) INFO 06-14 04:29:21 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 134.8 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.9%, Prefix cache hit rate: 90.9% [repeated 44x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:29:22 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:29:22 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:29:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:29:22 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:29:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:29:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:29:22 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:29:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:29:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:29:22 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:29:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:29:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:29:22 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:29:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:29:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:29:22 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:29:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:29:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:29:22 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:29:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:29:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:29:22 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:29:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:29:22 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:29:22 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 10x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) INFO 06-14 04:29:26 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 135.2 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.1%, Prefix cache hit rate: 90.9% [repeated 42x across cluster] +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:28 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:28 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:28 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:28 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:28 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:28 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:28 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:28 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:28 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:28 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:28 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:28 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:28 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:28 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:28 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:28 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=3946333, ip=10.128.56.73) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:28 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 10x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:29:29] OK: 147 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:29:29] OK: RSS 1.82 GiB | node mem 393.6/858.0 GiB used (45.9%), avail 464.3 GiB +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) INFO 06-14 04:29:31 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 134.9 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.2%, Prefix cache hit rate: 90.9% [repeated 42x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 11x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) INFO 06-14 04:29:36 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 134.6 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.4%, Prefix cache hit rate: 90.9% [repeated 41x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:37 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:37 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:37 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:37 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:37 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:37 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:37 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:37 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:37 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:37 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:37 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:37 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:37 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:37 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:37 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:37 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:37 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:37 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:37 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:37 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:37 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:37 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:37 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:37 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:37 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:29:37 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:29:38] OK: 118 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:29:38] OK: RSS 1.93 GiB | node mem 383.6/858.0 GiB used (44.7%), avail 474.4 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 31x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) INFO 06-14 04:29:41 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 134.3 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.6%, Prefix cache hit rate: 90.9% [repeated 41x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 12x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) INFO 06-14 04:29:47 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 100.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.1%, Prefix cache hit rate: 95.2% [repeated 42x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:29:49 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:29:49 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:29:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:29:49 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:29:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:29:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:29:49 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:29:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:29:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:29:49 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:29:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:29:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:29:49 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:29:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:29:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:29:49 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:29:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:29:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:29:49 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:29:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:29:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:29:49 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:29:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:29:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:29:49 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:29:49 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) INFO 06-14 04:29:52 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 100.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.2%, Prefix cache hit rate: 95.2% [repeated 42x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) INFO 06-14 04:29:57 [loggers.py:259] Engine 000: Avg prompt throughput: 90.4 tokens/s, Avg generation throughput: 79.8 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.4%, Prefix cache hit rate: 95.2% [repeated 43x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:29:58] OK: 284 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:29:58] OK: RSS 1.89 GiB | node mem 260.2/858.0 GiB used (30.3%), avail 597.8 GiB +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) INFO 06-14 04:30:02 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 100.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.6%, Prefix cache hit rate: 95.2% [repeated 44x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) INFO 06-14 04:30:07 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 100.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.7%, Prefix cache hit rate: 95.2% [repeated 44x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 8x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) INFO 06-14 04:30:12 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 92.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.8%, Prefix cache hit rate: 95.2% [repeated 43x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:30:15 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:30:15 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:30:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:30:15 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:30:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:30:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:30:15 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:30:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:30:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:30:15 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:30:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:30:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:30:15 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:30:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:30:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:30:15 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:30:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:30:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:30:15 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:30:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:30:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:30:15 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:30:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:30:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:30:15 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:30:15 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) INFO 06-14 04:30:17 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 44.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.6%, Prefix cache hit rate: 94.5% [repeated 45x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) INFO 06-14 04:30:22 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 44.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.7%, Prefix cache hit rate: 94.5% [repeated 44x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 21x across cluster] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) INFO 06-14 04:30:27 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 44.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.8%, Prefix cache hit rate: 94.5% [repeated 44x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 12x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:30:32 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:30:32 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:30:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:30:32 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:30:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:30:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:30:32 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:30:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:30:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:30:32 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:30:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:30:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:30:32 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:30:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:30:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:30:32 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:30:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:30:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:30:32 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:30:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:30:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:30:32 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:30:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:30:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:30:32 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:30:32 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) INFO 06-14 04:30:32 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 44.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.8%, Prefix cache hit rate: 94.5% [repeated 44x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 7x across cluster] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) INFO 06-14 04:30:37 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 208.7 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.7%, Prefix cache hit rate: 95.4% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:30:41 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:30:41 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:30:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:30:41 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:30:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:30:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:30:41 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:30:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:30:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:30:41 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:30:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:30:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:30:41 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:30:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:30:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:30:41 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:30:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:30:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:30:41 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:30:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:30:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:30:41 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:30:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:30:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:30:41 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:30:41 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) INFO 06-14 04:30:42 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 209.7 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.0%, Prefix cache hit rate: 95.4% [repeated 44x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) INFO 06-14 04:30:47 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 209.4 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.3%, Prefix cache hit rate: 95.4% [repeated 44x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) INFO 06-14 04:30:52 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 201.6 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.1%, Prefix cache hit rate: 95.4% [repeated 44x across cluster] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) INFO 06-14 04:30:57 [loggers.py:259] Engine 000: Avg prompt throughput: 291.6 tokens/s, Avg generation throughput: 175.9 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.2%, Prefix cache hit rate: 95.3% [repeated 44x across cluster] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) INFO 06-14 04:31:02 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 208.7 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.5%, Prefix cache hit rate: 95.3% [repeated 44x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:31:04 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:31:04 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:31:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:31:04 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:31:04 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:31:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:31:04 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:31:04 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:31:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:31:04 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:31:04 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:31:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:31:04 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:31:04 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:31:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:31:04 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:31:04 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:31:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:31:04 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:31:04 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:31:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:31:04 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:31:04 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:31:04 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:31:04 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:31:04 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) INFO 06-14 04:31:07 [loggers.py:259] Engine 000: Avg prompt throughput: 146.5 tokens/s, Avg generation throughput: 185.9 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.0%, Prefix cache hit rate: 95.3% [repeated 44x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:31:08 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:31:08 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:31:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:31:08 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:31:08 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:31:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:31:08 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:31:08 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:31:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:31:08 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:31:08 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:31:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:31:08 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:31:08 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:31:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:31:08 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:31:08 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:31:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:31:08 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:31:08 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:31:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:31:08 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:31:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:31:08 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:31:08 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 04:31:12 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 153.1 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 17.4%, Prefix cache hit rate: 96.2% [repeated 43x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:31:14] OK: 147 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:31:14] OK: RSS 1.92 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.2 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 04:31:17 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 162.2 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 17.6%, Prefix cache hit rate: 96.2% [repeated 44x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:31:21] OK: 151 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:31:21] OK: RSS 1.96 GiB | node mem 387.4/858.0 GiB used (45.2%), avail 470.5 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:31:22 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:31:22 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:31:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:31:22 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:31:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:31:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:31:22 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:31:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:31:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:31:22 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:31:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:31:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:31:22 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:31:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:31:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:31:22 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:31:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:31:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:31:22 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:31:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:31:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:31:22 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:31:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:31:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:31:22 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:31:22 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 04:31:22 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 151.6 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 17.8%, Prefix cache hit rate: 96.2% [repeated 44x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=3946333, ip=10.128.56.73) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:31:23 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:31:23 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:31:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:31:23 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:31:23 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:31:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:31:23 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:31:23 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:31:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:31:23 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:31:23 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:31:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:31:23 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:31:23 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:31:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:31:23 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:31:23 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:31:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:31:23 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:31:23 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:31:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:31:23 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:31:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:31:23 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:31:23 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 04:31:27 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 153.5 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 18.1%, Prefix cache hit rate: 96.2% [repeated 43x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:31:29] OK: 164 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:31:29] OK: RSS 1.84 GiB | node mem 393.6/858.0 GiB used (45.9%), avail 464.3 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 04:31:32 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 150.9 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 18.3%, Prefix cache hit rate: 96.2% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 04:31:37 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 151.6 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 18.5%, Prefix cache hit rate: 96.2% [repeated 46x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:31:38] OK: 122 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:31:38] OK: RSS 1.93 GiB | node mem 383.6/858.0 GiB used (44.7%), avail 474.4 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 04:31:42 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 151.8 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 18.7%, Prefix cache hit rate: 96.2% [repeated 46x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:31:44 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:31:44 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:31:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:31:44 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:31:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:31:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:31:44 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:31:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:31:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:31:44 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:31:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:31:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:31:44 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:31:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:31:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:31:44 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:31:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:31:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:31:44 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:31:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:31:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:31:44 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:31:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:31:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:31:44 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:31:44 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) INFO 06-14 04:31:47 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 231.2 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 31.9%, Prefix cache hit rate: 95.3% [repeated 47x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:31:51 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:31:51 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:31:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:31:51 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:31:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:31:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:31:51 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:31:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:31:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:31:51 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:31:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:31:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:31:51 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:31:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:31:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:31:51 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:31:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:31:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:31:51 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:31:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:31:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:31:51 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:31:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:31:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:31:51 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:31:51 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) INFO 06-14 04:31:52 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 229.0 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 32.2%, Prefix cache hit rate: 95.3% [repeated 46x across cluster] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) INFO 06-14 04:31:57 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 230.5 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 32.5%, Prefix cache hit rate: 95.3% [repeated 46x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:31:58] OK: 289 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:31:58] OK: RSS 1.89 GiB | node mem 260.2/858.0 GiB used (30.3%), avail 597.7 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) INFO 06-14 04:32:02 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 231.0 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 32.8%, Prefix cache hit rate: 95.3% [repeated 47x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 3x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) INFO 06-14 04:32:07 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 231.3 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 33.2%, Prefix cache hit rate: 95.3% [repeated 47x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) INFO 06-14 04:32:12 [loggers.py:259] Engine 000: Avg prompt throughput: 11.6 tokens/s, Avg generation throughput: 260.5 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 33.6%, Prefix cache hit rate: 95.3% [repeated 46x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) INFO 06-14 04:32:17 [loggers.py:259] Engine 000: Avg prompt throughput: 125.9 tokens/s, Avg generation throughput: 229.9 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 33.9%, Prefix cache hit rate: 95.3% [repeated 46x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:32:19 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:32:19 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:32:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:32:19 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:32:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:32:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:32:19 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:32:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:32:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:32:19 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:32:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:32:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:32:19 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:32:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:32:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:32:19 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:32:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:32:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:32:19 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:32:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:32:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:32:19 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:32:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:32:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:32:19 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:32:19 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) INFO 06-14 04:32:22 [loggers.py:259] Engine 000: Avg prompt throughput: 28.8 tokens/s, Avg generation throughput: 263.9 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 26.9%, Prefix cache hit rate: 95.3% [repeated 46x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) INFO 06-14 04:32:28 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 116.9 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.6%, Prefix cache hit rate: 95.1% [repeated 47x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) INFO 06-14 04:32:33 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 117.0 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.7%, Prefix cache hit rate: 95.1% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:32:34 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:32:34 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:32:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:32:34 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:32:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:32:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:32:34 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:32:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:32:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:32:34 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:32:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:32:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:32:34 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:32:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:32:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:32:34 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:32:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:32:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:32:34 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:32:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:32:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:32:34 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:32:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:32:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:32:34 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:32:34 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) INFO 06-14 04:32:38 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 117.7 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.9%, Prefix cache hit rate: 95.1% [repeated 46x across cluster] +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:32:37 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:32:37 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:32:37 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:32:37 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:32:37 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:32:37 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:32:37 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:32:37 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:32:37 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:32:37 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:32:37 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:32:37 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:32:37 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:32:37 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:32:37 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:32:37 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:32:37 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:32:37 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:32:37 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:32:37 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:32:37 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:32:37 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:32:37 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:32:37 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:32:37 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 7x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) INFO 06-14 04:32:43 [loggers.py:259] Engine 000: Avg prompt throughput: 113.1 tokens/s, Avg generation throughput: 104.0 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.2%, Prefix cache hit rate: 95.0% [repeated 46x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) INFO 06-14 04:32:48 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 117.5 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.4%, Prefix cache hit rate: 95.0% [repeated 46x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) INFO 06-14 04:32:53 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 119.3 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.5%, Prefix cache hit rate: 95.0% [repeated 46x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) INFO 06-14 04:32:58 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 116.3 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.7%, Prefix cache hit rate: 95.0% [repeated 46x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) INFO 06-14 04:33:03 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 116.2 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.9%, Prefix cache hit rate: 95.0% [repeated 46x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) INFO 06-14 04:33:08 [loggers.py:259] Engine 000: Avg prompt throughput: 128.0 tokens/s, Avg generation throughput: 103.2 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.2%, Prefix cache hit rate: 95.0% [repeated 46x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:33:08 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:33:08 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:33:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:33:08 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:33:08 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:33:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:33:08 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:33:08 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:33:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:33:08 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:33:08 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:33:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:33:08 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:33:08 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:33:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:33:08 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:33:08 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:33:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:33:08 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:33:08 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:33:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:33:08 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:33:08 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:33:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:33:08 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:33:08 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 3x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) INFO 06-14 04:33:13 [loggers.py:259] Engine 000: Avg prompt throughput: 133.9 tokens/s, Avg generation throughput: 87.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.6%, Prefix cache hit rate: 94.9% [repeated 47x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:33:14] OK: 143 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:33:14] OK: RSS 1.97 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 7x across cluster] +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) INFO 06-14 04:33:18 [loggers.py:259] Engine 000: Avg prompt throughput: 87.7 tokens/s, Avg generation throughput: 85.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.8%, Prefix cache hit rate: 95.0% [repeated 46x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:33:21] OK: 138 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:33:21] OK: RSS 1.99 GiB | node mem 389.3/858.0 GiB used (45.4%), avail 468.7 GiB +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:33:22 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:33:22 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:33:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:33:22 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:33:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:33:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:33:22 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:33:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:33:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:33:22 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:33:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:33:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:33:22 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:33:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:33:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:33:22 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:33:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:33:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:33:22 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:33:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:33:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:33:22 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:33:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:33:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:33:22 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:33:22 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) INFO 06-14 04:33:23 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 88.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.8%, Prefix cache hit rate: 95.0% [repeated 45x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) INFO 06-14 04:33:28 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 50.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.9%, Prefix cache hit rate: 95.0% [repeated 46x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:33:29] OK: 167 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:33:29] OK: RSS 1.85 GiB | node mem 393.7/858.0 GiB used (45.9%), avail 464.3 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 7x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) INFO 06-14 04:33:33 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 50.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.9%, Prefix cache hit rate: 95.0% [repeated 46x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:33:38] OK: 127 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:33:38] OK: RSS 1.93 GiB | node mem 383.6/858.0 GiB used (44.7%), avail 474.3 GiB +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) INFO 06-14 04:33:38 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 50.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.0%, Prefix cache hit rate: 95.0% [repeated 46x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) INFO 06-14 04:33:43 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 230.8 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 20.1%, Prefix cache hit rate: 96.7% [repeated 47x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 3x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) INFO 06-14 04:33:48 [loggers.py:259] Engine 000: Avg prompt throughput: 378.1 tokens/s, Avg generation throughput: 230.5 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 23.5%, Prefix cache hit rate: 96.6% [repeated 45x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) INFO 06-14 04:33:53 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 249.0 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 23.8%, Prefix cache hit rate: 96.6% [repeated 44x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:33:55 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:33:55 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:33:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:33:55 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:33:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:33:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:33:55 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:33:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:33:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:33:55 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:33:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:33:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:33:55 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:33:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:33:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:33:55 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:33:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:33:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:33:55 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:33:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:33:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:33:55 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:33:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:33:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:33:55 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:33:55 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 2x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:33:58] OK: 282 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:33:58] OK: RSS 1.89 GiB | node mem 260.2/858.0 GiB used (30.3%), avail 597.7 GiB +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) INFO 06-14 04:33:58 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 231.4 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 16.8%, Prefix cache hit rate: 96.6% [repeated 44x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) INFO 06-14 04:34:03 [loggers.py:259] Engine 000: Avg prompt throughput: 143.7 tokens/s, Avg generation throughput: 249.4 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 24.8%, Prefix cache hit rate: 96.6% [repeated 44x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) INFO 06-14 04:34:08 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 295.9 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 25.2%, Prefix cache hit rate: 96.6% [repeated 42x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) INFO 06-14 04:34:13 [loggers.py:259] Engine 000: Avg prompt throughput: 90.3 tokens/s, Avg generation throughput: 279.7 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 25.7%, Prefix cache hit rate: 96.6% [repeated 44x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) INFO 06-14 04:34:18 [loggers.py:259] Engine 000: Avg prompt throughput: 190.2 tokens/s, Avg generation throughput: 255.4 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 26.3%, Prefix cache hit rate: 96.6% [repeated 44x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 04:34:19 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 04:34:19 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 04:34:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 04:34:19 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 04:34:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 04:34:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 04:34:19 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 04:34:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 04:34:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 04:34:19 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 04:34:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 04:34:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 04:34:19 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 04:34:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 04:34:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 04:34:19 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 04:34:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 04:34:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 04:34:19 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 04:34:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 04:34:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 04:34:19 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 04:34:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 04:34:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 04:34:19 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 04:34:19 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) INFO 06-14 04:34:23 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 119.6 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.7%, Prefix cache hit rate: 94.9% [repeated 44x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) INFO 06-14 04:34:28 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 298.0 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 27.2%, Prefix cache hit rate: 96.6% [repeated 47x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=3946333, ip=10.128.56.73) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) ERROR 06-14 04:34:33 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) ERROR 06-14 04:34:33 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) ERROR 06-14 04:34:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) ERROR 06-14 04:34:33 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) ERROR 06-14 04:34:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) ERROR 06-14 04:34:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) ERROR 06-14 04:34:33 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) ERROR 06-14 04:34:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) ERROR 06-14 04:34:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) ERROR 06-14 04:34:33 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) ERROR 06-14 04:34:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) ERROR 06-14 04:34:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) ERROR 06-14 04:34:33 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) ERROR 06-14 04:34:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) ERROR 06-14 04:34:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) ERROR 06-14 04:34:33 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) ERROR 06-14 04:34:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) ERROR 06-14 04:34:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) ERROR 06-14 04:34:33 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) ERROR 06-14 04:34:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) ERROR 06-14 04:34:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) ERROR 06-14 04:34:33 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) ERROR 06-14 04:34:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) ERROR 06-14 04:34:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) ERROR 06-14 04:34:33 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=4037476, ip=10.128.56.68) ERROR 06-14 04:34:33 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) INFO 06-14 04:34:33 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 297.0 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 27.6%, Prefix cache hit rate: 96.6% [repeated 46x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) INFO 06-14 04:34:38 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 97.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.0%, Prefix cache hit rate: 94.9% [repeated 46x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:34:40 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:34:40 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:34:40 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:34:40 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:34:40 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:34:40 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:34:40 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:34:40 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:34:40 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:34:40 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:34:40 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:34:40 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:34:40 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:34:40 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:34:40 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:34:40 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:34:40 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:34:40 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:34:40 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:34:40 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:34:40 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:34:40 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:34:40 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:34:40 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:34:40 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:34:40 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 13x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) INFO 06-14 04:34:43 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 96.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.2%, Prefix cache hit rate: 94.9% [repeated 43x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) INFO 06-14 04:34:48 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 83.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.5%, Prefix cache hit rate: 94.9% [repeated 44x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:34:50 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:34:50 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:34:50 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:34:50 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:34:50 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:34:50 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:34:50 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:34:50 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:34:50 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:34:50 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:34:50 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:34:50 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:34:50 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:34:50 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:34:50 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:34:50 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:34:50 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:34:50 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:34:50 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:34:50 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:34:50 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:34:50 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:34:50 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:34:50 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:34:50 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:34:50 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) INFO 06-14 04:34:53 [loggers.py:259] Engine 000: Avg prompt throughput: 101.9 tokens/s, Avg generation throughput: 83.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.5%, Prefix cache hit rate: 95.0% [repeated 44x across cluster] +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:34:51 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:34:51 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:34:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:34:51 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:34:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:34:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:34:51 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:34:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:34:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:34:51 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:34:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:34:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:34:51 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:34:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:34:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:34:51 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:34:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:34:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:34:51 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:34:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:34:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:34:51 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:34:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:34:51 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:34:51 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) INFO 06-14 04:34:58 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 96.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.7%, Prefix cache hit rate: 95.0% [repeated 44x across cluster] +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) INFO 06-14 04:35:03 [loggers.py:259] Engine 000: Avg prompt throughput: 113.8 tokens/s, Avg generation throughput: 69.3 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.9%, Prefix cache hit rate: 95.0% [repeated 44x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) ERROR 06-14 04:35:06 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) ERROR 06-14 04:35:06 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) ERROR 06-14 04:35:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) ERROR 06-14 04:35:06 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) ERROR 06-14 04:35:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) ERROR 06-14 04:35:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) ERROR 06-14 04:35:06 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) ERROR 06-14 04:35:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) ERROR 06-14 04:35:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) ERROR 06-14 04:35:06 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) ERROR 06-14 04:35:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) ERROR 06-14 04:35:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) ERROR 06-14 04:35:06 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) ERROR 06-14 04:35:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) ERROR 06-14 04:35:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) ERROR 06-14 04:35:06 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) ERROR 06-14 04:35:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) ERROR 06-14 04:35:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) ERROR 06-14 04:35:06 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) ERROR 06-14 04:35:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) ERROR 06-14 04:35:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) ERROR 06-14 04:35:06 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) ERROR 06-14 04:35:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) ERROR 06-14 04:35:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) ERROR 06-14 04:35:06 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3945855, ip=10.128.56.73) ERROR 06-14 04:35:06 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) INFO 06-14 04:35:08 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 95.8 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 15.1%, Prefix cache hit rate: 95.0% [repeated 44x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:35:10 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:35:10 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:35:10 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:35:10 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:35:10 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:35:10 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:35:10 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:35:10 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:35:10 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:35:10 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:35:10 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:35:10 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:35:10 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:35:10 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:35:10 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:35:10 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:35:10 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:35:10 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:35:10 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:35:10 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:35:10 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:35:10 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:35:10 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:35:10 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:35:10 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:35:14] OK: 134 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) INFO 06-14 04:35:13 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 88.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.9%, Prefix cache hit rate: 95.0% [repeated 44x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:35:14] OK: RSS 1.98 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:35:19 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.2%, Prefix cache hit rate: 95.7% [repeated 45x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:35:21] OK: 125 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:35:21] OK: RSS 2.08 GiB | node mem 389.5/858.0 GiB used (45.4%), avail 468.5 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:35:24 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.3%, Prefix cache hit rate: 95.7% [repeated 43x across cluster] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:35:25 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:35:25 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:35:25 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:35:25 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:35:25 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:35:25 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:35:25 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:35:25 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:35:25 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:35:25 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:35:25 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:35:25 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:35:25 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:35:25 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:35:25 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:35:25 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:35:25 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:35:25 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:35:25 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:35:25 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:35:25 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:35:25 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:35:25 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:35:25 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:35:25 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:35:25 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:35:29 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.3%, Prefix cache hit rate: 95.7% [repeated 44x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:35:29] OK: 155 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:35:29] OK: RSS 1.91 GiB | node mem 393.7/858.0 GiB used (45.9%), avail 464.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:35:34 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.4%, Prefix cache hit rate: 95.7% [repeated 43x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:35:38] OK: 126 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:35:38] OK: RSS 1.93 GiB | node mem 383.7/858.0 GiB used (44.7%), avail 474.2 GiB +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:35:39 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.5%, Prefix cache hit rate: 95.7% [repeated 44x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:35:44 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.5%, Prefix cache hit rate: 95.7% [repeated 44x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=3946333, ip=10.128.56.73) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:35:48 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:35:48 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:35:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:35:48 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:35:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:35:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:35:48 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:35:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:35:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:35:48 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:35:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:35:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:35:48 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:35:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:35:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:35:48 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:35:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:35:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:35:48 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:35:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:35:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:35:48 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:35:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:35:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:35:48 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:35:48 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:35:49 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.6%, Prefix cache hit rate: 95.7% [repeated 43x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:35:49 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:35:49 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:35:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:35:49 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:35:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:35:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:35:49 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:35:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:35:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:35:49 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:35:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:35:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:35:49 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:35:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:35:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:35:49 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:35:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:35:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:35:49 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:35:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:35:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:35:49 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:35:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:35:49 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:35:49 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:35:54 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.7%, Prefix cache hit rate: 95.7% [repeated 43x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:35:58] OK: 273 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:35:58] OK: RSS 1.89 GiB | node mem 260.3/858.0 GiB used (30.3%), avail 597.7 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:35:59 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.7%, Prefix cache hit rate: 95.7% [repeated 43x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:36:04 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.8%, Prefix cache hit rate: 95.7% [repeated 43x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:36:09 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.9%, Prefix cache hit rate: 95.7% [repeated 43x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:36:11 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:36:11 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:36:11 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:36:11 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:36:11 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:36:11 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:36:11 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:36:11 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:36:11 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:36:11 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:36:11 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:36:11 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:36:11 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:36:11 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:36:11 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:36:11 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:36:11 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:36:11 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:36:11 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:36:11 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:36:11 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:36:11 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:36:11 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:36:11 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:36:11 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:36:11 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) INFO 06-14 04:36:14 [loggers.py:259] Engine 000: Avg prompt throughput: 122.3 tokens/s, Avg generation throughput: 75.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.8%, Prefix cache hit rate: 94.0% [repeated 44x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=3946333, ip=10.128.56.73) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) ERROR 06-14 04:36:14 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) ERROR 06-14 04:36:14 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) ERROR 06-14 04:36:14 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) ERROR 06-14 04:36:14 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) ERROR 06-14 04:36:14 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) ERROR 06-14 04:36:14 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) ERROR 06-14 04:36:14 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) ERROR 06-14 04:36:14 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) ERROR 06-14 04:36:14 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) ERROR 06-14 04:36:14 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) ERROR 06-14 04:36:14 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) ERROR 06-14 04:36:14 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) ERROR 06-14 04:36:14 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) ERROR 06-14 04:36:14 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) ERROR 06-14 04:36:14 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) ERROR 06-14 04:36:14 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) ERROR 06-14 04:36:14 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) ERROR 06-14 04:36:14 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) ERROR 06-14 04:36:14 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) ERROR 06-14 04:36:14 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) ERROR 06-14 04:36:14 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) ERROR 06-14 04:36:14 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) ERROR 06-14 04:36:14 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) ERROR 06-14 04:36:14 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) ERROR 06-14 04:36:14 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) INFO 06-14 04:36:19 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 48.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.9%, Prefix cache hit rate: 94.0% [repeated 44x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) INFO 06-14 04:36:24 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 48.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.9%, Prefix cache hit rate: 94.0% [repeated 44x across cluster] +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) INFO 06-14 04:36:29 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 48.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.0%, Prefix cache hit rate: 94.0% [repeated 44x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:36:31 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:36:31 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:36:31 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:36:31 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:36:31 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:36:31 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:36:31 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:36:31 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:36:31 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:36:31 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:36:31 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:36:31 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:36:31 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:36:31 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:36:31 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:36:31 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:36:31 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:36:31 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:36:31 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:36:31 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:36:31 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:36:31 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:36:31 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:36:31 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:36:31 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:36:31 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=3945544, ip=10.128.56.66) INFO 06-14 04:36:34 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 48.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.1%, Prefix cache hit rate: 94.0% [repeated 43x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=3946333, ip=10.128.56.73) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:36:32 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:36:32 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:36:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:36:32 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:36:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:36:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:36:32 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:36:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:36:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:36:32 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:36:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:36:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:36:32 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:36:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:36:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:36:32 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:36:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:36:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:36:32 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:36:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:36:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:36:32 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:36:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:36:32 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:36:32 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 04:36:39 [loggers.py:259] Engine 000: Avg prompt throughput: 80.3 tokens/s, Avg generation throughput: 63.5 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.6%, Prefix cache hit rate: 95.9% [repeated 44x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 7x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 04:36:44 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 73.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.7%, Prefix cache hit rate: 95.9% [repeated 43x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 04:36:49 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.8%, Prefix cache hit rate: 95.9% [repeated 45x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 04:36:54 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 73.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.9%, Prefix cache hit rate: 95.9% [repeated 44x across cluster] +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:36:55 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:36:55 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:36:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:36:55 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:36:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:36:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:36:55 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:36:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:36:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:36:55 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:36:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:36:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:36:55 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:36:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:36:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:36:55 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:36:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:36:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:36:55 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:36:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:36:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:36:55 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:36:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:36:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:36:55 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:36:55 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 04:36:59 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 73.1 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.0%, Prefix cache hit rate: 95.9% [repeated 45x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 04:37:04 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.3 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.1%, Prefix cache hit rate: 95.9% [repeated 45x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 04:37:09 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 73.5 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.2%, Prefix cache hit rate: 95.9% [repeated 45x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 12x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:37:14] OK: 130 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:37:14] OK: RSS 2.04 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 457.9 GiB +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 04:37:14 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 73.5 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.4%, Prefix cache hit rate: 95.9% [repeated 44x across cluster] +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:37:15 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:37:15 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:37:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:37:15 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:37:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:37:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:37:15 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:37:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:37:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:37:15 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:37:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:37:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:37:15 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:37:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:37:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:37:15 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:37:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:37:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:37:15 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:37:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:37:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:37:15 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:37:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:37:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:37:15 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:37:15 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 04:37:19 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 73.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.5%, Prefix cache hit rate: 95.9% [repeated 45x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:37:21] OK: 134 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:37:21] OK: RSS 2.13 GiB | node mem 389.5/858.0 GiB used (45.4%), avail 468.4 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 04:37:24 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 75.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.6%, Prefix cache hit rate: 95.9% [repeated 45x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 04:37:29 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.3 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.7%, Prefix cache hit rate: 95.9% [repeated 46x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:37:29] OK: 141 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:37:29] OK: RSS 2.02 GiB | node mem 393.9/858.0 GiB used (45.9%), avail 464.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 04:37:34 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.8%, Prefix cache hit rate: 95.9% [repeated 45x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:37:38] OK: 106 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:37:38] OK: RSS 1.94 GiB | node mem 383.8/858.0 GiB used (44.7%), avail 474.2 GiB +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 04:37:39 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 75.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.9%, Prefix cache hit rate: 95.9% [repeated 45x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 04:37:44 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 56.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.7%, Prefix cache hit rate: 95.9% [repeated 45x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:37:48 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:37:48 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:37:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:37:48 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:37:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:37:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:37:48 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:37:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:37:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:37:48 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:37:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:37:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:37:48 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:37:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:37:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:37:48 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:37:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:37:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:37:48 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:37:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:37:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:37:48 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:37:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:37:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:37:48 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:37:48 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=3946333, ip=10.128.56.73) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 04:37:49 [loggers.py:259] Engine 000: Avg prompt throughput: 298.1 tokens/s, Avg generation throughput: 66.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.2%, Prefix cache hit rate: 95.8% [repeated 45x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 04:37:54 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.3%, Prefix cache hit rate: 95.8% [repeated 44x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:37:58] OK: 269 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:37:58] OK: RSS 1.90 GiB | node mem 260.4/858.0 GiB used (30.4%), avail 597.6 GiB +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) INFO 06-14 04:38:00 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 77.8 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.7%, Prefix cache hit rate: 96.6% [repeated 46x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) INFO 06-14 04:38:05 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 75.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.8%, Prefix cache hit rate: 96.6% [repeated 45x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) INFO 06-14 04:38:10 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 75.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.9%, Prefix cache hit rate: 96.6% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:38:10 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:38:10 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:38:10 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:38:10 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:38:10 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:38:10 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:38:10 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:38:10 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:38:10 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:38:10 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:38:10 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:38:10 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:38:10 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:38:10 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:38:10 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:38:10 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:38:10 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:38:10 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:38:10 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:38:10 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:38:10 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:38:10 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:38:10 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:38:10 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:38:10 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:38:10 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 7x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) INFO 06-14 04:38:15 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 76.8 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.0%, Prefix cache hit rate: 96.6% [repeated 45x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:38:15 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:38:15 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:38:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:38:15 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:38:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:38:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:38:15 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:38:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:38:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:38:15 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:38:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:38:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:38:15 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:38:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:38:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:38:15 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:38:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:38:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:38:15 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:38:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:38:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:38:15 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:38:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:38:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:38:15 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:38:15 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) INFO 06-14 04:38:20 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.1%, Prefix cache hit rate: 96.6% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:38:20 [serving.py:315] Error in preprocessing prompt inputs [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:38:20 [serving.py:315] Traceback (most recent call last): [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:38:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:38:20 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:38:20 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:38:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:38:20 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:38:20 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:38:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:38:20 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:38:20 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:38:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:38:20 [serving.py:315] return await asyncio.gather( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:38:20 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:38:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:38:20 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:38:20 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:38:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:38:20 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:38:20 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:38:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:38:20 [serving.py:315] tokens = validator(tokenizer, tokens) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:38:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:38:20 [serving.py:315] raise VLLMValidationError( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945856, ip=10.128.56.73) ERROR 06-14 04:38:20 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) [repeated 2x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) INFO 06-14 04:38:25 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 76.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.2%, Prefix cache hit rate: 96.6% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) INFO 06-14 04:38:30 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.3%, Prefix cache hit rate: 96.6% [repeated 45x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) INFO 06-14 04:38:35 [loggers.py:259] Engine 000: Avg prompt throughput: 46.1 tokens/s, Avg generation throughput: 63.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.5%, Prefix cache hit rate: 96.6% [repeated 45x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 7x across cluster] +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) INFO 06-14 04:38:40 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 102.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.2%, Prefix cache hit rate: 96.5% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) INFO 06-14 04:38:45 [loggers.py:259] Engine 000: Avg prompt throughput: 111.8 tokens/s, Avg generation throughput: 82.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.5%, Prefix cache hit rate: 96.5% [repeated 45x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) INFO 06-14 04:38:50 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 103.5 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.6%, Prefix cache hit rate: 96.5% [repeated 45x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:38:52 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:38:52 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:38:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:38:52 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:38:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:38:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:38:52 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:38:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:38:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:38:52 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:38:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:38:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:38:52 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:38:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:38:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:38:52 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:38:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:38:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:38:52 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:38:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:38:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:38:52 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:38:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:38:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:38:52 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:38:52 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) INFO 06-14 04:38:55 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 102.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.8%, Prefix cache hit rate: 96.5% [repeated 46x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) INFO 06-14 04:39:00 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 103.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.9%, Prefix cache hit rate: 96.5% [repeated 44x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:39:02 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:39:02 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:39:02 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:39:02 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:39:02 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:39:02 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:39:02 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:39:02 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:39:02 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:39:02 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:39:02 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:39:02 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:39:02 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:39:02 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:39:02 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:39:02 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:39:02 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:39:02 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:39:02 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:39:02 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:39:02 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:39:02 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:39:02 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:39:02 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:39:02 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:39:02 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) INFO 06-14 04:39:05 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 103.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.1%, Prefix cache hit rate: 96.5% [repeated 44x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:07 [serving.py:315] Error in preprocessing prompt inputs [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:07 [serving.py:315] Traceback (most recent call last): [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:07 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:07 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:07 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:07 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:07 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:07 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:07 [serving.py:315] return await asyncio.gather( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:07 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:07 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:07 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:07 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:07 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:07 [serving.py:315] tokens = validator(tokenizer, tokens) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:07 [serving.py:315] raise VLLMValidationError( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:07 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) [repeated 2x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) INFO 06-14 04:39:10 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 89.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.0%, Prefix cache hit rate: 96.5% [repeated 42x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:39:14] OK: 120 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:39:14] OK: RSS 2.02 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) INFO 06-14 04:39:15 [loggers.py:259] Engine 000: Avg prompt throughput: 162.3 tokens/s, Avg generation throughput: 94.5 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.6%, Prefix cache hit rate: 96.4% [repeated 46x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) INFO 06-14 04:39:20 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 102.5 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.7%, Prefix cache hit rate: 96.4% [repeated 44x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:39:21] OK: 134 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:39:21] OK: RSS 2.13 GiB | node mem 389.5/858.0 GiB used (45.4%), avail 468.4 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 3x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) INFO 06-14 04:39:25 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.5%, Prefix cache hit rate: 92.7% [repeated 45x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:39:26 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:39:26 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:39:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:39:26 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:39:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:39:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:39:26 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:39:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:39:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:39:26 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:39:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:39:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:39:26 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:39:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:39:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:39:26 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:39:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:39:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:39:26 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:39:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:39:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:39:26 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:39:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:39:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:39:26 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 04:39:26 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 2x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:39:29] OK: 137 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:39:29] OK: RSS 2.03 GiB | node mem 393.9/858.0 GiB used (45.9%), avail 464.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) INFO 06-14 04:39:30 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.5%, Prefix cache hit rate: 92.7% [repeated 45x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:39:30 [serving.py:315] Error in preprocessing prompt inputs [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:39:30 [serving.py:315] Traceback (most recent call last): [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:39:30 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:39:30 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:39:30 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:39:30 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:39:30 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:39:30 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:39:30 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:39:30 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:39:30 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:39:30 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:39:30 [serving.py:315] return await asyncio.gather( [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:39:30 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:39:30 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:39:30 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:39:30 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:39:30 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:39:30 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:39:30 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:39:30 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:39:30 [serving.py:315] tokens = validator(tokenizer, tokens) [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:39:30 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:39:30 [serving.py:315] raise VLLMValidationError( [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:39:30 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) [repeated 3x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) INFO 06-14 04:39:35 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.6%, Prefix cache hit rate: 92.7% [repeated 44x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:35 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:35 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:35 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:35 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:35 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:35 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:35 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:35 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:35 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:35 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:39:35 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:39:38] OK: 97 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:39:38] OK: RSS 1.94 GiB | node mem 383.8/858.0 GiB used (44.7%), avail 474.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) INFO 06-14 04:39:40 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.7%, Prefix cache hit rate: 92.7% [repeated 44x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:39:43 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:39:43 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:39:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:39:43 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:39:43 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:39:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:39:43 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:39:43 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:39:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:39:43 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:39:43 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:39:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:39:43 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:39:43 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:39:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:39:43 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:39:43 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:39:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:39:43 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:39:43 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:39:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:39:43 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:39:43 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:39:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:39:43 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:39:43 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 7x across cluster] +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) INFO 06-14 04:39:45 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 48.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.7%, Prefix cache hit rate: 92.7% [repeated 44x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 3x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) INFO 06-14 04:39:50 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.8%, Prefix cache hit rate: 92.7% [repeated 44x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) INFO 06-14 04:39:55 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.9%, Prefix cache hit rate: 92.7% [repeated 44x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:39:58] OK: 257 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:39:58] OK: RSS 1.90 GiB | node mem 260.4/858.0 GiB used (30.4%), avail 597.5 GiB +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) INFO 06-14 04:40:00 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.9%, Prefix cache hit rate: 92.7% [repeated 44x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) INFO 06-14 04:40:05 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.0%, Prefix cache hit rate: 92.7% [repeated 43x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:40:09 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:40:09 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:40:09 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:40:09 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:40:09 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:40:09 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:40:09 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:40:09 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:40:09 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:40:09 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:40:09 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:40:09 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:40:09 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:40:09 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:40:09 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:40:09 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:40:09 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:40:09 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:40:09 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:40:09 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:40:09 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:40:09 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:40:09 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:40:09 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:40:09 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:40:09 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) INFO 06-14 04:40:10 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.1%, Prefix cache hit rate: 92.7% [repeated 43x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) INFO 06-14 04:40:15 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.1%, Prefix cache hit rate: 92.7% [repeated 41x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 10x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) INFO 06-14 04:40:20 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 85.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.1%, Prefix cache hit rate: 96.0% [repeated 42x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:40:23 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:40:23 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:40:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:40:23 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:40:23 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:40:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:40:23 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:40:23 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:40:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:40:23 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:40:23 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:40:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:40:23 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:40:23 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:40:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:40:23 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:40:23 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:40:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:40:23 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:40:23 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:40:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:40:23 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:40:23 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:40:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:40:23 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:40:23 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) INFO 06-14 04:40:25 [loggers.py:259] Engine 000: Avg prompt throughput: 25.9 tokens/s, Avg generation throughput: 79.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.7%, Prefix cache hit rate: 96.0% [repeated 42x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 7x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:40:26 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:40:26 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:40:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:40:26 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:40:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:40:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:40:26 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:40:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:40:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:40:26 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:40:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:40:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:40:26 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:40:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:40:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:40:26 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:40:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:40:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:40:26 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:40:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:40:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:40:26 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:40:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:40:26 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:40:26 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:40:28 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:40:28 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:40:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:40:28 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:40:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:40:28 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:40:28 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:40:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:40:28 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:40:28 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:40:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:40:28 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:40:28 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:40:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:40:28 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:40:28 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:40:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:40:28 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:40:28 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:40:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:40:28 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:40:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:40:28 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:40:28 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) INFO 06-14 04:40:30 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 53.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.9%, Prefix cache hit rate: 96.0% [repeated 42x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 04:40:28 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:40:34 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:40:34 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:40:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:40:34 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:40:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:40:34 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:40:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:40:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:40:34 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:40:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:40:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:40:34 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:40:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:40:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:40:34 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:40:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:40:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:40:34 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:40:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:40:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:40:34 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:40:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:40:34 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:40:34 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) INFO 06-14 04:40:35 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 48.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.9%, Prefix cache hit rate: 96.0% [repeated 43x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:40:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) INFO 06-14 04:40:40 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 48.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.0%, Prefix cache hit rate: 96.0% [repeated 42x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) INFO 06-14 04:40:45 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 48.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.1%, Prefix cache hit rate: 96.0% [repeated 41x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=3946333, ip=10.128.56.73) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:40:48 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:40:48 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:40:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:40:48 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:40:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:40:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:40:48 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:40:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:40:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:40:48 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:40:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:40:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:40:48 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:40:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:40:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:40:48 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:40:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:40:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:40:48 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:40:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:40:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:40:48 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:40:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:40:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:40:48 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:40:48 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) INFO 06-14 04:40:50 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 50.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.6%, Prefix cache hit rate: 95.2% [repeated 42x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:40:51 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:40:51 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:40:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:40:51 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:40:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:40:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:40:51 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:40:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:40:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:40:51 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:40:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:40:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:40:51 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:40:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:40:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:40:51 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:40:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:40:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:40:51 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:40:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:40:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:40:51 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:40:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:40:51 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:40:51 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) INFO 06-14 04:40:55 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 50.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.6%, Prefix cache hit rate: 95.2% [repeated 41x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:40:59 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:40:59 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:40:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:40:59 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:40:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:40:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:40:59 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:40:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:40:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:40:59 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:40:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:40:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:40:59 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:40:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:40:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:40:59 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:40:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:40:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:40:59 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:40:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:40:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:40:59 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:40:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:40:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:40:59 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:40:59 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) INFO 06-14 04:41:00 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 50.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.7%, Prefix cache hit rate: 95.2% [repeated 41x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) INFO 06-14 04:41:05 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 50.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.8%, Prefix cache hit rate: 95.2% [repeated 41x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) INFO 06-14 04:41:10 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 50.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.8%, Prefix cache hit rate: 95.2% [repeated 41x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 2x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:41:14] OK: 128 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:41:14] OK: RSS 2.01 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) INFO 06-14 04:41:16 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 50.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.9%, Prefix cache hit rate: 95.2% [repeated 40x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) INFO 06-14 04:41:21 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 50.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.0%, Prefix cache hit rate: 95.2% [repeated 41x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:41:21] OK: 129 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:41:21] OK: RSS 2.13 GiB | node mem 389.5/858.0 GiB used (45.4%), avail 468.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) INFO 06-14 04:41:26 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 49.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.0%, Prefix cache hit rate: 95.2% [repeated 40x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:41:29] OK: 134 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:41:29] OK: RSS 2.06 GiB | node mem 393.9/858.0 GiB used (45.9%), avail 464.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) INFO 06-14 04:41:31 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 50.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.1%, Prefix cache hit rate: 95.2% [repeated 41x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 14x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) INFO 06-14 04:41:36 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 50.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.2%, Prefix cache hit rate: 95.2% [repeated 41x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 2x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:41:38] OK: 100 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:41:38] OK: RSS 1.94 GiB | node mem 383.8/858.0 GiB used (44.7%), avail 474.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:41:39 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:41:39 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:41:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:41:39 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:41:39 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:41:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:41:39 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:41:39 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:41:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:41:39 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:41:39 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:41:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:41:39 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:41:39 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:41:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:41:39 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:41:39 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:41:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:41:39 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:41:39 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:41:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:41:39 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:41:39 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:41:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:41:39 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:41:39 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) INFO 06-14 04:41:41 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 212.2 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 16.2%, Prefix cache hit rate: 94.3% [repeated 43x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:41:43 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:41:43 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:41:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:41:43 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:41:43 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:41:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:41:43 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:41:43 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:41:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:41:43 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:41:43 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:41:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:41:43 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:41:43 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:41:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:41:43 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:41:43 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:41:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:41:43 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:41:43 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:41:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:41:43 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:41:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:41:43 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:41:43 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) INFO 06-14 04:41:46 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 211.2 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 16.5%, Prefix cache hit rate: 94.3% [repeated 41x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) INFO 06-14 04:41:51 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 42.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.7%, Prefix cache hit rate: 94.9% [repeated 42x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:41:52 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:41:52 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:41:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:41:52 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:41:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:41:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:41:52 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:41:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:41:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:41:52 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:41:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:41:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:41:52 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:41:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:41:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:41:52 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:41:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:41:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:41:52 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:41:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:41:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:41:52 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:41:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:41:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:41:52 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:41:52 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) INFO 06-14 04:41:56 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 41.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.7%, Prefix cache hit rate: 94.9% [repeated 41x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:41:58] OK: 260 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:41:58] OK: RSS 1.90 GiB | node mem 260.4/858.0 GiB used (30.4%), avail 597.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) INFO 06-14 04:42:01 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 41.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.8%, Prefix cache hit rate: 94.9% [repeated 42x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 8x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) INFO 06-14 04:42:06 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 42.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.8%, Prefix cache hit rate: 94.9% [repeated 42x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) INFO 06-14 04:42:11 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 41.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.9%, Prefix cache hit rate: 94.9% [repeated 42x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) INFO 06-14 04:42:16 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 41.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.0%, Prefix cache hit rate: 94.9% [repeated 41x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) INFO 06-14 04:42:21 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 42.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.0%, Prefix cache hit rate: 94.9% [repeated 41x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) INFO 06-14 04:42:26 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 42.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.1%, Prefix cache hit rate: 94.9% [repeated 41x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:42:28 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:42:28 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:42:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:42:28 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:42:28 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:42:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:42:28 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:42:28 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:42:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:42:28 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:42:28 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:42:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:42:28 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:42:28 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:42:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:42:28 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:42:28 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:42:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:42:28 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:42:28 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:42:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:42:28 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:42:28 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:42:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:42:28 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:42:28 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) INFO 06-14 04:42:31 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 43.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.1%, Prefix cache hit rate: 94.9% [repeated 41x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 12x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) INFO 06-14 04:42:36 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 41.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.2%, Prefix cache hit rate: 94.9% [repeated 41x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=3945723, ip=10.128.56.73) INFO 06-14 04:42:41 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 43.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.3%, Prefix cache hit rate: 94.9% [repeated 41x across cluster] +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) INFO 06-14 04:42:46 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 90.8 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.3%, Prefix cache hit rate: 94.5% [repeated 41x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) INFO 06-14 04:42:51 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 90.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.4%, Prefix cache hit rate: 94.5% [repeated 41x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:42:54 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:42:54 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:42:54 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:42:54 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:42:54 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:42:54 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:42:54 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:42:54 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:42:54 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:42:54 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:42:54 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:42:54 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:42:54 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:42:54 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:42:54 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:42:54 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:42:54 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:42:54 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:42:54 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:42:54 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:42:54 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:42:54 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:42:54 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:42:54 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:42:54 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=323387, ip=10.128.56.67) ERROR 06-14 04:42:54 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) INFO 06-14 04:42:56 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 90.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.5%, Prefix cache hit rate: 94.5% [repeated 41x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:43:00 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:43:00 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:43:00 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:43:00 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:43:00 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:43:00 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:43:00 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:43:00 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:43:00 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:43:00 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:43:00 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:43:00 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:43:00 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:43:00 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:43:00 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:43:00 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:43:00 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:43:00 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:43:00 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:43:00 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:43:00 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:43:00 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:43:00 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:43:00 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:43:00 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:43:00 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) INFO 06-14 04:43:01 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 90.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.6%, Prefix cache hit rate: 94.5% [repeated 42x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 7x across cluster] +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) INFO 06-14 04:43:06 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 90.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.8%, Prefix cache hit rate: 94.5% [repeated 42x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) INFO 06-14 04:43:11 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 90.8 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.9%, Prefix cache hit rate: 94.5% [repeated 42x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:43:14] OK: 132 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:43:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) INFO 06-14 04:43:16 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 90.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.0%, Prefix cache hit rate: 94.5% [repeated 42x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:43:21 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:43:21 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:43:21 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:43:21 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:43:21 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:43:21 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:43:21 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:43:21 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:43:21 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:43:21 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:43:21 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:43:21 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:43:21 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:43:21 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:43:21 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:43:21 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:43:21 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:43:21 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:43:21 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:43:21 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:43:21 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:43:21 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:43:21 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:43:21 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:43:21 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:43:21 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) INFO 06-14 04:43:21 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 91.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.1%, Prefix cache hit rate: 94.5% [repeated 42x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:43:21] OK: 128 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:43:21] OK: RSS 2.13 GiB | node mem 389.5/858.0 GiB used (45.4%), avail 468.4 GiB +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) INFO 06-14 04:43:26 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 91.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.3%, Prefix cache hit rate: 94.5% [repeated 42x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:43:26 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:43:26 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:43:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:43:26 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:43:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:43:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:43:26 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:43:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:43:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:43:26 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:43:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:43:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:43:26 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:43:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:43:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:43:26 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:43:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:43:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:43:26 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:43:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:43:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:43:26 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:43:26 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:43:26 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:43:26 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:43:26 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:43:29] OK: 139 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:43:29] OK: RSS 2.05 GiB | node mem 394.0/858.0 GiB used (45.9%), avail 464.0 GiB +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) INFO 06-14 04:43:31 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 91.3 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.4%, Prefix cache hit rate: 94.5% [repeated 42x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) INFO 06-14 04:43:36 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 90.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.5%, Prefix cache hit rate: 94.5% [repeated 42x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:43:38] OK: 98 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:43:38] OK: RSS 1.94 GiB | node mem 383.9/858.0 GiB used (44.7%), avail 474.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) INFO 06-14 04:43:41 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 90.8 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.6%, Prefix cache hit rate: 94.5% [repeated 42x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 8x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) INFO 06-14 04:43:46 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 90.8 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.8%, Prefix cache hit rate: 94.5% [repeated 42x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:43:51 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 78.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.5%, Prefix cache hit rate: 96.0% [repeated 42x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:43:56 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:43:56 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:43:56 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:43:56 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:43:56 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:43:56 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:43:56 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:43:56 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:43:56 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:43:56 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:43:56 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:43:56 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:43:56 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:43:56 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:43:56 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:43:56 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:43:56 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:43:56 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:43:56 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:43:56 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:43:56 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:43:56 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:43:56 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:43:56 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:43:56 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:43:56 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:43:56 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 80.5 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.7%, Prefix cache hit rate: 96.0% [repeated 42x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:43:58] OK: 259 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:43:58] OK: RSS 1.90 GiB | node mem 260.4/858.0 GiB used (30.4%), avail 597.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 3x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:44:01 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 79.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.8%, Prefix cache hit rate: 96.0% [repeated 41x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 2x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:44:06 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 78.3 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.9%, Prefix cache hit rate: 96.0% [repeated 42x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:44:08 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:44:08 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:44:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:44:08 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:44:08 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:44:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:44:08 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:44:08 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:44:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:44:08 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:44:08 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:44:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:44:08 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:44:08 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:44:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:44:08 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:44:08 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:44:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:44:08 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:44:08 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:44:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:44:08 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:44:08 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:44:08 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:44:08 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:44:08 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:44:11 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 78.1 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.0%, Prefix cache hit rate: 96.0% [repeated 43x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:44:16 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 79.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.1%, Prefix cache hit rate: 96.0% [repeated 43x across cluster] +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:44:19 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:44:19 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:44:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:44:19 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:44:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:44:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:44:19 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:44:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:44:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:44:19 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:44:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:44:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:44:19 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:44:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:44:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:44:19 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:44:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:44:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:44:19 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:44:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:44:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:44:19 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:44:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:44:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:44:19 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:44:19 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:44:21 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 78.5 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.2%, Prefix cache hit rate: 96.0% [repeated 42x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:44:26 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 80.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.3%, Prefix cache hit rate: 96.0% [repeated 43x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:44:27 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:44:27 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:44:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:44:27 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:44:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:44:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:44:27 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:44:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:44:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:44:27 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:44:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:44:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:44:27 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:44:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:44:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:44:27 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:44:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:44:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:44:27 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:44:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:44:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:44:27 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:44:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:44:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:44:27 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:44:27 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:44:31 [loggers.py:259] Engine 000: Avg prompt throughput: 91.5 tokens/s, Avg generation throughput: 61.8 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.5%, Prefix cache hit rate: 96.1% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:44:36 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 80.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.6%, Prefix cache hit rate: 96.1% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:44:41 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 80.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.8%, Prefix cache hit rate: 96.1% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:44:46 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 79.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.9%, Prefix cache hit rate: 96.1% [repeated 45x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:44:51 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 82.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.0%, Prefix cache hit rate: 96.1% [repeated 44x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 8x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) INFO 06-14 04:44:56 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 78.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.1%, Prefix cache hit rate: 96.1% [repeated 44x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) INFO 06-14 04:45:02 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 111.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.1%, Prefix cache hit rate: 95.9% [repeated 45x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) INFO 06-14 04:45:07 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 111.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.3%, Prefix cache hit rate: 95.9% [repeated 44x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) INFO 06-14 04:45:12 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 111.1 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.5%, Prefix cache hit rate: 95.9% [repeated 44x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:45:14] OK: 107 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:45:14] OK: RSS 2.01 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) INFO 06-14 04:45:17 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 111.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.6%, Prefix cache hit rate: 95.9% [repeated 44x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:45:21] OK: 131 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:45:21] OK: RSS 2.14 GiB | node mem 389.5/858.0 GiB used (45.4%), avail 468.4 GiB +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) INFO 06-14 04:45:22 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 110.8 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.8%, Prefix cache hit rate: 95.9% [repeated 44x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 3x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) INFO 06-14 04:45:27 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 111.0 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.9%, Prefix cache hit rate: 95.9% [repeated 43x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:45:29] OK: 139 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:45:29] OK: RSS 2.06 GiB | node mem 394.0/858.0 GiB used (45.9%), avail 464.0 GiB +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) INFO 06-14 04:45:32 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 110.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.1%, Prefix cache hit rate: 95.9% [repeated 44x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:45:37 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.3%, Prefix cache hit rate: 95.6% [repeated 45x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:45:38 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:45:38 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:45:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:45:38 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:45:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:45:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:45:38 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:45:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:45:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:45:38 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:45:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:45:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:45:38 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:45:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:45:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:45:38 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:45:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:45:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:45:38 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:45:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:45:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:45:38 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:45:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:45:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:45:38 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:45:38 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:45:38] OK: 92 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:45:38] OK: RSS 1.94 GiB | node mem 383.8/858.0 GiB used (44.7%), avail 474.1 GiB +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:45:42 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.4%, Prefix cache hit rate: 95.6% [repeated 44x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:45:47 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.4%, Prefix cache hit rate: 95.6% [repeated 44x across cluster] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:45:51 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:45:51 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:45:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:45:51 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:45:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:45:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:45:51 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:45:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:45:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:45:51 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:45:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:45:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:45:51 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:45:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:45:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:45:51 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:45:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:45:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:45:51 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:45:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:45:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:45:51 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:45:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:45:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:45:51 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507974, ip=10.128.34.179) ERROR 06-14 04:45:51 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:45:52 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.5%, Prefix cache hit rate: 95.6% [repeated 44x across cluster] +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:45:57 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.6%, Prefix cache hit rate: 95.6% [repeated 44x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:45:58] OK: 259 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:45:58] OK: RSS 1.91 GiB | node mem 260.4/858.0 GiB used (30.4%), avail 597.5 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:46:02 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.6%, Prefix cache hit rate: 95.6% [repeated 44x across cluster] +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ERROR 06-14 04:46:06 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ERROR 06-14 04:46:06 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ERROR 06-14 04:46:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ERROR 06-14 04:46:06 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ERROR 06-14 04:46:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ERROR 06-14 04:46:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ERROR 06-14 04:46:06 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ERROR 06-14 04:46:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ERROR 06-14 04:46:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ERROR 06-14 04:46:06 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ERROR 06-14 04:46:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ERROR 06-14 04:46:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ERROR 06-14 04:46:06 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ERROR 06-14 04:46:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ERROR 06-14 04:46:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ERROR 06-14 04:46:06 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ERROR 06-14 04:46:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ERROR 06-14 04:46:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ERROR 06-14 04:46:06 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ERROR 06-14 04:46:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ERROR 06-14 04:46:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ERROR 06-14 04:46:06 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ERROR 06-14 04:46:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ERROR 06-14 04:46:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ERROR 06-14 04:46:06 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=153668, ip=10.128.56.65) ERROR 06-14 04:46:06 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:46:07 [loggers.py:259] Engine 000: Avg prompt throughput: 193.0 tokens/s, Avg generation throughput: 31.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.5%, Prefix cache hit rate: 95.5% [repeated 44x across cluster] +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:46:12 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.5%, Prefix cache hit rate: 95.5% [repeated 43x across cluster] +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:46:17 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.6%, Prefix cache hit rate: 95.5% [repeated 43x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:46:22 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.7%, Prefix cache hit rate: 95.5% [repeated 43x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 8x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:46:25 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:46:25 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:46:25 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:46:25 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:46:25 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:46:25 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:46:25 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:46:25 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:46:25 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:46:25 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:46:25 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:46:25 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:46:25 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:46:25 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:46:25 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:46:25 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:46:25 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:46:25 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:46:25 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:46:25 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:46:25 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:46:25 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:46:25 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:46:25 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:46:25 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 04:46:25 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:46:27 [loggers.py:259] Engine 000: Avg prompt throughput: 163.5 tokens/s, Avg generation throughput: 21.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 1.9%, Prefix cache hit rate: 95.5% [repeated 42x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 4x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:46:29 [serving.py:315] Error in preprocessing prompt inputs [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:46:29 [serving.py:315] Traceback (most recent call last): [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:46:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:46:29 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:46:29 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:46:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:46:29 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:46:29 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:46:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:46:29 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:46:29 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:46:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:46:29 [serving.py:315] return await asyncio.gather( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:46:29 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:46:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:46:29 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:46:29 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:46:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:46:29 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:46:29 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:46:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:46:29 [serving.py:315] tokens = validator(tokenizer, tokens) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:46:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:46:29 [serving.py:315] raise VLLMValidationError( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:46:29 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:46:32 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 46.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.0%, Prefix cache hit rate: 95.5% [repeated 43x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:46:37 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.1%, Prefix cache hit rate: 95.5% [repeated 43x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 04:46:41 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 04:46:41 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 04:46:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 04:46:41 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 04:46:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 04:46:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 04:46:41 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 04:46:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 04:46:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 04:46:41 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 04:46:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 04:46:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 04:46:41 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 04:46:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 04:46:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 04:46:41 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 04:46:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 04:46:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 04:46:41 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 04:46:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 04:46:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 04:46:41 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 04:46:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 04:46:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 04:46:41 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 04:46:41 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:46:42 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.1%, Prefix cache hit rate: 95.5% [repeated 43x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:46:47 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.2%, Prefix cache hit rate: 95.5% [repeated 42x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:46:51 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:46:51 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:46:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:46:51 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:46:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:46:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:46:51 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:46:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:46:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:46:51 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:46:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:46:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:46:51 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:46:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:46:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:46:51 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:46:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:46:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:46:51 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:46:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:46:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:46:51 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:46:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:46:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:46:51 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:46:51 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=3946333, ip=10.128.56.73) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1507804, ip=10.128.34.181) INFO 06-14 04:46:52 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.3%, Prefix cache hit rate: 95.5% [repeated 42x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) INFO 06-14 04:46:57 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 162.2 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 15.8%, Prefix cache hit rate: 95.7% [repeated 42x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) INFO 06-14 04:47:02 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 162.6 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 16.0%, Prefix cache hit rate: 95.7% [repeated 42x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 7x across cluster] +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:47:06 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:47:06 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:47:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:47:06 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:47:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:47:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:47:06 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:47:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:47:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:47:06 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:47:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:47:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:47:06 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:47:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:47:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:47:06 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:47:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:47:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:47:06 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:47:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:47:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:47:06 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:47:06 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:47:06 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:47:06 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) ERROR 06-14 04:47:06 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) INFO 06-14 04:47:07 [loggers.py:259] Engine 000: Avg prompt throughput: 254.6 tokens/s, Avg generation throughput: 135.4 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.3%, Prefix cache hit rate: 96.0% [repeated 43x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 7x across cluster] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) INFO 06-14 04:47:12 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 154.3 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.5%, Prefix cache hit rate: 96.0% [repeated 41x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:47:14] OK: 103 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:47:14] OK: RSS 2.02 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) INFO 06-14 04:47:18 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 155.3 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.7%, Prefix cache hit rate: 96.0% [repeated 41x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:47:21] OK: 117 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:47:21] OK: RSS 2.15 GiB | node mem 389.6/858.0 GiB used (45.4%), avail 468.4 GiB +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) INFO 06-14 04:47:23 [loggers.py:259] Engine 000: Avg prompt throughput: 95.5 tokens/s, Avg generation throughput: 140.7 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 15.0%, Prefix cache hit rate: 96.0% [repeated 41x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) INFO 06-14 04:47:28 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 154.9 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 15.3%, Prefix cache hit rate: 96.0% [repeated 41x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:47:29] OK: 141 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:47:29] OK: RSS 2.07 GiB | node mem 394.0/858.0 GiB used (45.9%), avail 463.9 GiB +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) INFO 06-14 04:47:33 [loggers.py:259] Engine 000: Avg prompt throughput: 185.5 tokens/s, Avg generation throughput: 141.2 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 15.7%, Prefix cache hit rate: 96.0% [repeated 41x across cluster] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) INFO 06-14 04:47:38 [loggers.py:259] Engine 000: Avg prompt throughput: 154.2 tokens/s, Avg generation throughput: 139.7 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 16.1%, Prefix cache hit rate: 95.9% [repeated 41x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:47:38] OK: 95 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:47:38] OK: RSS 1.94 GiB | node mem 383.9/858.0 GiB used (44.7%), avail 474.1 GiB +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) INFO 06-14 04:47:43 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 157.8 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 16.3%, Prefix cache hit rate: 95.9% [repeated 41x across cluster] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) INFO 06-14 04:47:48 [loggers.py:259] Engine 000: Avg prompt throughput: 189.2 tokens/s, Avg generation throughput: 146.1 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.9%, Prefix cache hit rate: 95.9% [repeated 41x across cluster] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) INFO 06-14 04:47:53 [loggers.py:259] Engine 000: Avg prompt throughput: 51.1 tokens/s, Avg generation throughput: 132.8 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 16.9%, Prefix cache hit rate: 95.9% [repeated 41x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) INFO 06-14 04:47:58 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 154.9 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 17.2%, Prefix cache hit rate: 95.9% [repeated 40x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:47:58] OK: 251 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:47:58] OK: RSS 1.91 GiB | node mem 260.4/858.0 GiB used (30.3%), avail 597.6 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) INFO 06-14 04:48:03 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 160.0 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.4%, Prefix cache hit rate: 95.9% [repeated 40x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) INFO 06-14 04:48:08 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 93.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.0%, Prefix cache hit rate: 94.9% [repeated 41x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) INFO 06-14 04:48:13 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 93.5 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.1%, Prefix cache hit rate: 94.9% [repeated 40x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) INFO 06-14 04:48:18 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 93.8 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.6%, Prefix cache hit rate: 94.9% [repeated 41x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) INFO 06-14 04:48:23 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 88.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.3%, Prefix cache hit rate: 94.9% [repeated 40x across cluster] +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) INFO 06-14 04:48:28 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 94.1 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.9%, Prefix cache hit rate: 94.9% [repeated 42x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) INFO 06-14 04:48:33 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 94.5 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.0%, Prefix cache hit rate: 94.9% [repeated 42x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) INFO 06-14 04:48:38 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 94.5 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.1%, Prefix cache hit rate: 94.9% [repeated 42x across cluster] +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) INFO 06-14 04:48:43 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 94.3 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.3%, Prefix cache hit rate: 94.9% [repeated 42x across cluster] +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) INFO 06-14 04:48:48 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 94.3 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.4%, Prefix cache hit rate: 94.9% [repeated 41x across cluster] +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) INFO 06-14 04:48:53 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 94.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.5%, Prefix cache hit rate: 94.9% [repeated 41x across cluster] +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) INFO 06-14 04:48:58 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 94.1 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.7%, Prefix cache hit rate: 94.9% [repeated 41x across cluster] +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) INFO 06-14 04:49:03 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 94.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.8%, Prefix cache hit rate: 94.9% [repeated 41x across cluster] +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) INFO 06-14 04:49:08 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 94.1 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.9%, Prefix cache hit rate: 94.9% [repeated 40x across cluster] +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) INFO 06-14 04:49:13 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 71.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.3%, Prefix cache hit rate: 94.9% [repeated 41x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:49:14] OK: 102 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:49:14] OK: RSS 2.02 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) INFO 06-14 04:49:18 [loggers.py:259] Engine 000: Avg prompt throughput: 179.6 tokens/s, Avg generation throughput: 88.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.4%, Prefix cache hit rate: 94.9% [repeated 40x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:49:21] OK: 119 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:49:21] OK: RSS 2.16 GiB | node mem 389.6/858.0 GiB used (45.4%), avail 468.4 GiB +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) INFO 06-14 04:49:23 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 93.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.5%, Prefix cache hit rate: 94.9% [repeated 39x across cluster] +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) INFO 06-14 04:49:28 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 94.1 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.7%, Prefix cache hit rate: 94.9% [repeated 39x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:49:29] OK: 136 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:49:29] OK: RSS 2.07 GiB | node mem 394.1/858.0 GiB used (45.9%), avail 463.9 GiB +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:49:33 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:49:33 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:49:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:49:33 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:49:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:49:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:49:33 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:49:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:49:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:49:33 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:49:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:49:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:49:33 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:49:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:49:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:49:33 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:49:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:49:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:49:33 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:49:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:49:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:49:33 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:49:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:49:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:49:33 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:49:33 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) INFO 06-14 04:49:33 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 94.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.8%, Prefix cache hit rate: 94.9% [repeated 40x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:49:38] OK: 82 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:49:38] OK: RSS 1.94 GiB | node mem 383.9/858.0 GiB used (44.7%), avail 474.0 GiB +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) INFO 06-14 04:49:38 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 94.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.9%, Prefix cache hit rate: 94.9% [repeated 40x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 3x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:42 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:42 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:42 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:42 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:42 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:42 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:42 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:42 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:42 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:42 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:42 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:42 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:42 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:42 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:42 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:42 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:42 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:42 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:42 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:42 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:42 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:42 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:42 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:42 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:42 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:42 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 04:49:43 [loggers.py:259] Engine 000: Avg prompt throughput: 170.6 tokens/s, Avg generation throughput: 166.4 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.1%, Prefix cache hit rate: 94.8% [repeated 41x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 2x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:47 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:47 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:47 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:47 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:47 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:47 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:47 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:47 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:47 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:47 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:47 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:47 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:47 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:47 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:47 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:47 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:47 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:47 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:47 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:47 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:47 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:47 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:47 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:47 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:47 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:49:47 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 04:49:48 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 191.5 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.4%, Prefix cache hit rate: 94.8% [repeated 40x across cluster] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:49:52 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:49:52 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:49:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:49:52 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:49:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:49:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:49:52 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:49:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:49:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:49:52 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:49:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:49:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:49:52 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:49:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:49:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:49:52 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:49:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:49:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:49:52 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:49:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:49:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:49:52 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:49:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:49:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:49:52 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:49:52 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 04:49:53 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 191.5 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.7%, Prefix cache hit rate: 94.8% [repeated 40x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:49:58] OK: 245 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:49:58] OK: RSS 1.91 GiB | node mem 260.4/858.0 GiB used (30.4%), avail 597.6 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:49:58 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:49:58 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:49:58 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:49:58 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:49:58 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:49:58 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:49:58 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:49:58 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:49:58 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:49:58 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:49:58 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:49:58 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:49:58 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:49:58 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:49:58 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:49:58 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:49:58 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:49:58 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:49:58 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:49:58 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:49:58 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:49:58 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:49:58 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:49:58 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:49:58 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 04:49:58 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 04:49:58 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 191.4 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.9%, Prefix cache hit rate: 94.8% [repeated 40x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new [repeated 3x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:50:03 [serving.py:315] Error in preprocessing prompt inputs [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:50:03 [serving.py:315] Traceback (most recent call last): [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:50:03 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:50:03 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:50:03 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:50:03 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:50:03 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:50:03 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:50:03 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:50:03 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:50:03 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:50:03 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:50:03 [serving.py:315] return await asyncio.gather( [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:50:03 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:50:03 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:50:03 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:50:03 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:50:03 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:50:03 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:50:03 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:50:03 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:50:03 [serving.py:315] tokens = validator(tokenizer, tokens) [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:50:03 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:50:03 [serving.py:315] raise VLLMValidationError( [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:50:03 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 04:50:03 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 176.0 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.0%, Prefix cache hit rate: 94.8% [repeated 40x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 04:50:08 [loggers.py:259] Engine 000: Avg prompt throughput: 171.4 tokens/s, Avg generation throughput: 153.6 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 15.6%, Prefix cache hit rate: 94.8% [repeated 40x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 04:50:13 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 191.1 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 15.9%, Prefix cache hit rate: 94.8% [repeated 40x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 04:50:18 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 191.5 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 16.2%, Prefix cache hit rate: 94.8% [repeated 38x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 04:50:23 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 190.6 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 16.4%, Prefix cache hit rate: 94.8% [repeated 40x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 7x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 04:50:28 [loggers.py:259] Engine 000: Avg prompt throughput: 144.4 tokens/s, Avg generation throughput: 175.3 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 16.9%, Prefix cache hit rate: 94.8% [repeated 39x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 8x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:50:31 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:50:31 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:50:31 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:50:31 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:50:31 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:50:31 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:50:31 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:50:31 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:50:31 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:50:31 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:50:31 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:50:31 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:50:31 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:50:31 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:50:31 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:50:31 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:50:31 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:50:31 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:50:31 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:50:31 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:50:31 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:50:31 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:50:31 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:50:31 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:50:31 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 04:50:31 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 04:50:33 [loggers.py:259] Engine 000: Avg prompt throughput: 102.5 tokens/s, Avg generation throughput: 118.7 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.6%, Prefix cache hit rate: 94.8% [repeated 39x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:50:33 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:50:33 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:50:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:50:33 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:50:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:50:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:50:33 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:50:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:50:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:50:33 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:50:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:50:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:50:33 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:50:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:50:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:50:33 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:50:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:50:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:50:33 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:50:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:50:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:50:33 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:50:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:50:33 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 04:50:33 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 04:50:38 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 145.1 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.8%, Prefix cache hit rate: 94.8% [repeated 37x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 04:50:43 [loggers.py:259] Engine 000: Avg prompt throughput: 128.7 tokens/s, Avg generation throughput: 124.7 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.2%, Prefix cache hit rate: 94.8% [repeated 38x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 04:50:48 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 145.3 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.4%, Prefix cache hit rate: 94.8% [repeated 37x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:50:52 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:50:52 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:50:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:50:52 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:50:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:50:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:50:52 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:50:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:50:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:50:52 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:50:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:50:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:50:52 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:50:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:50:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:50:52 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:50:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:50:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:50:52 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:50:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:50:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:50:52 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:50:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:50:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:50:52 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:50:52 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 04:50:53 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 145.3 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.6%, Prefix cache hit rate: 94.8% [repeated 38x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers [repeated 3x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) INFO 06-14 04:50:59 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 113.7 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.8%, Prefix cache hit rate: 95.6% [repeated 39x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) INFO 06-14 04:51:04 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 103.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.3%, Prefix cache hit rate: 95.6% [repeated 39x across cluster] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:51:05 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:51:05 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:51:05 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:51:05 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:51:05 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:51:05 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:51:05 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:51:05 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:51:05 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:51:05 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:51:05 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:51:05 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:51:05 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:51:05 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:51:05 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:51:05 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:51:05 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:51:05 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:51:05 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:51:05 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:51:05 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:51:05 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:51:05 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:51:05 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:51:05 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:51:05 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) INFO 06-14 04:51:09 [loggers.py:259] Engine 000: Avg prompt throughput: 52.0 tokens/s, Avg generation throughput: 110.5 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.1%, Prefix cache hit rate: 95.6% [repeated 38x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) ERROR 06-14 04:51:12 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) ERROR 06-14 04:51:12 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) ERROR 06-14 04:51:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) ERROR 06-14 04:51:12 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) ERROR 06-14 04:51:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) ERROR 06-14 04:51:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) ERROR 06-14 04:51:12 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) ERROR 06-14 04:51:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) ERROR 06-14 04:51:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) ERROR 06-14 04:51:12 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) ERROR 06-14 04:51:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) ERROR 06-14 04:51:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) ERROR 06-14 04:51:12 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) ERROR 06-14 04:51:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) ERROR 06-14 04:51:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) ERROR 06-14 04:51:12 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) ERROR 06-14 04:51:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) ERROR 06-14 04:51:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) ERROR 06-14 04:51:12 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) ERROR 06-14 04:51:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) ERROR 06-14 04:51:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) ERROR 06-14 04:51:12 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) ERROR 06-14 04:51:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) ERROR 06-14 04:51:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) ERROR 06-14 04:51:12 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507597, ip=10.128.34.178) ERROR 06-14 04:51:12 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) INFO 06-14 04:51:14 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 115.2 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.3%, Prefix cache hit rate: 95.6% [repeated 39x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:51:14] OK: 99 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:51:14] OK: RSS 2.02 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) INFO 06-14 04:51:19 [loggers.py:259] Engine 000: Avg prompt throughput: 77.7 tokens/s, Avg generation throughput: 97.3 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.5%, Prefix cache hit rate: 95.6% [repeated 37x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:51:21] OK: 116 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:51:21] OK: RSS 2.14 GiB | node mem 389.6/858.0 GiB used (45.4%), avail 468.4 GiB +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) INFO 06-14 04:51:24 [loggers.py:259] Engine 000: Avg prompt throughput: 131.8 tokens/s, Avg generation throughput: 63.1 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.2%, Prefix cache hit rate: 95.5% [repeated 37x across cluster] +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 04:51:24 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 04:51:24 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 04:51:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 04:51:24 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 04:51:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 04:51:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 04:51:24 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 04:51:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 04:51:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 04:51:24 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 04:51:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 04:51:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 04:51:24 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 04:51:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 04:51:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 04:51:24 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 04:51:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 04:51:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 04:51:24 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 04:51:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 04:51:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 04:51:24 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 04:51:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 04:51:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 04:51:24 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 04:51:24 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) INFO 06-14 04:51:29 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 102.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.4%, Prefix cache hit rate: 95.5% [repeated 37x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:51:27 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:51:27 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:51:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:51:27 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:51:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:51:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:51:27 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:51:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:51:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:51:27 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:51:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:51:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:51:27 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:51:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:51:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:51:27 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:51:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:51:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:51:27 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:51:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:51:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:51:27 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:51:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:51:27 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:51:27 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:51:29] OK: 115 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:51:29] OK: RSS 2.09 GiB | node mem 394.1/858.0 GiB used (45.9%), avail 463.8 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:51:32 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:51:32 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:51:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:51:32 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:51:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:51:32 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:51:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:51:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:51:32 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:51:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:51:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:51:32 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:51:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:51:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:51:32 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:51:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:51:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:51:32 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:51:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:51:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:51:32 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:51:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:51:32 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:51:32 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) INFO 06-14 04:51:34 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 102.3 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.5%, Prefix cache hit rate: 95.5% [repeated 37x across cluster] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:51:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:51:38] OK: 75 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:51:38] OK: RSS 1.94 GiB | node mem 383.9/858.0 GiB used (44.7%), avail 474.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:51:39 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:51:39 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:51:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:51:39 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:51:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:51:39 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:51:39 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:51:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:51:39 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:51:39 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:51:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:51:39 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:51:39 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:51:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:51:39 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:51:39 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:51:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:51:39 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:51:39 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:51:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:51:39 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:51:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:51:39 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:51:39 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) INFO 06-14 04:51:39 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 102.1 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.7%, Prefix cache hit rate: 95.5% [repeated 36x across cluster] +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) ERROR 06-14 04:51:39 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:51:43 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:51:43 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:51:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:51:43 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:51:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:51:43 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:51:43 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:51:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:51:43 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:51:43 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:51:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:51:43 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:51:43 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:51:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:51:43 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:51:43 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:51:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:51:43 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:51:43 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:51:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:51:43 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:51:43 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:51:43 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:51:43 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) INFO 06-14 04:51:44 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 102.0 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.8%, Prefix cache hit rate: 95.5% [repeated 37x across cluster] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:51:44 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:51:44 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:51:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:51:44 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:51:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:51:44 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:51:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:51:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:51:44 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:51:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:51:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:51:44 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:51:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:51:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:51:44 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:51:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:51:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:51:44 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:51:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:51:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:51:44 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:51:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:51:44 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:51:44 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:51:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) INFO 06-14 04:51:49 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 102.5 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.9%, Prefix cache hit rate: 95.5% [repeated 36x across cluster] +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) INFO 06-14 04:51:54 [loggers.py:259] Engine 000: Avg prompt throughput: 21.0 tokens/s, Avg generation throughput: 97.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.1%, Prefix cache hit rate: 95.5% [repeated 37x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:51:58] OK: 234 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:51:58] OK: RSS 1.92 GiB | node mem 260.4/858.0 GiB used (30.3%), avail 597.6 GiB +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) INFO 06-14 04:51:59 [loggers.py:259] Engine 000: Avg prompt throughput: 52.6 tokens/s, Avg generation throughput: 87.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.3%, Prefix cache hit rate: 95.4% [repeated 37x across cluster] +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) INFO 06-14 04:52:04 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 101.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.4%, Prefix cache hit rate: 95.4% [repeated 38x across cluster] +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) INFO 06-14 04:52:09 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 102.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.6%, Prefix cache hit rate: 95.4% [repeated 38x across cluster] +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) INFO 06-14 04:52:14 [loggers.py:259] Engine 000: Avg prompt throughput: 70.0 tokens/s, Avg generation throughput: 83.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.8%, Prefix cache hit rate: 95.5% [repeated 38x across cluster] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:52:15 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:52:15 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:52:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:52:15 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:52:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:52:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:52:15 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:52:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:52:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:52:15 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:52:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:52:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:52:15 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:52:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:52:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:52:15 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:52:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:52:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:52:15 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:52:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:52:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:52:15 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:52:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:52:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:52:15 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 04:52:15 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496912, ip=10.128.34.182) INFO 06-14 04:52:19 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 103.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.9%, Prefix cache hit rate: 95.5% [repeated 36x across cluster] +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) INFO 06-14 04:52:24 [loggers.py:259] Engine 000: Avg prompt throughput: 21.1 tokens/s, Avg generation throughput: 40.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.7%, Prefix cache hit rate: 95.0% [repeated 36x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:52:27 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:52:27 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:52:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:52:27 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:52:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:52:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:52:27 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:52:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:52:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:52:27 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:52:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:52:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:52:27 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:52:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:52:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:52:27 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:52:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:52:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:52:27 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:52:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:52:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:52:27 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:52:27 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:52:27 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:52:27 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:52:27 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) INFO 06-14 04:52:29 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 45.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.8%, Prefix cache hit rate: 95.0% [repeated 35x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new [repeated 2x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:52:30 [serving.py:315] Error in preprocessing prompt inputs [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:52:30 [serving.py:315] Traceback (most recent call last): [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:52:30 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:52:30 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:52:30 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:52:30 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:52:30 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:52:30 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:52:30 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:52:30 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:52:30 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:52:30 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:52:30 [serving.py:315] return await asyncio.gather( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:52:30 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:52:30 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:52:30 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:52:30 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:52:30 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:52:30 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:52:30 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:52:30 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:52:30 [serving.py:315] tokens = validator(tokenizer, tokens) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:52:30 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:52:30 [serving.py:315] raise VLLMValidationError( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:52:30 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) INFO 06-14 04:52:34 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 45.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.8%, Prefix cache hit rate: 95.0% [repeated 35x across cluster] +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) INFO 06-14 04:52:39 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 45.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.9%, Prefix cache hit rate: 95.0% [repeated 36x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) INFO 06-14 04:52:44 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 50.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.2%, Prefix cache hit rate: 93.5% [repeated 36x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) INFO 06-14 04:52:49 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 95.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 15.9%, Prefix cache hit rate: 95.4% [repeated 36x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 3x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) INFO 06-14 04:52:54 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 95.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 16.0%, Prefix cache hit rate: 95.4% [repeated 35x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 10x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) INFO 06-14 04:52:59 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 95.5 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 16.2%, Prefix cache hit rate: 95.4% [repeated 36x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:53:01 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:53:01 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:53:01 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:53:01 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:53:01 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:53:01 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:53:01 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:53:01 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:53:01 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:53:01 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:53:01 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:53:01 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:53:01 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:53:01 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:53:01 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:53:01 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:53:01 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:53:01 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:53:01 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:53:01 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:53:01 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:53:01 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:53:01 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:53:01 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:53:01 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 04:53:01 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) INFO 06-14 04:53:04 [loggers.py:259] Engine 000: Avg prompt throughput: 10.2 tokens/s, Avg generation throughput: 75.8 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.5%, Prefix cache hit rate: 95.4% [repeated 37x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) INFO 06-14 04:53:09 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 95.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.6%, Prefix cache hit rate: 95.4% [repeated 37x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:53:14] OK: 98 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:53:14] OK: RSS 2.02 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) INFO 06-14 04:53:14 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 95.8 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.7%, Prefix cache hit rate: 95.4% [repeated 37x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) INFO 06-14 04:53:19 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 95.8 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.9%, Prefix cache hit rate: 95.4% [repeated 38x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:53:21] OK: 103 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:53:21] OK: RSS 2.14 GiB | node mem 389.6/858.0 GiB used (45.4%), avail 468.3 GiB +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) INFO 06-14 04:53:24 [loggers.py:259] Engine 000: Avg prompt throughput: 142.6 tokens/s, Avg generation throughput: 79.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.2%, Prefix cache hit rate: 95.4% [repeated 38x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) INFO 06-14 04:53:29 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 96.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.3%, Prefix cache hit rate: 95.4% [repeated 37x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:53:29] OK: 106 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:53:29] OK: RSS 2.09 GiB | node mem 394.2/858.0 GiB used (45.9%), avail 463.8 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) INFO 06-14 04:53:34 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 96.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.4%, Prefix cache hit rate: 95.4% [repeated 38x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 8x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:53:38] OK: 61 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:53:38] OK: RSS 1.94 GiB | node mem 384.0/858.0 GiB used (44.8%), avail 474.0 GiB +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) INFO 06-14 04:53:39 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 92.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.9%, Prefix cache hit rate: 95.4% [repeated 37x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:53:41 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:53:41 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:53:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:53:41 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:53:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:53:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:53:41 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:53:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:53:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:53:41 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:53:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:53:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:53:41 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:53:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:53:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:53:41 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:53:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:53:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:53:41 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:53:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:53:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:53:41 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:53:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:53:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:53:41 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:53:41 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 2x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) INFO 06-14 04:53:44 [loggers.py:259] Engine 000: Avg prompt throughput: 244.3 tokens/s, Avg generation throughput: 76.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.0%, Prefix cache hit rate: 95.4% [repeated 38x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:53:41 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:53:41 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:53:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:53:41 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:53:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:53:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:53:41 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:53:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:53:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:53:41 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:53:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:53:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:53:41 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:53:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:53:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:53:41 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:53:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:53:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:53:41 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:53:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:53:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:53:41 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:53:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:53:41 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 04:53:41 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) INFO 06-14 04:53:50 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.9%, Prefix cache hit rate: 94.7% [repeated 40x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:53:51 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:53:51 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:53:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:53:51 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:53:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:53:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:53:51 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:53:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:53:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:53:51 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:53:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:53:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:53:51 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:53:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:53:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:53:51 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:53:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:53:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:53:51 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:53:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:53:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:53:51 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:53:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:53:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:53:51 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 04:53:51 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 3x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) INFO 06-14 04:53:55 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.0%, Prefix cache hit rate: 94.7% [repeated 38x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 7x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:53:58] OK: 225 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:53:58] OK: RSS 1.92 GiB | node mem 260.4/858.0 GiB used (30.3%), avail 597.6 GiB +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) INFO 06-14 04:54:00 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.0%, Prefix cache hit rate: 94.7% [repeated 38x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 9x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) INFO 06-14 04:54:05 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.1%, Prefix cache hit rate: 94.7% [repeated 38x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 7x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) INFO 06-14 04:54:10 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.2%, Prefix cache hit rate: 94.7% [repeated 37x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 3x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) INFO 06-14 04:54:15 [loggers.py:259] Engine 000: Avg prompt throughput: 10.8 tokens/s, Avg generation throughput: 53.3 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.4%, Prefix cache hit rate: 94.7% [repeated 38x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:54:15 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:54:15 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:54:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:54:15 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:54:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:54:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:54:15 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:54:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:54:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:54:15 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:54:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:54:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:54:15 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:54:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:54:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:54:15 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:54:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:54:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:54:15 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:54:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:54:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:54:15 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:54:15 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:54:15 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:54:15 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 04:54:15 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) INFO 06-14 04:54:20 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 95.0 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.5%, Prefix cache hit rate: 94.7% [repeated 38x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:54:25 [loggers.py:259] Engine 000: Avg prompt throughput: 52.4 tokens/s, Avg generation throughput: 143.5 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.9%, Prefix cache hit rate: 95.7% [repeated 38x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:54:30 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 143.1 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.7%, Prefix cache hit rate: 95.7% [repeated 38x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:54:35 [loggers.py:259] Engine 000: Avg prompt throughput: 177.3 tokens/s, Avg generation throughput: 158.1 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.6%, Prefix cache hit rate: 95.7% [repeated 39x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:54:40 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 164.2 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.8%, Prefix cache hit rate: 95.7% [repeated 38x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:54:45 [loggers.py:259] Engine 000: Avg prompt throughput: 106.2 tokens/s, Avg generation throughput: 149.4 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.2%, Prefix cache hit rate: 95.7% [repeated 36x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:54:50 [loggers.py:259] Engine 000: Avg prompt throughput: 169.2 tokens/s, Avg generation throughput: 118.0 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.5%, Prefix cache hit rate: 95.7% [repeated 37x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:54:55 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 159.5 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.7%, Prefix cache hit rate: 95.7% [repeated 37x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:55:00 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 159.3 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.9%, Prefix cache hit rate: 95.7% [repeated 38x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:55:05 [loggers.py:259] Engine 000: Avg prompt throughput: 89.9 tokens/s, Avg generation throughput: 144.2 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 10.1%, Prefix cache hit rate: 95.7% [repeated 36x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:55:09 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:55:09 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:55:09 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:55:09 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:55:09 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:55:09 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:55:09 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:55:09 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:55:09 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:55:09 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:55:09 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:55:09 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:55:09 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:55:09 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:55:09 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:55:09 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:55:09 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:55:09 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:55:09 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:55:09 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:55:09 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:55:09 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:55:09 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:55:09 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:55:09 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 04:55:09 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:55:10 [loggers.py:259] Engine 000: Avg prompt throughput: 764.5 tokens/s, Avg generation throughput: 128.8 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.8%, Prefix cache hit rate: 95.6% [repeated 37x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:55:14] OK: 102 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:55:14] OK: RSS 2.02 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:55:13 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:55:13 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:55:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:55:13 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:55:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:55:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:55:13 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:55:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:55:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:55:13 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:55:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:55:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:55:13 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:55:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:55:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:55:13 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:55:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:55:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:55:13 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:55:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:55:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:55:13 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:55:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:55:13 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 04:55:13 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:55:15 [loggers.py:259] Engine 000: Avg prompt throughput: 36.1 tokens/s, Avg generation throughput: 184.9 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 15.1%, Prefix cache hit rate: 95.6% [repeated 37x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:55:20 [loggers.py:259] Engine 000: Avg prompt throughput: 11.0 tokens/s, Avg generation throughput: 177.5 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.4%, Prefix cache hit rate: 95.6% [repeated 36x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:55:21] OK: 112 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:55:21] OK: RSS 2.15 GiB | node mem 389.6/858.0 GiB used (45.4%), avail 468.3 GiB +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:55:25 [loggers.py:259] Engine 000: Avg prompt throughput: 128.9 tokens/s, Avg generation throughput: 231.1 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 16.0%, Prefix cache hit rate: 95.6% [repeated 36x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:55:29 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:55:29 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:55:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:55:29 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:55:29 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:55:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:55:29 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:55:29 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:55:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:55:29 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:55:29 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:55:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:55:29 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:55:29 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:55:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:55:29 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:55:29 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:55:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:55:29 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:55:29 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:55:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:55:29 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:55:29 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:55:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:55:29 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507316, ip=10.128.34.185) ERROR 06-14 04:55:29 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:55:29] OK: 106 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:55:29] OK: RSS 2.09 GiB | node mem 394.2/858.0 GiB used (45.9%), avail 463.8 GiB +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:55:30 [loggers.py:259] Engine 000: Avg prompt throughput: 46.6 tokens/s, Avg generation throughput: 223.2 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.7%, Prefix cache hit rate: 95.6% [repeated 36x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=3946333, ip=10.128.56.73) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) ERROR 06-14 04:55:32 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) ERROR 06-14 04:55:32 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) ERROR 06-14 04:55:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) ERROR 06-14 04:55:32 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) ERROR 06-14 04:55:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) ERROR 06-14 04:55:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) ERROR 06-14 04:55:32 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) ERROR 06-14 04:55:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) ERROR 06-14 04:55:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) ERROR 06-14 04:55:32 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) ERROR 06-14 04:55:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) ERROR 06-14 04:55:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) ERROR 06-14 04:55:32 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) ERROR 06-14 04:55:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) ERROR 06-14 04:55:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) ERROR 06-14 04:55:32 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) ERROR 06-14 04:55:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) ERROR 06-14 04:55:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) ERROR 06-14 04:55:32 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) ERROR 06-14 04:55:32 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) ERROR 06-14 04:55:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) ERROR 06-14 04:55:32 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) ERROR 06-14 04:55:32 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) ERROR 06-14 04:55:32 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496911, ip=10.128.34.182) ERROR 06-14 04:55:32 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:55:35 [loggers.py:259] Engine 000: Avg prompt throughput: 163.6 tokens/s, Avg generation throughput: 217.9 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 16.9%, Prefix cache hit rate: 95.6% [repeated 35x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:55:38] OK: 61 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:55:38] OK: RSS 1.94 GiB | node mem 384.0/858.0 GiB used (44.8%), avail 474.0 GiB +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:55:40 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 244.8 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 17.2%, Prefix cache hit rate: 95.6% [repeated 36x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:55:45 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 236.2 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 16.0%, Prefix cache hit rate: 95.6% [repeated 35x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:55:50 [loggers.py:259] Engine 000: Avg prompt throughput: 35.9 tokens/s, Avg generation throughput: 241.7 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 18.0%, Prefix cache hit rate: 95.6% [repeated 36x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:55:55 [loggers.py:259] Engine 000: Avg prompt throughput: 45.1 tokens/s, Avg generation throughput: 223.7 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 18.3%, Prefix cache hit rate: 95.6% [repeated 35x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:55:56 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:55:56 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:55:56 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:55:56 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:55:56 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:55:56 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:55:56 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:55:56 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:55:56 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:55:56 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:55:56 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:55:56 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:55:56 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:55:56 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:55:56 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:55:56 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:55:56 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:55:56 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:55:56 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:55:56 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:55:56 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:55:56 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:55:56 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:55:56 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:55:56 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 04:55:56 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:55:58] OK: 231 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:55:58] OK: RSS 1.92 GiB | node mem 260.3/858.0 GiB used (30.3%), avail 597.6 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:56:00 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 228.6 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.5%, Prefix cache hit rate: 95.6% [repeated 37x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:56:05 [loggers.py:259] Engine 000: Avg prompt throughput: 46.4 tokens/s, Avg generation throughput: 226.6 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 19.0%, Prefix cache hit rate: 95.6% [repeated 34x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:56:10 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 237.6 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 17.5%, Prefix cache hit rate: 95.6% [repeated 36x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:56:15 [loggers.py:259] Engine 000: Avg prompt throughput: 136.4 tokens/s, Avg generation throughput: 225.4 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 19.9%, Prefix cache hit rate: 95.6% [repeated 36x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:56:20 [loggers.py:259] Engine 000: Avg prompt throughput: 99.6 tokens/s, Avg generation throughput: 226.7 tokens/s, Running: 6 reqs, Waiting: 0 reqs, GPU KV cache usage: 20.3%, Prefix cache hit rate: 95.6% [repeated 37x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:56:22 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:56:22 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:56:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:56:22 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:56:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:56:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:56:22 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:56:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:56:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:56:22 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:56:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:56:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:56:22 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:56:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:56:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:56:22 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:56:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:56:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:56:22 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:56:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:56:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:56:22 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:56:22 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:56:22 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:56:22 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 04:56:22 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:56:25 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 190.8 tokens/s, Running: 3 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.0%, Prefix cache hit rate: 95.6% [repeated 37x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:56:30 [loggers.py:259] Engine 000: Avg prompt throughput: 324.4 tokens/s, Avg generation throughput: 169.7 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.3%, Prefix cache hit rate: 95.6% [repeated 37x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers [repeated 15x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:56:35 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 173.8 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.9%, Prefix cache hit rate: 95.6% [repeated 36x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 7x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:56:40 [loggers.py:259] Engine 000: Avg prompt throughput: 217.5 tokens/s, Avg generation throughput: 175.3 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.1%, Prefix cache hit rate: 95.6% [repeated 38x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:56:45 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 202.3 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.4%, Prefix cache hit rate: 95.6% [repeated 38x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:56:49 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:56:49 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:56:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:56:49 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:56:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:56:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:56:49 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:56:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:56:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:56:49 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:56:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:56:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:56:49 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:56:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:56:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:56:49 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:56:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:56:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:56:49 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:56:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:56:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:56:49 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:56:49 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:56:49 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:56:49 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:56:49 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:56:50 [loggers.py:259] Engine 000: Avg prompt throughput: 126.3 tokens/s, Avg generation throughput: 188.7 tokens/s, Running: 5 reqs, Waiting: 0 reqs, GPU KV cache usage: 13.8%, Prefix cache hit rate: 95.6% [repeated 38x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:56:52 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:56:52 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:56:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:56:52 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:56:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:56:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:56:52 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:56:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:56:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:56:52 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:56:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:56:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:56:52 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:56:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:56:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:56:52 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:56:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:56:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:56:52 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:56:52 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:56:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:56:52 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:56:52 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:56:52 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:56:52 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) INFO 06-14 04:56:55 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 199.1 tokens/s, Running: 4 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.1%, Prefix cache hit rate: 95.6% [repeated 37x across cluster] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) INFO 06-14 04:57:00 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 39.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 0.8%, Prefix cache hit rate: 95.2% [repeated 39x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) INFO 06-14 04:57:05 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 60.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.8%, Prefix cache hit rate: 95.3% [repeated 39x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) INFO 06-14 04:57:11 [loggers.py:259] Engine 000: Avg prompt throughput: 216.0 tokens/s, Avg generation throughput: 92.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.2%, Prefix cache hit rate: 95.3% [repeated 37x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=3946333, ip=10.128.56.73) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:57:13 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:57:13 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:57:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:57:13 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:57:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:57:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:57:13 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:57:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:57:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:57:13 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:57:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:57:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:57:13 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:57:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:57:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:57:13 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:57:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:57:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:57:13 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:57:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:57:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:57:13 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:57:13 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:57:13 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:57:13 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 04:57:13 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:57:14] OK: 102 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:57:14] OK: RSS 2.02 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) INFO 06-14 04:57:16 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 96.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.3%, Prefix cache hit rate: 95.3% [repeated 38x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) INFO 06-14 04:57:21 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 96.0 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.5%, Prefix cache hit rate: 95.3% [repeated 38x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:57:21] OK: 99 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:57:21] OK: RSS 2.15 GiB | node mem 389.6/858.0 GiB used (45.4%), avail 468.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) INFO 06-14 04:57:26 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 53.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.3%, Prefix cache hit rate: 95.7% [repeated 39x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:57:29] OK: 116 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:57:29] OK: RSS 2.09 GiB | node mem 394.2/858.0 GiB used (45.9%), avail 463.8 GiB +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) INFO 06-14 04:57:31 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 54.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.4%, Prefix cache hit rate: 95.7% [repeated 38x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) INFO 06-14 04:57:36 [loggers.py:259] Engine 000: Avg prompt throughput: 94.0 tokens/s, Avg generation throughput: 29.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.6%, Prefix cache hit rate: 95.7% [repeated 39x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:57:38] OK: 53 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:57:38] OK: RSS 1.94 GiB | node mem 384.0/858.0 GiB used (44.8%), avail 474.0 GiB +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:57:41 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:57:41 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:57:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:57:41 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:57:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:57:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:57:41 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:57:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:57:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:57:41 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:57:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:57:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:57:41 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:57:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:57:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:57:41 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:57:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:57:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:57:41 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:57:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:57:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:57:41 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:57:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:57:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:57:41 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=323512, ip=10.128.56.67) ERROR 06-14 04:57:41 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) INFO 06-14 04:57:41 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 54.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.7%, Prefix cache hit rate: 95.7% [repeated 38x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) INFO 06-14 04:57:46 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 53.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.7%, Prefix cache hit rate: 95.7% [repeated 38x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) INFO 06-14 04:57:51 [loggers.py:259] Engine 000: Avg prompt throughput: 136.1 tokens/s, Avg generation throughput: 30.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.0%, Prefix cache hit rate: 95.8% [repeated 37x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 2x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) INFO 06-14 04:57:56 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 53.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.0%, Prefix cache hit rate: 95.8% [repeated 38x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers [repeated 5x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:57:58] OK: 233 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:57:58] OK: RSS 1.93 GiB | node mem 260.3/858.0 GiB used (30.3%), avail 597.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=3946333, ip=10.128.56.73) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:57:59 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:57:59 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:57:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:57:59 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:57:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:57:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:57:59 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:57:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:57:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:57:59 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:57:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:57:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:57:59 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:57:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:57:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:57:59 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:57:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:57:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:57:59 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:57:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:57:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:57:59 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:57:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:57:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:57:59 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3942128, ip=10.128.56.76) ERROR 06-14 04:57:59 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) INFO 06-14 04:58:01 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 54.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.1%, Prefix cache hit rate: 95.8% [repeated 38x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:58:00 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:58:00 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:58:00 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:58:00 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:58:00 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:58:00 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:58:00 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:58:00 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:58:00 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:58:00 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:58:00 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:58:00 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:58:00 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:58:00 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:58:00 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:58:00 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:58:00 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:58:00 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:58:00 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:58:00 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:58:00 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:58:00 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:58:00 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:58:00 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 04:58:00 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) INFO 06-14 04:58:06 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 54.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.2%, Prefix cache hit rate: 95.8% [repeated 38x across cluster] +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) INFO 06-14 04:58:11 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 54.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.3%, Prefix cache hit rate: 95.8% [repeated 37x across cluster] +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) INFO 06-14 04:58:16 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 54.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.3%, Prefix cache hit rate: 95.8% [repeated 37x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:58:18 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:58:18 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:58:18 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:58:18 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:58:18 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:58:18 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:58:18 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:58:18 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:58:18 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:58:18 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:58:18 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:58:18 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:58:18 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:58:18 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:58:18 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:58:18 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:58:18 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:58:18 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:58:18 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:58:18 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:58:18 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:58:18 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:58:18 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:58:18 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:58:18 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) ERROR 06-14 04:58:18 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) INFO 06-14 04:58:21 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 54.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.4%, Prefix cache hit rate: 95.8% [repeated 39x across cluster] +(AsyncVLLMInferenceEngine pid=1507315, ip=10.128.34.185) INFO 06-14 04:58:26 [loggers.py:259] Engine 000: Avg prompt throughput: 265.6 tokens/s, Avg generation throughput: 23.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.8%, Prefix cache hit rate: 95.7% [repeated 38x across cluster] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) INFO 06-14 04:58:31 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 44.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.0%, Prefix cache hit rate: 95.9% [repeated 39x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:58:33 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:58:33 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:58:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:58:33 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:58:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:58:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:58:33 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:58:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:58:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:58:33 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:58:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:58:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:58:33 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:58:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:58:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:58:33 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:58:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:58:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:58:33 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:58:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:58:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:58:33 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:58:33 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:58:33 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:58:33 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3942257, ip=10.128.56.76) ERROR 06-14 04:58:33 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) INFO 06-14 04:58:36 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 44.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.1%, Prefix cache hit rate: 95.9% [repeated 37x across cluster] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) INFO 06-14 04:58:41 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 44.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.1%, Prefix cache hit rate: 95.9% [repeated 37x across cluster] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) INFO 06-14 04:58:46 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 44.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.2%, Prefix cache hit rate: 95.9% [repeated 36x across cluster] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:58:48 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:58:48 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:58:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:58:48 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:58:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:58:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:58:48 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:58:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:58:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:58:48 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:58:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:58:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:58:48 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:58:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:58:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:58:48 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:58:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:58:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:58:48 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:58:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:58:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:58:48 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:58:48 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:58:48 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:58:48 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507805, ip=10.128.34.181) ERROR 06-14 04:58:48 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) INFO 06-14 04:58:51 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 44.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.3%, Prefix cache hit rate: 95.9% [repeated 37x across cluster] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) INFO 06-14 04:58:56 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 44.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.3%, Prefix cache hit rate: 95.9% [repeated 36x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:58:59 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:58:59 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:58:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:58:59 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:58:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:58:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:58:59 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:58:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:58:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:58:59 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:58:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:58:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:58:59 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:58:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:58:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:58:59 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:58:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:58:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:58:59 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:58:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:58:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:58:59 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:58:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:58:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:58:59 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 04:58:59 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) INFO 06-14 04:59:01 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 44.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.4%, Prefix cache hit rate: 95.9% [repeated 36x across cluster] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) INFO 06-14 04:59:06 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 44.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 2.5%, Prefix cache hit rate: 95.9% [repeated 37x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) INFO 06-14 04:59:11 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 44.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.3%, Prefix cache hit rate: 93.7% [repeated 38x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:59:14] OK: 95 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [04:59:14] OK: RSS 2.02 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 04:59:16 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 48.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.6%, Prefix cache hit rate: 95.1% [repeated 36x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:59:21] OK: 85 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [04:59:21] OK: RSS 2.15 GiB | node mem 389.6/858.0 GiB used (45.4%), avail 468.4 GiB +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 04:59:21 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 48.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.7%, Prefix cache hit rate: 95.1% [repeated 35x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 04:59:26 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 48.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.7%, Prefix cache hit rate: 95.1% [repeated 34x across cluster] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:59:29 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:59:29 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:59:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:59:29 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:59:29 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:59:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:59:29 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:59:29 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:59:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:59:29 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:59:29 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:59:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:59:29 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:59:29 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:59:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:59:29 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:59:29 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:59:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:59:29 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:59:29 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:59:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:59:29 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:59:29 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:59:29 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:59:29 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507972, ip=10.128.34.179) ERROR 06-14 04:59:29 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:59:29] OK: 114 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [04:59:29] OK: RSS 2.09 GiB | node mem 394.2/858.0 GiB used (46.0%), avail 463.7 GiB +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 04:59:31 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 48.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.8%, Prefix cache hit rate: 95.1% [repeated 34x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 04:59:36 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 48.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.9%, Prefix cache hit rate: 95.1% [repeated 33x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:59:38] OK: 51 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [04:59:38] OK: RSS 1.94 GiB | node mem 384.0/858.0 GiB used (44.8%), avail 474.0 GiB +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 04:59:41 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 48.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.9%, Prefix cache hit rate: 95.1% [repeated 33x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:59:44 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:59:44 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:59:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:59:44 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:59:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:59:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:59:44 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:59:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:59:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:59:44 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:59:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:59:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:59:44 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:59:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:59:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:59:44 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:59:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:59:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:59:44 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:59:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:59:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:59:44 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:59:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:59:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:59:44 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3942255, ip=10.128.56.76) ERROR 06-14 04:59:44 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 04:59:46 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 48.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.0%, Prefix cache hit rate: 95.1% [repeated 32x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 04:59:51 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 48.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.1%, Prefix cache hit rate: 95.1% [repeated 33x across cluster] +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) INFO 06-14 04:59:57 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 43.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.5%, Prefix cache hit rate: 93.2% [repeated 33x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:59:58] OK: 223 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [04:59:58] OK: RSS 1.94 GiB | node mem 260.4/858.0 GiB used (30.3%), avail 597.6 GiB +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) INFO 06-14 05:00:02 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 42.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.5%, Prefix cache hit rate: 93.2% [repeated 33x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) INFO 06-14 05:00:07 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 42.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.6%, Prefix cache hit rate: 93.2% [repeated 33x across cluster] +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) INFO 06-14 05:00:12 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 42.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.6%, Prefix cache hit rate: 93.2% [repeated 33x across cluster] +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 05:00:12 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 05:00:12 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 05:00:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 05:00:12 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 05:00:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 05:00:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 05:00:12 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 05:00:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 05:00:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 05:00:12 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 05:00:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 05:00:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 05:00:12 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 05:00:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 05:00:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 05:00:12 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 05:00:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 05:00:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 05:00:12 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 05:00:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 05:00:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 05:00:12 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 05:00:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 05:00:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 05:00:12 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507596, ip=10.128.34.178) ERROR 06-14 05:00:12 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) INFO 06-14 05:00:17 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 41.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.7%, Prefix cache hit rate: 93.2% [repeated 32x across cluster] +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) INFO 06-14 05:00:22 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 41.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.7%, Prefix cache hit rate: 93.2% [repeated 32x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) INFO 06-14 05:00:27 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 41.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.8%, Prefix cache hit rate: 93.2% [repeated 33x across cluster] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:00:28 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:00:28 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:00:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:00:28 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:00:28 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:00:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:00:28 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:00:28 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:00:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:00:28 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:00:28 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:00:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:00:28 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:00:28 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:00:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:00:28 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:00:28 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:00:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:00:28 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:00:28 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:00:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:00:28 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:00:28 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:00:28 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:00:28 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:00:28 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) INFO 06-14 05:00:32 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 41.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.9%, Prefix cache hit rate: 93.2% [repeated 32x across cluster] +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) INFO 06-14 05:00:37 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 41.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.9%, Prefix cache hit rate: 93.2% [repeated 31x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:00:38 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:00:38 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:00:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:00:38 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:00:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:00:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:00:38 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:00:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:00:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:00:38 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:00:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:00:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:00:38 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:00:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:00:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:00:38 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:00:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:00:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:00:38 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:00:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:00:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:00:38 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:00:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:00:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:00:38 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:00:38 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) INFO 06-14 05:00:42 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 41.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.0%, Prefix cache hit rate: 93.2% [repeated 32x across cluster] +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) INFO 06-14 05:00:47 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 41.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.0%, Prefix cache hit rate: 93.2% [repeated 32x across cluster] +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) INFO 06-14 05:00:52 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 40.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.1%, Prefix cache hit rate: 93.2% [repeated 33x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 05:00:55 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 05:00:55 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 05:00:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 05:00:55 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 05:00:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 05:00:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 05:00:55 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 05:00:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 05:00:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 05:00:55 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 05:00:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 05:00:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 05:00:55 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 05:00:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 05:00:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 05:00:55 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 05:00:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 05:00:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 05:00:55 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 05:00:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 05:00:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 05:00:55 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 05:00:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 05:00:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 05:00:55 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507441, ip=10.128.34.185) ERROR 06-14 05:00:55 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) INFO 06-14 05:00:57 [loggers.py:259] Engine 000: Avg prompt throughput: 88.6 tokens/s, Avg generation throughput: 32.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.5%, Prefix cache hit rate: 96.1% [repeated 31x across cluster] +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) INFO 06-14 05:01:02 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.5%, Prefix cache hit rate: 96.1% [repeated 31x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:01:07 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 78.1 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.4%, Prefix cache hit rate: 96.2% [repeated 32x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:01:07 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:01:07 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:01:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:01:07 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:01:07 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:01:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:01:07 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:01:07 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:01:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:01:07 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:01:07 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:01:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:01:07 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:01:07 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:01:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:01:07 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:01:07 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:01:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:01:07 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:01:07 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:01:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:01:07 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:01:07 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:01:07 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:01:07 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507806, ip=10.128.34.181) ERROR 06-14 05:01:07 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:01:12 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 76.3 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.5%, Prefix cache hit rate: 96.2% [repeated 31x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:01:14] OK: 86 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:01:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:01:17 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 75.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.6%, Prefix cache hit rate: 96.2% [repeated 30x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:01:21] OK: 74 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:01:21] OK: RSS 2.15 GiB | node mem 389.6/858.0 GiB used (45.4%), avail 468.4 GiB +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:01:22 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 75.0 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.7%, Prefix cache hit rate: 96.2% [repeated 31x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:01:27 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 76.1 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.8%, Prefix cache hit rate: 96.2% [repeated 31x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:01:29] OK: 116 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:01:29] OK: RSS 2.09 GiB | node mem 394.3/858.0 GiB used (46.0%), avail 463.7 GiB +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:01:32 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 75.5 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.9%, Prefix cache hit rate: 96.2% [repeated 30x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:01:37 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 76.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.0%, Prefix cache hit rate: 96.2% [repeated 30x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:01:38] OK: 50 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:01:38] OK: RSS 1.94 GiB | node mem 384.0/858.0 GiB used (44.8%), avail 474.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:01:42 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 76.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.1%, Prefix cache hit rate: 96.2% [repeated 30x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:01:47 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 75.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.2%, Prefix cache hit rate: 96.2% [repeated 29x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:01:52 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 76.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.3%, Prefix cache hit rate: 96.2% [repeated 28x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:01:57 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 77.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.5%, Prefix cache hit rate: 96.2% [repeated 28x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:01:58] OK: 214 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:01:58] OK: RSS 1.94 GiB | node mem 260.4/858.0 GiB used (30.4%), avail 597.6 GiB +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:02:02 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 75.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.6%, Prefix cache hit rate: 96.2% [repeated 28x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:02:05 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:02:05 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:02:05 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:02:05 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:02:05 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:02:05 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:02:05 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:02:05 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:02:05 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:02:05 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:02:05 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:02:05 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:02:05 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:02:05 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:02:05 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:02:05 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:02:05 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:02:05 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:02:05 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:02:05 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:02:05 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:02:05 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:02:05 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:02:05 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:02:05 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:02:05 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:02:07 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 76.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.7%, Prefix cache hit rate: 96.2% [repeated 28x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:02:12 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 75.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.8%, Prefix cache hit rate: 96.2% [repeated 27x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 05:02:14 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 05:02:14 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 05:02:14 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 05:02:14 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 05:02:14 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 05:02:14 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 05:02:14 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 05:02:14 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 05:02:14 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 05:02:14 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 05:02:14 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 05:02:14 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 05:02:14 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 05:02:14 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 05:02:14 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 05:02:14 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 05:02:14 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 05:02:14 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 05:02:14 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 05:02:14 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 05:02:14 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 05:02:14 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 05:02:14 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 05:02:14 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 05:02:14 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=4037603, ip=10.128.56.68) ERROR 06-14 05:02:14 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:02:17 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 76.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.9%, Prefix cache hit rate: 96.2% [repeated 28x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=3946333, ip=10.128.56.73) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=3946333, ip=10.128.56.73) +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:02:22 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 76.3 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.0%, Prefix cache hit rate: 96.2% [repeated 27x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:02:27 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 76.3 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.1%, Prefix cache hit rate: 96.2% [repeated 27x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:02:32 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 76.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.2%, Prefix cache hit rate: 96.2% [repeated 27x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:02:38 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.1%, Prefix cache hit rate: 96.7% [repeated 28x across cluster] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:02:38 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:02:38 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:02:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:02:38 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:02:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:02:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:02:38 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:02:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:02:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:02:38 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:02:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:02:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:02:38 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:02:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:02:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:02:38 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:02:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:02:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:02:38 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:02:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:02:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:02:38 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:02:38 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:02:38 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:02:38 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:02:38 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:02:43 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 73.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.2%, Prefix cache hit rate: 96.7% [repeated 27x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:02:48 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.3%, Prefix cache hit rate: 96.7% [repeated 27x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:02:53 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 72.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.4%, Prefix cache hit rate: 96.7% [repeated 25x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:02:58 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 71.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.5%, Prefix cache hit rate: 96.7% [repeated 26x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:03:03 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 72.1 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.6%, Prefix cache hit rate: 96.7% [repeated 26x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:03:08 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 73.1 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.7%, Prefix cache hit rate: 96.7% [repeated 26x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:03:13 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.8%, Prefix cache hit rate: 96.7% [repeated 25x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:03:14] OK: 78 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:03:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:03:18 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 73.8 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.9%, Prefix cache hit rate: 96.7% [repeated 25x across cluster] +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 05:03:19 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 05:03:19 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 05:03:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 05:03:19 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 05:03:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 05:03:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 05:03:19 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 05:03:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 05:03:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 05:03:19 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 05:03:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 05:03:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 05:03:19 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 05:03:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 05:03:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 05:03:19 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 05:03:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 05:03:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 05:03:19 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 05:03:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 05:03:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 05:03:19 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 05:03:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 05:03:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 05:03:19 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496076, ip=10.128.34.183) ERROR 06-14 05:03:19 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:03:21] OK: 69 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:03:21] OK: RSS 2.15 GiB | node mem 389.6/858.0 GiB used (45.4%), avail 468.3 GiB +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:03:23 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 73.1 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.0%, Prefix cache hit rate: 96.7% [repeated 24x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:03:24 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:03:24 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:03:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:03:24 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:03:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:03:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:03:24 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:03:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:03:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:03:24 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:03:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:03:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:03:24 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:03:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:03:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:03:24 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:03:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:03:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:03:24 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:03:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:03:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:03:24 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:03:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:03:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:03:24 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:03:24 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:03:28 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.0 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.1%, Prefix cache hit rate: 96.7% [repeated 24x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:03:29] OK: 106 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:03:29] OK: RSS 2.09 GiB | node mem 394.3/858.0 GiB used (46.0%), avail 463.7 GiB +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:03:25 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:03:25 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:03:25 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:03:25 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:03:25 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:03:25 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:03:25 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:03:25 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:03:25 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:03:25 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:03:25 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:03:25 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:03:25 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:03:25 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:03:25 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:03:25 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:03:25 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:03:25 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:03:25 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:03:25 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:03:25 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:03:25 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:03:25 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:03:25 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:03:25 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:03:33 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.2%, Prefix cache hit rate: 96.7% [repeated 23x across cluster] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:03:35 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:03:35 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:03:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:03:35 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:03:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:03:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:03:35 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:03:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:03:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:03:35 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:03:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:03:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:03:35 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:03:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:03:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:03:35 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:03:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:03:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:03:35 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:03:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:03:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:03:35 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:03:35 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:03:35 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:03:35 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:03:35 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:03:38] OK: 49 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:03:38] OK: RSS 1.94 GiB | node mem 384.0/858.0 GiB used (44.8%), avail 473.9 GiB +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:03:38 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.3%, Prefix cache hit rate: 96.7% [repeated 23x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:03:43 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 73.1 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.4%, Prefix cache hit rate: 96.7% [repeated 23x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:03:47 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:03:47 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:03:47 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:03:47 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:03:47 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:03:47 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:03:47 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:03:47 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:03:47 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:03:47 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:03:47 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:03:47 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:03:47 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:03:47 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:03:47 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:03:47 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:03:47 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:03:47 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:03:47 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:03:47 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:03:47 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:03:47 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:03:47 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:03:47 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:03:47 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:03:47 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:03:48 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 72.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.5%, Prefix cache hit rate: 96.7% [repeated 23x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:03:53 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.5 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.6%, Prefix cache hit rate: 96.7% [repeated 23x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:03:58 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.0 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.7%, Prefix cache hit rate: 96.7% [repeated 23x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:03:58] OK: 204 / 131,072 FDs open (0.2% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:03:58] OK: RSS 1.95 GiB | node mem 260.4/858.0 GiB used (30.4%), avail 597.6 GiB +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:04:03 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 73.1 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.8%, Prefix cache hit rate: 96.7% [repeated 23x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:04:08 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 72.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.9%, Prefix cache hit rate: 96.7% [repeated 23x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:04:13 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 73.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.0%, Prefix cache hit rate: 96.7% [repeated 23x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:04:18 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 73.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.1%, Prefix cache hit rate: 96.7% [repeated 23x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:04:23 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.2%, Prefix cache hit rate: 96.7% [repeated 23x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:04:28 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.3%, Prefix cache hit rate: 96.7% [repeated 24x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:04:33 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 73.3 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.4%, Prefix cache hit rate: 96.7% [repeated 24x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:04:38 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.1 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.5%, Prefix cache hit rate: 96.7% [repeated 24x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:04:41 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:04:41 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:04:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:04:41 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:04:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:04:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:04:41 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:04:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:04:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:04:41 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:04:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:04:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:04:41 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:04:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:04:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:04:41 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:04:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:04:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:04:41 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:04:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:04:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:04:41 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:04:41 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:04:41 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:04:41 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496074, ip=10.128.34.183) ERROR 06-14 05:04:41 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:04:43 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 73.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.6%, Prefix cache hit rate: 96.7% [repeated 22x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 05:04:42 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 05:04:42 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 05:04:42 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 05:04:42 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 05:04:42 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 05:04:42 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 05:04:42 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 05:04:42 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 05:04:42 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 05:04:42 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 05:04:42 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 05:04:42 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 05:04:42 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 05:04:42 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 05:04:42 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 05:04:42 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 05:04:42 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 05:04:42 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 05:04:42 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 05:04:42 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 05:04:42 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 05:04:42 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 05:04:42 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 05:04:42 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3945545, ip=10.128.56.66) ERROR 06-14 05:04:42 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:04:48 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.0 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.7%, Prefix cache hit rate: 96.7% [repeated 22x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:04:53 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.8%, Prefix cache hit rate: 96.7% [repeated 21x across cluster] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 05:04:55 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 05:04:55 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 05:04:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 05:04:55 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 05:04:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 05:04:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 05:04:55 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 05:04:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 05:04:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 05:04:55 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 05:04:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 05:04:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 05:04:55 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 05:04:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 05:04:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 05:04:55 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 05:04:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 05:04:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 05:04:55 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 05:04:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 05:04:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 05:04:55 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 05:04:55 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 05:04:55 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 05:04:55 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=153532, ip=10.128.56.65) ERROR 06-14 05:04:55 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:04:58 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.9%, Prefix cache hit rate: 96.7% [repeated 21x across cluster] +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 05:05:02 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 05:05:02 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 05:05:02 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 05:05:02 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 05:05:02 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 05:05:02 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 05:05:02 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 05:05:02 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 05:05:02 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 05:05:02 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 05:05:02 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 05:05:02 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 05:05:02 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 05:05:02 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 05:05:02 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 05:05:02 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 05:05:02 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 05:05:02 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 05:05:02 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 05:05:02 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 05:05:02 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 05:05:02 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 05:05:02 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 05:05:02 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 05:05:02 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) ERROR 06-14 05:05:02 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:05:03 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 73.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.0%, Prefix cache hit rate: 96.7% [repeated 20x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:05:08 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.2%, Prefix cache hit rate: 96.7% [repeated 20x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:05:13 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.0 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.3%, Prefix cache hit rate: 96.7% [repeated 20x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:05:14] OK: 71 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:05:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:05:18 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 73.5 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.4%, Prefix cache hit rate: 96.7% [repeated 20x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:05:21] OK: 59 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:05:21] OK: RSS 2.15 GiB | node mem 389.6/858.0 GiB used (45.4%), avail 468.3 GiB +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:05:23 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 75.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.5%, Prefix cache hit rate: 96.7% [repeated 20x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:05:24 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:05:24 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:05:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:05:24 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:05:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:05:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:05:24 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:05:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:05:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:05:24 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:05:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:05:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:05:24 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:05:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:05:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:05:24 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:05:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:05:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:05:24 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:05:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:05:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:05:24 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:05:24 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:05:24 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:05:24 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496910, ip=10.128.34.182) ERROR 06-14 05:05:24 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:05:28 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 75.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.6%, Prefix cache hit rate: 96.7% [repeated 19x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:05:29] OK: 90 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:05:29] OK: RSS 2.09 GiB | node mem 394.3/858.0 GiB used (46.0%), avail 463.6 GiB +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:05:33 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.7%, Prefix cache hit rate: 96.7% [repeated 18x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:05:38] OK: 49 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:05:38] OK: RSS 1.94 GiB | node mem 384.1/858.0 GiB used (44.8%), avail 473.9 GiB +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:05:38 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.8%, Prefix cache hit rate: 96.7% [repeated 19x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:05:43 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.9%, Prefix cache hit rate: 96.7% [repeated 19x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:05:45 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:05:45 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:05:45 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:05:45 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:05:45 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:05:45 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:05:45 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:05:45 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:05:45 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:05:45 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:05:45 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:05:45 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:05:45 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:05:45 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:05:45 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:05:45 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:05:45 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:05:45 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:05:45 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:05:45 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:05:45 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:05:45 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:05:45 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:05:45 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:05:45 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:05:45 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:05:48 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 75.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.0%, Prefix cache hit rate: 96.7% [repeated 19x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:05:53 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 72.8 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.1%, Prefix cache hit rate: 96.7% [repeated 19x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:05:58] OK: 193 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:05:58] OK: RSS 1.96 GiB | node mem 260.3/858.0 GiB used (30.3%), avail 597.6 GiB +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:05:58 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.2%, Prefix cache hit rate: 96.7% [repeated 18x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:06:03 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.3 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.3%, Prefix cache hit rate: 96.7% [repeated 19x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:06:08 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.4%, Prefix cache hit rate: 96.7% [repeated 19x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:06:13 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 73.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.5%, Prefix cache hit rate: 96.7% [repeated 19x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:06:19 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 38.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.2%, Prefix cache hit rate: 95.1% [repeated 20x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Provider List: https://docs.litellm.ai/docs/providers +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:06:24 [loggers.py:259] Engine 000: Avg prompt throughput: 79.2 tokens/s, Avg generation throughput: 20.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.3%, Prefix cache hit rate: 95.1% [repeated 19x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:06:29 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 38.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.3%, Prefix cache hit rate: 95.1% [repeated 19x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:06:34 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 38.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.4%, Prefix cache hit rate: 95.1% [repeated 19x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:06:34 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:06:34 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:06:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:06:34 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:06:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:06:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:06:34 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:06:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:06:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:06:34 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:06:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:06:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:06:34 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:06:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:06:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:06:34 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:06:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:06:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:06:34 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:06:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:06:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:06:34 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:06:34 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:06:34 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:06:34 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:06:34 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) INFO 06-14 05:06:39 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 57.0 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 17.5%, Prefix cache hit rate: 94.7% [repeated 19x across cluster] +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) INFO 06-14 05:06:44 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 46.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.9%, Prefix cache hit rate: 94.7% [repeated 19x across cluster] +(AsyncVLLMInferenceEngine pid=3945415, ip=10.128.56.66) INFO 06-14 05:06:49 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 29.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.0%, Prefix cache hit rate: 94.7% [repeated 19x across cluster] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:06:51 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:06:51 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:06:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:06:51 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:06:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:06:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:06:51 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:06:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:06:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:06:51 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:06:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:06:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:06:51 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:06:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:06:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:06:51 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:06:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:06:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:06:51 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:06:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:06:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:06:51 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:06:51 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:06:51 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:06:51 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:06:51 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) INFO 06-14 05:06:54 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 43.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.1%, Prefix cache hit rate: 96.1% [repeated 19x across cluster] +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 05:06:57 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 05:06:57 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 05:06:57 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 05:06:57 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 05:06:57 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 05:06:57 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 05:06:57 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 05:06:57 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 05:06:57 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 05:06:57 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 05:06:57 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 05:06:57 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 05:06:57 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 05:06:57 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 05:06:57 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 05:06:57 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 05:06:57 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 05:06:57 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 05:06:57 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 05:06:57 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 05:06:57 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 05:06:57 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 05:06:57 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 05:06:57 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 05:06:57 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507676, ip=10.128.34.181) ERROR 06-14 05:06:57 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) INFO 06-14 05:06:59 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 43.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.1%, Prefix cache hit rate: 96.1% [repeated 18x across cluster] +(AsyncVLLMInferenceEngine pid=3945543, ip=10.128.56.66) INFO 06-14 05:07:04 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 43.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.2%, Prefix cache hit rate: 96.1% [repeated 17x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:07:09 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 38.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.0%, Prefix cache hit rate: 95.1% [repeated 17x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 05:07:10 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 05:07:10 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 05:07:10 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 05:07:10 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 05:07:10 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 05:07:10 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 05:07:10 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 05:07:10 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 05:07:10 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 05:07:10 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 05:07:10 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 05:07:10 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 05:07:10 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 05:07:10 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 05:07:10 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 05:07:10 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 05:07:10 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 05:07:10 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 05:07:10 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 05:07:10 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 05:07:10 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 05:07:10 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 05:07:10 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 05:07:10 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 05:07:10 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3942256, ip=10.128.56.76) ERROR 06-14 05:07:10 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:07:14] OK: 61 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:07:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:07:14 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 38.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.0%, Prefix cache hit rate: 95.1% [repeated 15x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:07:16 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:07:16 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:07:16 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:07:16 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:07:16 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:07:16 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:07:16 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:07:16 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:07:16 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:07:16 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:07:16 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:07:16 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:07:16 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:07:16 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:07:16 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:07:16 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:07:16 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:07:16 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:07:16 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:07:16 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:07:16 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:07:16 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:07:16 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:07:16 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:07:16 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=3945857, ip=10.128.56.73) ERROR 06-14 05:07:16 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:07:19 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 38.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.1%, Prefix cache hit rate: 95.1% [repeated 14x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:07:21] OK: 54 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:07:21] OK: RSS 2.15 GiB | node mem 389.6/858.0 GiB used (45.4%), avail 468.3 GiB +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:07:24 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 38.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.1%, Prefix cache hit rate: 95.1% [repeated 14x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:07:29 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 38.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.2%, Prefix cache hit rate: 95.1% [repeated 14x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:07:29] OK: 83 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:07:29] OK: RSS 2.09 GiB | node mem 394.3/858.0 GiB used (46.0%), avail 463.6 GiB +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:07:34 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 38.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.2%, Prefix cache hit rate: 95.1% [repeated 14x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:07:38] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:07:38] OK: RSS 1.89 GiB | node mem 384.0/858.0 GiB used (44.8%), avail 473.9 GiB +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:07:39 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 38.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.3%, Prefix cache hit rate: 95.1% [repeated 14x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:07:44 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 38.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.3%, Prefix cache hit rate: 95.1% [repeated 14x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:07:49 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.4%, Prefix cache hit rate: 95.1% [repeated 14x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:07:54 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.4%, Prefix cache hit rate: 95.1% [repeated 14x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:07:58] OK: 151 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:07:58] OK: RSS 1.96 GiB | node mem 260.4/858.0 GiB used (30.3%), avail 597.6 GiB +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:07:59 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:07:59 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:07:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:07:59 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:07:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:07:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:07:59 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:07:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:07:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:07:59 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:07:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:07:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:07:59 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:07:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:07:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:07:59 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:07:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:07:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:07:59 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:07:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:07:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:07:59 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:07:59 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:07:59 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:07:59 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:07:59 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:07:59 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.5%, Prefix cache hit rate: 95.1% [repeated 14x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:08:04 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.5%, Prefix cache hit rate: 95.1% [repeated 14x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:08:09 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.6%, Prefix cache hit rate: 95.1% [repeated 14x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:08:14 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 38.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.6%, Prefix cache hit rate: 95.1% [repeated 14x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 05:08:18 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 05:08:18 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 05:08:18 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 05:08:18 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 05:08:18 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 05:08:18 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 05:08:18 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 05:08:18 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 05:08:18 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 05:08:18 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 05:08:18 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 05:08:18 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 05:08:18 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 05:08:18 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 05:08:18 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 05:08:18 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 05:08:18 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 05:08:18 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 05:08:18 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 05:08:18 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 05:08:18 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 05:08:18 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 05:08:18 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 05:08:18 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 05:08:18 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507188, ip=10.128.34.185) ERROR 06-14 05:08:18 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:08:19 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 38.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.7%, Prefix cache hit rate: 95.1% [repeated 13x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new [repeated 2x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:20 [serving.py:315] Error in preprocessing prompt inputs [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:20 [serving.py:315] Traceback (most recent call last): [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:20 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:20 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:20 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:20 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:20 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:20 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:20 [serving.py:315] return await asyncio.gather( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:20 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:20 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:20 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:20 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:20 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:20 [serving.py:315] tokens = validator(tokenizer, tokens) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:20 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:20 [serving.py:315] raise VLLMValidationError( [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:20 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:08:24 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.7%, Prefix cache hit rate: 95.1% [repeated 13x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:08:29 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.8%, Prefix cache hit rate: 95.1% [repeated 13x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:08:34 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.9%, Prefix cache hit rate: 95.1% [repeated 13x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:08:39 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.9%, Prefix cache hit rate: 95.1% [repeated 13x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:44 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:44 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:44 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:44 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:44 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:44 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:44 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:44 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:44 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:44 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:44 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:44 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=153667, ip=10.128.56.65) ERROR 06-14 05:08:44 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:08:44 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.0%, Prefix cache hit rate: 95.1% [repeated 12x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:08:49 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.0%, Prefix cache hit rate: 95.1% [repeated 11x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:08:54 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.1%, Prefix cache hit rate: 95.1% [repeated 11x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:08:59 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.1%, Prefix cache hit rate: 95.1% [repeated 11x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:09:05 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.2%, Prefix cache hit rate: 95.1% [repeated 11x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:09:10 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.2%, Prefix cache hit rate: 95.1% [repeated 11x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:09:14] OK: 58 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:09:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:09:14 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:09:14 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:09:14 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:09:14 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:09:14 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:09:14 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:09:14 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:09:14 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:09:14 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:09:14 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:09:14 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:09:14 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:09:14 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:09:14 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:09:14 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:09:14 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:09:14 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:09:14 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:09:14 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:09:14 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:09:14 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:09:14 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:09:14 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:09:14 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:09:14 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=323386, ip=10.128.56.67) ERROR 06-14 05:09:14 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:09:15 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.3%, Prefix cache hit rate: 95.1% [repeated 10x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:09:20 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.3%, Prefix cache hit rate: 95.1% [repeated 9x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:09:21] OK: 51 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:09:21] OK: RSS 2.15 GiB | node mem 389.6/858.0 GiB used (45.4%), avail 468.3 GiB +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:09:25 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.4%, Prefix cache hit rate: 95.1% [repeated 9x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:09:29] OK: 65 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:09:29] OK: RSS 2.10 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:09:30 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.4%, Prefix cache hit rate: 95.1% [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:09:35 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.5%, Prefix cache hit rate: 95.1% [repeated 9x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:09:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:09:38] OK: RSS 1.89 GiB | node mem 384.1/858.0 GiB used (44.8%), avail 473.9 GiB +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:09:40 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.5%, Prefix cache hit rate: 95.1% [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:09:45 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.6%, Prefix cache hit rate: 95.1% [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:09:50 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.6%, Prefix cache hit rate: 95.1% [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:09:55 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.7%, Prefix cache hit rate: 95.1% [repeated 9x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:09:58] OK: 140 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:09:58] OK: RSS 1.97 GiB | node mem 260.4/858.0 GiB used (30.3%), avail 597.6 GiB +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:10:00 [loggers.py:259] Engine 000: Avg prompt throughput: 379.8 tokens/s, Avg generation throughput: 16.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.8%, Prefix cache hit rate: 95.1% [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:10:05 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.8%, Prefix cache hit rate: 95.1% [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:10:10 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.9%, Prefix cache hit rate: 95.1% [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:10:15 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.9%, Prefix cache hit rate: 95.1% [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:10:19 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:10:19 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:10:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:10:19 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:10:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:10:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:10:19 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:10:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:10:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:10:19 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:10:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:10:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:10:19 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:10:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:10:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:10:19 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:10:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:10:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:10:19 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:10:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:10:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:10:19 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:10:19 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:10:19 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:10:19 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:10:19 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:10:20 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.0%, Prefix cache hit rate: 95.1% [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:10:25 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.0%, Prefix cache hit rate: 95.1% [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:10:30 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.1%, Prefix cache hit rate: 95.1% [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:10:35 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.1%, Prefix cache hit rate: 95.1% [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:10:39 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:10:39 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:10:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:10:39 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:10:39 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:10:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:10:39 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:10:39 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:10:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:10:39 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:10:39 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:10:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:10:39 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:10:39 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:10:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:10:39 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:10:39 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:10:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:10:39 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:10:39 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:10:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:10:39 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:10:39 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:10:39 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:10:39 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496075, ip=10.128.34.183) ERROR 06-14 05:10:39 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:10:40 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.2%, Prefix cache hit rate: 95.1% [repeated 9x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:10:45 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.2%, Prefix cache hit rate: 95.1% [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:10:50 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.3%, Prefix cache hit rate: 95.1% [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:10:55 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.3%, Prefix cache hit rate: 95.1% [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:11:00 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.4%, Prefix cache hit rate: 95.1% [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:11:05 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.4%, Prefix cache hit rate: 95.1% [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:11:10 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.5%, Prefix cache hit rate: 95.1% [repeated 8x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:11:14] OK: 53 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:11:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:11:15 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.6%, Prefix cache hit rate: 95.1% [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:11:20 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.6%, Prefix cache hit rate: 95.1% [repeated 8x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:11:21] OK: 49 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:11:21] OK: RSS 2.15 GiB | node mem 389.6/858.0 GiB used (45.4%), avail 468.4 GiB +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:11:25 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.7%, Prefix cache hit rate: 95.1% [repeated 8x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:11:29] OK: 61 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:11:29] OK: RSS 2.10 GiB | node mem 394.3/858.0 GiB used (46.0%), avail 463.6 GiB +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:11:30 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.7%, Prefix cache hit rate: 95.1% [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:11:35 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.8%, Prefix cache hit rate: 95.1% [repeated 8x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:11:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:11:38] OK: RSS 1.89 GiB | node mem 384.1/858.0 GiB used (44.8%), avail 473.9 GiB +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:11:40 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.8%, Prefix cache hit rate: 95.1% [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:11:45 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.9%, Prefix cache hit rate: 95.1% [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:11:50 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.9%, Prefix cache hit rate: 95.1% [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:11:55 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 36.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.0%, Prefix cache hit rate: 95.1% [repeated 8x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:11:58] OK: 136 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:11:58] OK: RSS 1.98 GiB | node mem 260.4/858.0 GiB used (30.3%), avail 597.6 GiB +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:12:00 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.0%, Prefix cache hit rate: 95.1% [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:12:05 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.1%, Prefix cache hit rate: 95.1% [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:12:10 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.1%, Prefix cache hit rate: 95.1% [repeated 8x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:12:15 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.2%, Prefix cache hit rate: 95.1% [repeated 7x across cluster] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:12:18 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:12:18 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:12:18 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:12:18 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:12:18 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:12:18 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:12:18 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:12:18 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:12:18 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:12:18 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:12:18 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:12:18 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:12:18 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:12:18 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:12:18 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:12:18 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:12:18 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:12:18 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:12:18 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:12:18 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:12:18 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:12:18 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:12:18 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:12:18 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:12:18 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1496779, ip=10.128.34.182) ERROR 06-14 05:12:18 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1496555, ip=10.128.34.183) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1496555, ip=10.128.34.183) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:12:20 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.2%, Prefix cache hit rate: 95.1% [repeated 7x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:12:25 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.3%, Prefix cache hit rate: 95.1% [repeated 6x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:12:30 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.3%, Prefix cache hit rate: 95.1% [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:12:35 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 36.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.4%, Prefix cache hit rate: 95.1% [repeated 6x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 05:12:36 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 05:12:36 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 05:12:36 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 05:12:36 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 05:12:36 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 05:12:36 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 05:12:36 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 05:12:36 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 05:12:36 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 05:12:36 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 05:12:36 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 05:12:36 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 05:12:36 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 05:12:36 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 05:12:36 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 05:12:36 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 05:12:36 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 05:12:36 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 05:12:36 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 05:12:36 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 05:12:36 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 05:12:36 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 05:12:36 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 05:12:36 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 05:12:36 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507468, ip=10.128.34.178) ERROR 06-14 05:12:36 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:12:40 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.4%, Prefix cache hit rate: 95.1% [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:12:45 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.5%, Prefix cache hit rate: 95.1% [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:12:50 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.5%, Prefix cache hit rate: 95.1% [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:12:55 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 36.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.6%, Prefix cache hit rate: 95.1% [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:13:00 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.6%, Prefix cache hit rate: 95.1% [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:13:05 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.7%, Prefix cache hit rate: 95.1% [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:13:10 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.7%, Prefix cache hit rate: 95.1% [repeated 6x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:13:14] OK: 50 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:13:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:13:15 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.8%, Prefix cache hit rate: 95.1% [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:13:20 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.9%, Prefix cache hit rate: 95.1% [repeated 6x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:13:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:13:21] OK: RSS 2.15 GiB | node mem 390.5/858.0 GiB used (45.5%), avail 467.5 GiB +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:13:25 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.9%, Prefix cache hit rate: 95.1% [repeated 6x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:13:29] OK: 56 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:13:29] OK: RSS 2.10 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:13:30 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.0%, Prefix cache hit rate: 95.1% [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:13:35 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.0%, Prefix cache hit rate: 95.1% [repeated 6x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:13:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:13:38] OK: RSS 1.89 GiB | node mem 384.1/858.0 GiB used (44.8%), avail 473.9 GiB +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:13:40 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.1%, Prefix cache hit rate: 95.1% [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) INFO 06-14 05:13:45 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.1%, Prefix cache hit rate: 95.1% [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:13:47 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:13:47 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:13:47 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:13:47 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:13:47 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:13:47 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:13:47 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:13:47 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:13:47 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:13:47 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:13:47 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:13:47 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:13:47 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:13:47 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:13:47 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:13:47 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:13:47 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:13:47 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:13:47 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:13:47 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:13:47 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:13:47 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:13:47 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:13:47 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:13:47 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507973, ip=10.128.34.179) ERROR 06-14 05:13:47 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) INFO 06-14 05:13:51 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 44.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.6%, Prefix cache hit rate: 94.8% [repeated 6x across cluster] +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) INFO 06-14 05:13:56 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 44.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.6%, Prefix cache hit rate: 94.8% [repeated 5x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:13:58] OK: 132 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:13:58] OK: RSS 1.98 GiB | node mem 260.3/858.0 GiB used (30.3%), avail 597.6 GiB +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) INFO 06-14 05:14:01 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 44.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.7%, Prefix cache hit rate: 94.8% [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) INFO 06-14 05:14:06 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 44.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.8%, Prefix cache hit rate: 94.8% [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=1507595, ip=10.128.34.178) INFO 06-14 05:14:11 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 44.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.8%, Prefix cache hit rate: 94.8% [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) INFO 06-14 05:14:17 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 75.0 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 14.0%, Prefix cache hit rate: 95.2% [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:14:25 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 73.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.8%, Prefix cache hit rate: 96.3% [repeated 5x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:14:30 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 73.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.9%, Prefix cache hit rate: 96.3% [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:14:35 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 75.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.0%, Prefix cache hit rate: 96.3% [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:14:40 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 74.4 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.1%, Prefix cache hit rate: 96.3% [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:14:45 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 73.2 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.2%, Prefix cache hit rate: 96.3% [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:14:50 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 77.3 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.3%, Prefix cache hit rate: 96.3% [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:14:55 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 75.0 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.4%, Prefix cache hit rate: 96.3% [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:15:00 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 72.6 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.5%, Prefix cache hit rate: 96.3% [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:15:05 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 71.3 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.6%, Prefix cache hit rate: 96.3% [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:15:10 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 72.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.7%, Prefix cache hit rate: 96.3% [repeated 4x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:15:14] OK: 50 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:15:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:15:15 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 73.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.9%, Prefix cache hit rate: 96.3% [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:15:20 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 67.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.2%, Prefix cache hit rate: 96.3% [repeated 4x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:15:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:15:21] OK: RSS 2.15 GiB | node mem 390.5/858.0 GiB used (45.5%), avail 467.5 GiB +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:15:25 [loggers.py:259] Engine 000: Avg prompt throughput: 190.6 tokens/s, Avg generation throughput: 62.8 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.6%, Prefix cache hit rate: 96.2% [repeated 4x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:15:29] OK: 55 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:15:29] OK: RSS 2.10 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:15:30 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 65.9 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.7%, Prefix cache hit rate: 96.1% [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:15:35 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 65.3 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.8%, Prefix cache hit rate: 96.1% [repeated 4x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:15:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:15:38] OK: RSS 1.89 GiB | node mem 384.1/858.0 GiB used (44.8%), avail 473.9 GiB +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:15:40 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 64.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.8%, Prefix cache hit rate: 96.1% [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:15:45 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 65.5 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.9%, Prefix cache hit rate: 96.1% [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:15:50 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 65.3 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.0%, Prefix cache hit rate: 96.1% [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:15:55 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 64.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.1%, Prefix cache hit rate: 96.1% [repeated 3x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:15:58] OK: 131 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:15:58] OK: RSS 1.98 GiB | node mem 260.4/858.0 GiB used (30.3%), avail 597.6 GiB +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:16:00 [loggers.py:259] Engine 000: Avg prompt throughput: 322.2 tokens/s, Avg generation throughput: 49.5 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.6%, Prefix cache hit rate: 96.1% [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:16:05 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 64.7 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.7%, Prefix cache hit rate: 96.1% [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:16:10 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 65.3 tokens/s, Running: 2 reqs, Waiting: 0 reqs, GPU KV cache usage: 12.8%, Prefix cache hit rate: 96.1% [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:16:12 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:16:12 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:16:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:16:12 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:16:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:16:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:16:12 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:16:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:16:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:16:12 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:16:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:16:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:16:12 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:16:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:16:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:16:12 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:16:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:16:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:16:12 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:16:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:16:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:16:12 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:16:12 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:16:12 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:16:12 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) ERROR 06-14 05:16:12 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508398, ip=10.128.34.179) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508398, ip=10.128.34.179) +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:16:15 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 47.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.9%, Prefix cache hit rate: 96.1% [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:16:20 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 32.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.0%, Prefix cache hit rate: 96.1% [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:16:23 [serving.py:315] Error in preprocessing prompt inputs +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:16:23 [serving.py:315] Traceback (most recent call last): +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:16:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/chat_completion/serving.py", line 299, in render_chat_request +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:16:23 [serving.py:315] conversation, engine_prompts = await self._preprocess_chat( +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:16:23 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:16:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 1018, in _preprocess_chat +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:16:23 [serving.py:315] (conversation,), (engine_prompt,) = await renderer.render_chat_async( +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:16:23 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:16:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 381, in render_chat_async +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:16:23 [serving.py:315] tok_prompts = await self.tokenize_prompts_async(dict_prompts, tok_params) +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:16:23 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:16:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 278, in tokenize_prompts_async +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:16:23 [serving.py:315] return await asyncio.gather( +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:16:23 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:16:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/protocol.py", line 271, in tokenize_prompt_async +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:16:23 [serving.py:315] return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:16:23 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:16:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 373, in apply_post_tokenization +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:16:23 [serving.py:315] prompt["prompt_token_ids"] = self._validate_tokens( # type: ignore[typeddict-unknown-key] +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:16:23 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:16:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 357, in _validate_tokens +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:16:23 [serving.py:315] tokens = validator(tokenizer, tokens) +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:16:23 [serving.py:315] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:16:23 [serving.py:315] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/renderers/params.py", line 337, in _token_len_check +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:16:23 [serving.py:315] raise VLLMValidationError( +(AsyncVLLMInferenceEngine pid=1495944, ip=10.128.34.183) ERROR 06-14 05:16:23 [serving.py:315] vllm.exceptions.VLLMValidationError: You passed 32769 input tokens and requested 0 output tokens. However, the model's context length is only 32768 tokens, resulting in a maximum input length of 32768 tokens. Please reduce the length of the input prompt. (parameter=input_tokens, value=32769) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new +(RolloutCoordinator pid=1508077, ip=10.128.34.178) LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()'. +(RolloutCoordinator pid=1508077, ip=10.128.34.178) +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:16:25 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 32.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.0%, Prefix cache hit rate: 96.1% [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:16:30 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 32.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.1%, Prefix cache hit rate: 96.1% [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:16:35 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 32.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.1%, Prefix cache hit rate: 96.1% [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:16:40 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 32.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.2%, Prefix cache hit rate: 96.1% [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:16:45 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 32.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.2%, Prefix cache hit rate: 96.1% [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:16:50 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 32.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.3%, Prefix cache hit rate: 96.1% [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:16:55 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 32.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.3%, Prefix cache hit rate: 96.1% [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:17:00 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 32.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.3%, Prefix cache hit rate: 96.1% [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:17:05 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 32.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.4%, Prefix cache hit rate: 96.1% [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:17:10 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 32.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.4%, Prefix cache hit rate: 96.1% [repeated 4x across cluster] +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:17:14] OK: 49 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:17:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:17:15 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 32.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.5%, Prefix cache hit rate: 96.1% [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:17:20 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 32.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.5%, Prefix cache hit rate: 96.1% [repeated 3x across cluster] +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:17:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:17:21] OK: RSS 2.15 GiB | node mem 390.5/858.0 GiB used (45.5%), avail 467.5 GiB +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:17:25 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 32.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.6%, Prefix cache hit rate: 96.1% [repeated 3x across cluster] +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:17:29] OK: 51 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:17:29] OK: RSS 2.10 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:17:30 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 32.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.6%, Prefix cache hit rate: 96.1% [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:17:35 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 32.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.7%, Prefix cache hit rate: 96.1% [repeated 3x across cluster] +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:17:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:17:38] OK: RSS 1.89 GiB | node mem 384.1/858.0 GiB used (44.8%), avail 473.9 GiB +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:17:40 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 32.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.7%, Prefix cache hit rate: 96.1% [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:17:45 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 32.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 4.7%, Prefix cache hit rate: 96.1% [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:17:51 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.5%, Prefix cache hit rate: 96.2% [repeated 4x across cluster] +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:17:56 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 36.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.5%, Prefix cache hit rate: 96.2% [repeated 3x across cluster] +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:17:58] OK: 128 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:17:58] OK: RSS 1.99 GiB | node mem 260.4/858.0 GiB used (30.4%), avail 597.6 GiB +(AsyncVLLMInferenceEngine pid=323258, ip=10.128.56.67) INFO 06-14 05:18:01 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 37.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 3.6%, Prefix cache hit rate: 96.2% [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:18:10 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.0%, Prefix cache hit rate: 96.1% [repeated 3x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:18:15 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.0%, Prefix cache hit rate: 96.1% [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:18:20 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.1%, Prefix cache hit rate: 96.1% [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:18:25 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 33.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.1%, Prefix cache hit rate: 96.1% [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:18:30 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.2%, Prefix cache hit rate: 96.1% [repeated 2x across cluster] +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:18:35 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.2%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:18:40 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.3%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:18:45 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.3%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:18:50 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.4%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:18:55 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.4%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:19:00 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.5%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:19:05 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.5%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:19:10 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.6%, Prefix cache hit rate: 96.1% +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:19:14] OK: 49 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:19:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.0 GiB +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:19:16 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.6%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:19:21 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.7%, Prefix cache hit rate: 96.1% +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:19:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:19:21] OK: RSS 2.15 GiB | node mem 390.5/858.0 GiB used (45.5%), avail 467.4 GiB +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:19:26 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.7%, Prefix cache hit rate: 96.1% +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:19:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:19:29] OK: RSS 2.10 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:19:31 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.8%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:19:36 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.8%, Prefix cache hit rate: 96.1% +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:19:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:19:38] OK: RSS 1.89 GiB | node mem 384.1/858.0 GiB used (44.8%), avail 473.8 GiB +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:19:41 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.8%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:19:46 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.9%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:19:51 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 5.9%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:19:56 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.0%, Prefix cache hit rate: 96.1% +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:19:58] OK: 126 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:19:58] OK: RSS 1.99 GiB | node mem 260.4/858.0 GiB used (30.3%), avail 597.6 GiB +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:20:01 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.0%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:20:06 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.1%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:20:11 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.1%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:20:16 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.2%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:20:21 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.2%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:20:26 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.3%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:20:31 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.3%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:20:36 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.4%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:20:41 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.4%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:20:46 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.5%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:20:51 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.5%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:20:56 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.6%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:21:01 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.6%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:21:06 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.7%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:21:11 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.7%, Prefix cache hit rate: 96.1% +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:21:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:21:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.0 GiB +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:21:16 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.8%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:21:21 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.8%, Prefix cache hit rate: 96.1% +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:21:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:21:21] OK: RSS 2.15 GiB | node mem 390.5/858.0 GiB used (45.5%), avail 467.4 GiB +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:21:26 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.9%, Prefix cache hit rate: 96.1% +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:21:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:21:29] OK: RSS 2.10 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:21:31 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 6.9%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:21:36 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.0%, Prefix cache hit rate: 96.1% +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:21:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:21:38] OK: RSS 1.89 GiB | node mem 384.2/858.0 GiB used (44.8%), avail 473.8 GiB +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:21:41 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.0%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:21:46 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.1%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:21:51 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.1%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:21:56 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.2%, Prefix cache hit rate: 96.1% +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:21:58] OK: 126 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:21:58] OK: RSS 1.99 GiB | node mem 260.4/858.0 GiB used (30.3%), avail 597.6 GiB +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:22:01 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.2%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:22:06 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.3%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:22:11 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.3%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:22:16 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.4%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:22:21 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.4%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:22:26 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.5%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:22:31 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.5%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:22:36 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.6%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:22:41 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 34.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.6%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:22:46 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 36.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.7%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:22:51 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.7%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:22:56 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.4 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.7%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:23:01 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.8%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:23:06 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.9%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:23:11 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.9%, Prefix cache hit rate: 96.1% +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:23:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:23:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.0 GiB +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:23:16 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 7.9%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:23:21 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.0%, Prefix cache hit rate: 96.1% +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:23:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:23:21] OK: RSS 2.15 GiB | node mem 390.6/858.0 GiB used (45.5%), avail 467.4 GiB +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:23:26 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.0%, Prefix cache hit rate: 96.1% +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:23:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:23:29] OK: RSS 2.10 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:23:31 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.1%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:23:36 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.1%, Prefix cache hit rate: 96.1% +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:23:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:23:38] OK: RSS 1.89 GiB | node mem 384.2/858.0 GiB used (44.8%), avail 473.8 GiB +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:23:41 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.2%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:23:46 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.2%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:23:51 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.9 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.3%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:23:56 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.3%, Prefix cache hit rate: 96.1% +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:23:58] OK: 126 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:23:58] OK: RSS 1.99 GiB | node mem 260.4/858.0 GiB used (30.3%), avail 597.6 GiB +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:24:01 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.4%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:24:06 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.4%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:24:11 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 36.0 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.5%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:24:16 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.5%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:24:21 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.3 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.6%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:24:27 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.6%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:24:32 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.8 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.7%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:24:37 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.7 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.7%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:24:42 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.6 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.8%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:24:47 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.8%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:24:52 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 35.2 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.9%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:24:57 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 36.1 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 8.9%, Prefix cache hit rate: 96.1% +(AsyncVLLMInferenceEngine pid=1507842, ip=10.128.34.179) INFO 06-14 05:25:02 [loggers.py:259] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 36.5 tokens/s, Running: 1 reqs, Waiting: 0 reqs, GPU KV cache usage: 9.0%, Prefix cache hit rate: 96.1% +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:25:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:25:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:25:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:25:21] OK: RSS 2.15 GiB | node mem 390.6/858.0 GiB used (45.5%), avail 467.4 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:25:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:25:29] OK: RSS 2.10 GiB | node mem 394.3/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:25:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:25:38] OK: RSS 1.89 GiB | node mem 384.2/858.0 GiB used (44.8%), avail 473.8 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:25:58] OK: 125 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:25:58] OK: RSS 2.00 GiB | node mem 260.4/858.0 GiB used (30.3%), avail 597.6 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:27:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:27:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:27:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:27:21] OK: RSS 2.15 GiB | node mem 390.6/858.0 GiB used (45.5%), avail 467.4 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:27:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:27:29] OK: RSS 2.10 GiB | node mem 394.3/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:27:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:27:38] OK: RSS 1.89 GiB | node mem 384.2/858.0 GiB used (44.8%), avail 473.8 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:27:58] OK: 125 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:27:58] OK: RSS 2.00 GiB | node mem 260.3/858.0 GiB used (30.3%), avail 597.7 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:29:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:29:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:29:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:29:21] OK: RSS 2.15 GiB | node mem 390.6/858.0 GiB used (45.5%), avail 467.4 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:29:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:29:29] OK: RSS 2.10 GiB | node mem 394.3/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:29:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:29:38] OK: RSS 1.89 GiB | node mem 384.2/858.0 GiB used (44.8%), avail 473.8 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:29:58] OK: 125 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:29:58] OK: RSS 2.00 GiB | node mem 260.3/858.0 GiB used (30.3%), avail 597.6 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:31:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:31:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:31:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:31:21] OK: RSS 2.15 GiB | node mem 390.5/858.0 GiB used (45.5%), avail 467.4 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:31:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:31:29] OK: RSS 2.10 GiB | node mem 394.3/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:31:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:31:38] OK: RSS 1.89 GiB | node mem 384.2/858.0 GiB used (44.8%), avail 473.8 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:31:58] OK: 125 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:31:58] OK: RSS 2.00 GiB | node mem 260.3/858.0 GiB used (30.3%), avail 597.6 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:33:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:33:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:33:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:33:21] OK: RSS 2.15 GiB | node mem 390.6/858.0 GiB used (45.5%), avail 467.4 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:33:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:33:29] OK: RSS 2.10 GiB | node mem 394.3/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:33:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:33:38] OK: RSS 1.89 GiB | node mem 384.2/858.0 GiB used (44.8%), avail 473.8 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:33:58] OK: 125 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:33:58] OK: RSS 2.00 GiB | node mem 260.3/858.0 GiB used (30.3%), avail 597.6 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:35:14] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:35:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:35:21] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:35:21] OK: RSS 2.14 GiB | node mem 390.6/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:35:29] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:35:29] OK: RSS 2.07 GiB | node mem 394.3/858.0 GiB used (46.0%), avail 463.7 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:35:38] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:35:38] OK: RSS 1.88 GiB | node mem 384.2/858.0 GiB used (44.8%), avail 473.7 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:35:58] OK: 125 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:35:58] OK: RSS 2.00 GiB | node mem 260.3/858.0 GiB used (30.3%), avail 597.6 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:37:14] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:37:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:37:21] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:37:21] OK: RSS 2.14 GiB | node mem 390.6/858.0 GiB used (45.5%), avail 467.4 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:37:29] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:37:29] OK: RSS 2.07 GiB | node mem 394.3/858.0 GiB used (46.0%), avail 463.7 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:37:38] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:37:38] OK: RSS 1.88 GiB | node mem 384.2/858.0 GiB used (44.8%), avail 473.8 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:37:58] OK: 123 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:37:58] OK: RSS 2.00 GiB | node mem 260.3/858.0 GiB used (30.3%), avail 597.7 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:39:14] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:39:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:39:21] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:39:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:39:29] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:39:29] OK: RSS 2.07 GiB | node mem 394.3/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:39:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:39:38] OK: RSS 1.88 GiB | node mem 384.3/858.0 GiB used (44.8%), avail 473.7 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:39:58] OK: 109 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:39:58] OK: RSS 2.00 GiB | node mem 260.3/858.0 GiB used (30.3%), avail 597.7 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:41:14] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:41:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:41:21] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:41:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:41:29] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:41:29] OK: RSS 2.07 GiB | node mem 394.3/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:41:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:41:38] OK: RSS 1.88 GiB | node mem 384.3/858.0 GiB used (44.8%), avail 473.7 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:41:58] OK: 104 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:41:58] OK: RSS 2.00 GiB | node mem 260.3/858.0 GiB used (30.3%), avail 597.6 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:43:14] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:43:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:43:21] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:43:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:43:29] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:43:29] OK: RSS 2.07 GiB | node mem 394.3/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:43:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:43:38] OK: RSS 1.88 GiB | node mem 384.3/858.0 GiB used (44.8%), avail 473.6 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:43:58] OK: 97 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:43:58] OK: RSS 2.00 GiB | node mem 260.3/858.0 GiB used (30.3%), avail 597.7 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:45:14] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:45:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:45:21] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:45:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:45:29] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:45:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:45:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:45:38] OK: RSS 1.88 GiB | node mem 384.3/858.0 GiB used (44.8%), avail 473.7 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:45:58] OK: 94 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:45:58] OK: RSS 2.00 GiB | node mem 260.3/858.0 GiB used (30.3%), avail 597.7 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:47:14] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:47:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:47:21] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:47:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:47:29] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:47:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:47:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:47:38] OK: RSS 1.88 GiB | node mem 384.3/858.0 GiB used (44.8%), avail 473.6 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:47:58] OK: 93 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:47:58] OK: RSS 2.00 GiB | node mem 260.3/858.0 GiB used (30.3%), avail 597.7 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:49:14] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:49:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:49:21] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:49:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:49:29] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:49:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:49:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:49:38] OK: RSS 1.88 GiB | node mem 384.4/858.0 GiB used (44.8%), avail 473.6 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:49:58] OK: 90 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:49:58] OK: RSS 2.00 GiB | node mem 260.2/858.0 GiB used (30.3%), avail 597.7 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:51:14] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:51:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:51:21] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:51:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:51:29] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:51:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:51:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:51:38] OK: RSS 1.88 GiB | node mem 384.4/858.0 GiB used (44.8%), avail 473.5 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:51:58] OK: 88 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:51:58] OK: RSS 2.00 GiB | node mem 260.2/858.0 GiB used (30.3%), avail 597.8 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:53:14] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:53:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:53:21] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:53:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:53:29] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:53:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:53:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:53:38] OK: RSS 1.88 GiB | node mem 384.4/858.0 GiB used (44.8%), avail 473.5 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:53:58] OK: 86 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:53:58] OK: RSS 2.00 GiB | node mem 260.2/858.0 GiB used (30.3%), avail 597.8 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:55:14] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:55:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:55:21] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:55:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:55:29] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:55:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:55:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:55:38] OK: RSS 1.88 GiB | node mem 384.5/858.0 GiB used (44.8%), avail 473.5 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:55:58] OK: 84 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:55:58] OK: RSS 2.00 GiB | node mem 260.1/858.0 GiB used (30.3%), avail 597.8 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:57:14] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:57:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:57:21] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:57:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:57:29] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:57:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:57:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:57:38] OK: RSS 1.88 GiB | node mem 384.5/858.0 GiB used (44.8%), avail 473.5 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:57:58] OK: 84 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:57:58] OK: RSS 2.00 GiB | node mem 260.2/858.0 GiB used (30.3%), avail 597.8 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:59:14] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [05:59:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:59:21] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [05:59:21] OK: RSS 2.14 GiB | node mem 390.6/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:59:29] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [05:59:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:59:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [05:59:38] OK: RSS 1.88 GiB | node mem 384.5/858.0 GiB used (44.8%), avail 473.5 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:59:58] OK: 82 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [05:59:58] OK: RSS 2.00 GiB | node mem 260.1/858.0 GiB used (30.3%), avail 597.8 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:01:14] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:01:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:01:21] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:01:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:01:29] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:01:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:01:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:01:38] OK: RSS 1.88 GiB | node mem 384.5/858.0 GiB used (44.8%), avail 473.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:01:58] OK: 82 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:01:58] OK: RSS 2.00 GiB | node mem 260.2/858.0 GiB used (30.3%), avail 597.8 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:03:14] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:03:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:03:21] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:03:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:03:29] OK: 48 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:03:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:03:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:03:38] OK: RSS 1.88 GiB | node mem 384.6/858.0 GiB used (44.8%), avail 473.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:03:58] OK: 82 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:03:58] OK: RSS 2.00 GiB | node mem 260.1/858.0 GiB used (30.3%), avail 597.9 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:05:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:05:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:05:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:05:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:05:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:05:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:05:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:05:38] OK: RSS 1.88 GiB | node mem 384.6/858.0 GiB used (44.8%), avail 473.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:05:58] OK: 81 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:05:58] OK: RSS 2.00 GiB | node mem 260.1/858.0 GiB used (30.3%), avail 597.9 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:07:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:07:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:07:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:07:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:07:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:07:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:07:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:07:38] OK: RSS 1.88 GiB | node mem 384.6/858.0 GiB used (44.8%), avail 473.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:07:58] OK: 78 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:07:58] OK: RSS 2.00 GiB | node mem 260.1/858.0 GiB used (30.3%), avail 597.9 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:09:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:09:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:09:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:09:21] OK: RSS 2.14 GiB | node mem 390.6/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:09:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:09:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:09:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:09:38] OK: RSS 1.88 GiB | node mem 384.6/858.0 GiB used (44.8%), avail 473.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:09:58] OK: 68 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:09:58] OK: RSS 2.00 GiB | node mem 260.0/858.0 GiB used (30.3%), avail 598.0 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:11:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:11:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:11:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:11:21] OK: RSS 2.14 GiB | node mem 390.6/858.0 GiB used (45.5%), avail 467.4 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:11:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:11:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:11:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:11:38] OK: RSS 1.88 GiB | node mem 384.6/858.0 GiB used (44.8%), avail 473.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:11:58] OK: 63 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:11:58] OK: RSS 2.00 GiB | node mem 260.0/858.0 GiB used (30.3%), avail 597.9 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:13:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:13:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:13:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:13:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:13:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:13:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:13:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:13:38] OK: RSS 1.88 GiB | node mem 384.6/858.0 GiB used (44.8%), avail 473.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:13:58] OK: 63 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:13:58] OK: RSS 2.00 GiB | node mem 260.0/858.0 GiB used (30.3%), avail 598.0 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:15:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:15:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:15:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:15:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:15:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:15:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:15:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:15:38] OK: RSS 1.88 GiB | node mem 384.6/858.0 GiB used (44.8%), avail 473.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:15:58] OK: 63 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:15:58] OK: RSS 2.00 GiB | node mem 260.0/858.0 GiB used (30.3%), avail 598.0 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:17:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:17:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:17:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:17:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:17:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:17:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:17:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:17:38] OK: RSS 1.88 GiB | node mem 384.6/858.0 GiB used (44.8%), avail 473.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:17:58] OK: 63 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:17:58] OK: RSS 2.00 GiB | node mem 260.0/858.0 GiB used (30.3%), avail 598.0 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:19:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:19:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:19:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:19:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:19:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:19:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:19:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:19:38] OK: RSS 1.88 GiB | node mem 384.6/858.0 GiB used (44.8%), avail 473.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:19:58] OK: 63 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:19:58] OK: RSS 2.00 GiB | node mem 259.9/858.0 GiB used (30.3%), avail 598.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:21:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:21:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:21:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:21:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:21:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:21:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:21:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:21:38] OK: RSS 1.88 GiB | node mem 384.6/858.0 GiB used (44.8%), avail 473.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:21:58] OK: 63 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:21:58] OK: RSS 2.00 GiB | node mem 259.8/858.0 GiB used (30.3%), avail 598.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:23:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:23:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:23:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:23:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:23:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:23:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:23:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:23:38] OK: RSS 1.88 GiB | node mem 384.6/858.0 GiB used (44.8%), avail 473.3 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:23:58] OK: 63 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:23:58] OK: RSS 2.00 GiB | node mem 259.9/858.0 GiB used (30.3%), avail 598.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:25:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:25:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:25:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:25:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:25:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:25:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:25:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:25:38] OK: RSS 1.88 GiB | node mem 384.6/858.0 GiB used (44.8%), avail 473.3 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:25:58] OK: 63 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:25:58] OK: RSS 2.00 GiB | node mem 259.8/858.0 GiB used (30.3%), avail 598.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:27:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:27:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:27:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:27:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:27:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:27:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:27:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:27:38] OK: RSS 1.88 GiB | node mem 384.6/858.0 GiB used (44.8%), avail 473.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:27:58] OK: 63 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:27:58] OK: RSS 2.00 GiB | node mem 259.8/858.0 GiB used (30.3%), avail 598.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:29:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:29:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:29:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:29:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:29:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:29:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:29:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:29:38] OK: RSS 1.88 GiB | node mem 384.6/858.0 GiB used (44.8%), avail 473.3 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:29:58] OK: 63 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:29:58] OK: RSS 2.00 GiB | node mem 259.8/858.0 GiB used (30.3%), avail 598.2 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:31:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:31:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:31:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:31:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:31:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:31:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:31:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:31:38] OK: RSS 1.88 GiB | node mem 384.6/858.0 GiB used (44.8%), avail 473.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:31:58] OK: 63 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:31:58] OK: RSS 2.00 GiB | node mem 259.8/858.0 GiB used (30.3%), avail 598.2 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:33:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:33:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:33:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:33:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:33:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:33:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:33:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:33:38] OK: RSS 1.88 GiB | node mem 384.7/858.0 GiB used (44.8%), avail 473.3 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:33:58] OK: 63 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:33:58] OK: RSS 2.00 GiB | node mem 259.8/858.0 GiB used (30.3%), avail 598.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:35:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:35:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:35:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:35:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:35:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:35:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:35:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:35:38] OK: RSS 1.88 GiB | node mem 384.7/858.0 GiB used (44.8%), avail 473.3 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:35:58] OK: 63 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:35:58] OK: RSS 2.00 GiB | node mem 259.8/858.0 GiB used (30.3%), avail 598.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:37:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:37:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:37:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:37:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:37:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:37:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:37:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:37:38] OK: RSS 1.88 GiB | node mem 384.7/858.0 GiB used (44.8%), avail 473.3 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:37:58] OK: 63 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:37:58] OK: RSS 2.00 GiB | node mem 259.8/858.0 GiB used (30.3%), avail 598.2 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:39:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:39:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:39:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:39:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:39:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:39:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:39:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:39:38] OK: RSS 1.88 GiB | node mem 384.7/858.0 GiB used (44.8%), avail 473.2 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:39:58] OK: RSS 2.00 GiB | node mem 259.8/858.0 GiB used (30.3%), avail 598.2 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:39:58] OK: 63 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:41:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:41:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:41:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:41:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:41:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:41:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:41:38] OK: RSS 1.88 GiB | node mem 384.7/858.0 GiB used (44.8%), avail 473.2 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:41:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:41:58] OK: 63 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:41:58] OK: RSS 2.00 GiB | node mem 259.8/858.0 GiB used (30.3%), avail 598.2 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:43:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:43:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:43:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:43:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:43:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:43:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:43:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:43:38] OK: RSS 1.88 GiB | node mem 384.8/858.0 GiB used (44.8%), avail 473.2 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:43:58] OK: RSS 2.00 GiB | node mem 259.7/858.0 GiB used (30.3%), avail 598.2 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:43:58] OK: 63 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:45:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:45:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:45:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:45:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:45:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:45:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:45:38] OK: RSS 1.88 GiB | node mem 384.8/858.0 GiB used (44.8%), avail 473.2 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:45:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:45:58] OK: 63 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:45:58] OK: RSS 2.00 GiB | node mem 259.7/858.0 GiB used (30.3%), avail 598.3 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:47:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:47:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:47:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:47:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:47:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:47:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:47:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:47:38] OK: RSS 1.88 GiB | node mem 384.8/858.0 GiB used (44.9%), avail 473.2 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:47:58] OK: RSS 2.00 GiB | node mem 259.7/858.0 GiB used (30.3%), avail 598.3 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:47:58] OK: 63 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:49:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179)[0m [fd-monitor] [06:49:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:49:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:49:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:49:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:49:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:49:38] OK: RSS 1.88 GiB | node mem 384.8/858.0 GiB used (44.9%), avail 473.1 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:49:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:49:58] OK: 63 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:49:58] OK: RSS 2.00 GiB | node mem 259.6/858.0 GiB used (30.3%), avail 598.3 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:51:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:51:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:51:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:51:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:51:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:51:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:51:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:51:38] OK: RSS 1.88 GiB | node mem 384.9/858.0 GiB used (44.9%), avail 473.1 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:51:58] OK: RSS 2.00 GiB | node mem 259.6/858.0 GiB used (30.3%), avail 598.3 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:51:58] OK: 63 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:53:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:53:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:53:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:53:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:53:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:53:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:53:38] OK: RSS 1.88 GiB | node mem 384.9/858.0 GiB used (44.9%), avail 473.1 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:53:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:53:58] OK: 63 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:53:58] OK: RSS 2.00 GiB | node mem 259.7/858.0 GiB used (30.3%), avail 598.3 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:55:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:55:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:55:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:55:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:55:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:55:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:55:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:55:38] OK: RSS 1.88 GiB | node mem 385.0/858.0 GiB used (44.9%), avail 473.0 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:55:58] OK: RSS 2.00 GiB | node mem 259.7/858.0 GiB used (30.3%), avail 598.3 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:55:58] OK: 63 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:57:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:57:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:57:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:57:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:57:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:57:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:57:38] OK: RSS 1.88 GiB | node mem 385.0/858.0 GiB used (44.9%), avail 472.9 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:57:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:57:58] OK: 63 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:57:58] OK: RSS 2.00 GiB | node mem 259.6/858.0 GiB used (30.3%), avail 598.3 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:59:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [06:59:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:59:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [06:59:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:59:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [06:59:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:59:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [06:59:38] OK: RSS 1.88 GiB | node mem 385.0/858.0 GiB used (44.9%), avail 472.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:59:58] OK: RSS 2.00 GiB | node mem 259.6/858.0 GiB used (30.3%), avail 598.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [06:59:58] OK: 63 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:01:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:01:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:01:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:01:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:01:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:01:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:01:38] OK: RSS 1.88 GiB | node mem 385.0/858.0 GiB used (44.9%), avail 472.9 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:01:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:01:58] OK: 63 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:01:58] OK: RSS 2.00 GiB | node mem 259.6/858.0 GiB used (30.3%), avail 598.4 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:03:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:03:14] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:03:21] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:03:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:03:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:03:29] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:03:38] OK: 45 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:03:38] OK: RSS 1.88 GiB | node mem 385.0/858.0 GiB used (44.9%), avail 472.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:03:58] OK: RSS 2.00 GiB | node mem 259.5/858.0 GiB used (30.3%), avail 598.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:03:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:05:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:05:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:05:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:05:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:05:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:05:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:05:38] OK: RSS 1.88 GiB | node mem 385.0/858.0 GiB used (44.9%), avail 472.9 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:05:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:05:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:05:58] OK: RSS 2.00 GiB | node mem 259.5/858.0 GiB used (30.3%), avail 598.4 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:07:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:07:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:07:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:07:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:07:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:07:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:07:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:07:38] OK: RSS 1.88 GiB | node mem 385.0/858.0 GiB used (44.9%), avail 472.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:07:58] OK: RSS 2.00 GiB | node mem 259.5/858.0 GiB used (30.2%), avail 598.5 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:07:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:09:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:09:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:09:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:09:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:09:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:09:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:09:38] OK: RSS 1.88 GiB | node mem 385.0/858.0 GiB used (44.9%), avail 472.9 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:09:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:09:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:09:58] OK: RSS 2.00 GiB | node mem 259.5/858.0 GiB used (30.2%), avail 598.5 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:11:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:11:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:11:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:11:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:11:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:11:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:11:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:11:38] OK: RSS 1.88 GiB | node mem 385.0/858.0 GiB used (44.9%), avail 473.0 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:11:58] OK: RSS 2.00 GiB | node mem 259.5/858.0 GiB used (30.2%), avail 598.5 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:11:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:13:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:13:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:13:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:13:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:13:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:13:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:13:38] OK: RSS 1.88 GiB | node mem 385.0/858.0 GiB used (44.9%), avail 473.0 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:13:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:13:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:13:58] OK: RSS 2.00 GiB | node mem 259.5/858.0 GiB used (30.2%), avail 598.5 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:15:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:15:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:15:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:15:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:15:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:15:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:15:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:15:38] OK: RSS 1.88 GiB | node mem 385.0/858.0 GiB used (44.9%), avail 473.0 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:15:58] OK: RSS 2.00 GiB | node mem 259.5/858.0 GiB used (30.2%), avail 598.5 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:15:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:17:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:17:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:17:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:17:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:17:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:17:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:17:38] OK: RSS 1.88 GiB | node mem 385.0/858.0 GiB used (44.9%), avail 473.0 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:17:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:17:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:17:58] OK: RSS 2.00 GiB | node mem 259.4/858.0 GiB used (30.2%), avail 598.5 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:19:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:19:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:19:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:19:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:19:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:19:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:19:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:19:38] OK: RSS 1.88 GiB | node mem 385.0/858.0 GiB used (44.9%), avail 472.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:19:58] OK: RSS 2.00 GiB | node mem 259.4/858.0 GiB used (30.2%), avail 598.5 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:19:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:21:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:21:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:21:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:21:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:21:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:21:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:21:38] OK: RSS 1.88 GiB | node mem 385.1/858.0 GiB used (44.9%), avail 472.9 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:21:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:21:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:21:58] OK: RSS 2.00 GiB | node mem 259.5/858.0 GiB used (30.2%), avail 598.5 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:23:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:23:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:23:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:23:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:23:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:23:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:23:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:23:38] OK: RSS 1.88 GiB | node mem 385.1/858.0 GiB used (44.9%), avail 472.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:23:58] OK: RSS 2.00 GiB | node mem 259.4/858.0 GiB used (30.2%), avail 598.5 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:23:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:25:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:25:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:25:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:25:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:25:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:25:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:25:38] OK: RSS 1.88 GiB | node mem 385.1/858.0 GiB used (44.9%), avail 472.9 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:25:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:25:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:25:58] OK: RSS 2.00 GiB | node mem 259.4/858.0 GiB used (30.2%), avail 598.6 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:27:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:27:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:27:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:27:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:27:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:27:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:27:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:27:38] OK: RSS 1.88 GiB | node mem 385.1/858.0 GiB used (44.9%), avail 472.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:27:58] OK: RSS 2.00 GiB | node mem 259.4/858.0 GiB used (30.2%), avail 598.6 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:27:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:29:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:29:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:29:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:29:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:29:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:29:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:29:38] OK: RSS 1.88 GiB | node mem 385.1/858.0 GiB used (44.9%), avail 472.9 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:29:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:29:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:29:58] OK: RSS 2.00 GiB | node mem 259.4/858.0 GiB used (30.2%), avail 598.6 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:31:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:31:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:31:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:31:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:31:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:31:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:31:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:31:38] OK: RSS 1.88 GiB | node mem 385.1/858.0 GiB used (44.9%), avail 472.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:31:58] OK: RSS 2.00 GiB | node mem 259.4/858.0 GiB used (30.2%), avail 598.6 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:31:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:33:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:33:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:33:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:33:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:33:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:33:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:33:38] OK: RSS 1.88 GiB | node mem 385.1/858.0 GiB used (44.9%), avail 472.9 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:33:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:33:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:33:58] OK: RSS 2.00 GiB | node mem 259.4/858.0 GiB used (30.2%), avail 598.6 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:35:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:35:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:35:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:35:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:35:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:35:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:35:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:35:38] OK: RSS 1.88 GiB | node mem 385.1/858.0 GiB used (44.9%), avail 472.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:35:58] OK: RSS 2.00 GiB | node mem 259.3/858.0 GiB used (30.2%), avail 598.6 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:35:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:37:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:37:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:37:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:37:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:37:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:37:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:37:38] OK: RSS 1.88 GiB | node mem 385.1/858.0 GiB used (44.9%), avail 472.9 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:37:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:37:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:37:58] OK: RSS 2.00 GiB | node mem 259.3/858.0 GiB used (30.2%), avail 598.6 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:39:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:39:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:39:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:39:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:39:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:39:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:39:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:39:38] OK: RSS 1.88 GiB | node mem 385.1/858.0 GiB used (44.9%), avail 472.8 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:39:58] OK: RSS 2.00 GiB | node mem 259.3/858.0 GiB used (30.2%), avail 598.6 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:39:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:41:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:41:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:41:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.3 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:41:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:41:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:41:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:41:38] OK: RSS 1.88 GiB | node mem 385.1/858.0 GiB used (44.9%), avail 472.8 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:41:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:41:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:41:58] OK: RSS 2.00 GiB | node mem 259.3/858.0 GiB used (30.2%), avail 598.7 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:43:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:43:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:43:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:43:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:43:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:43:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:43:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:43:38] OK: RSS 1.88 GiB | node mem 385.1/858.0 GiB used (44.9%), avail 472.8 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:43:58] OK: RSS 2.00 GiB | node mem 259.2/858.0 GiB used (30.2%), avail 598.7 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:43:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:45:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:45:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:45:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:45:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:45:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:45:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:45:38] OK: RSS 1.88 GiB | node mem 385.1/858.0 GiB used (44.9%), avail 472.9 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:45:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:45:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:45:58] OK: RSS 2.00 GiB | node mem 259.2/858.0 GiB used (30.2%), avail 598.7 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:47:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:47:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:47:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:47:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:47:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:47:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:47:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:47:38] OK: RSS 1.88 GiB | node mem 385.1/858.0 GiB used (44.9%), avail 472.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:47:58] OK: RSS 2.00 GiB | node mem 259.2/858.0 GiB used (30.2%), avail 598.8 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:47:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:49:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:49:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:49:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:49:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:49:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:49:29] OK: RSS 2.07 GiB | node mem 394.6/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:49:38] OK: RSS 1.88 GiB | node mem 385.1/858.0 GiB used (44.9%), avail 472.8 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:49:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:49:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:49:58] OK: RSS 2.00 GiB | node mem 259.2/858.0 GiB used (30.2%), avail 598.8 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:51:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:51:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:51:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:51:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:51:29] OK: RSS 2.07 GiB | node mem 394.6/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:51:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:51:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:51:38] OK: RSS 1.88 GiB | node mem 385.2/858.0 GiB used (44.9%), avail 472.8 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:51:58] OK: RSS 2.00 GiB | node mem 259.2/858.0 GiB used (30.2%), avail 598.8 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:51:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:53:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:53:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:53:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:53:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:53:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:53:29] OK: RSS 2.07 GiB | node mem 394.6/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:53:38] OK: RSS 1.88 GiB | node mem 385.2/858.0 GiB used (44.9%), avail 472.8 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:53:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:53:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:53:58] OK: RSS 2.00 GiB | node mem 259.2/858.0 GiB used (30.2%), avail 598.8 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:55:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:55:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:55:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:55:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:55:29] OK: RSS 2.07 GiB | node mem 394.6/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:55:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:55:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:55:38] OK: RSS 1.88 GiB | node mem 385.2/858.0 GiB used (44.9%), avail 472.8 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:55:58] OK: RSS 2.00 GiB | node mem 259.1/858.0 GiB used (30.2%), avail 598.8 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:55:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:57:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:57:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:57:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:57:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:57:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:57:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:57:38] OK: RSS 1.88 GiB | node mem 385.2/858.0 GiB used (44.9%), avail 472.8 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:57:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:57:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:57:58] OK: RSS 2.00 GiB | node mem 259.0/858.0 GiB used (30.2%), avail 598.9 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:59:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [07:59:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:59:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [07:59:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:59:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [07:59:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:59:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [07:59:38] OK: RSS 1.88 GiB | node mem 385.2/858.0 GiB used (44.9%), avail 472.8 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:59:58] OK: RSS 2.00 GiB | node mem 259.0/858.0 GiB used (30.2%), avail 598.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [07:59:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:01:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:01:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:01:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:01:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:01:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:01:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:01:38] OK: RSS 1.88 GiB | node mem 385.2/858.0 GiB used (44.9%), avail 472.7 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:01:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:01:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:01:58] OK: RSS 2.00 GiB | node mem 259.0/858.0 GiB used (30.2%), avail 599.0 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:03:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:03:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:03:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:03:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:03:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:03:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:03:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:03:38] OK: RSS 1.88 GiB | node mem 385.2/858.0 GiB used (44.9%), avail 472.7 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:03:58] OK: RSS 2.00 GiB | node mem 259.0/858.0 GiB used (30.2%), avail 599.0 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:03:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:05:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:05:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:05:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:05:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:05:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:05:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:05:38] OK: RSS 1.88 GiB | node mem 385.2/858.0 GiB used (44.9%), avail 472.7 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:05:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:05:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:05:58] OK: RSS 2.00 GiB | node mem 259.0/858.0 GiB used (30.2%), avail 599.0 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:07:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:07:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:07:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:07:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:07:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:07:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:07:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:07:38] OK: RSS 1.88 GiB | node mem 385.3/858.0 GiB used (44.9%), avail 472.7 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:07:58] OK: RSS 2.00 GiB | node mem 259.0/858.0 GiB used (30.2%), avail 599.0 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:07:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:09:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:09:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:09:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:09:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:09:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:09:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:09:38] OK: RSS 1.88 GiB | node mem 385.3/858.0 GiB used (44.9%), avail 472.7 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:09:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:09:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:09:58] OK: RSS 2.00 GiB | node mem 259.0/858.0 GiB used (30.2%), avail 598.9 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:11:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:11:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:11:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:11:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:11:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:11:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:11:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:11:38] OK: RSS 1.88 GiB | node mem 385.3/858.0 GiB used (44.9%), avail 472.7 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:11:58] OK: RSS 2.00 GiB | node mem 259.0/858.0 GiB used (30.2%), avail 599.0 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:11:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:13:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:13:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:13:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:13:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:13:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:13:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:13:38] OK: RSS 1.88 GiB | node mem 385.3/858.0 GiB used (44.9%), avail 472.7 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:13:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:13:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:13:58] OK: RSS 2.00 GiB | node mem 259.0/858.0 GiB used (30.2%), avail 599.0 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:15:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:15:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:15:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:15:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.6%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:15:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:15:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:15:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:15:38] OK: RSS 1.88 GiB | node mem 385.3/858.0 GiB used (44.9%), avail 472.6 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:15:58] OK: RSS 2.00 GiB | node mem 258.9/858.0 GiB used (30.2%), avail 599.1 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:15:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:17:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:17:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:17:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.6%), avail 467.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:17:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:17:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:17:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:17:38] OK: RSS 1.88 GiB | node mem 385.4/858.0 GiB used (44.9%), avail 472.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:17:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:17:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:17:58] OK: RSS 2.00 GiB | node mem 258.9/858.0 GiB used (30.2%), avail 599.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:19:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.2 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:19:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:19:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:19:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.6%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:19:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:19:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:19:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:19:38] OK: RSS 1.88 GiB | node mem 385.4/858.0 GiB used (44.9%), avail 472.6 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:19:58] OK: RSS 2.00 GiB | node mem 258.9/858.0 GiB used (30.2%), avail 599.1 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:19:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:21:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:21:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:21:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:21:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.6%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:21:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:21:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:21:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:21:38] OK: RSS 1.88 GiB | node mem 385.4/858.0 GiB used (44.9%), avail 472.6 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:21:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:21:58] OK: RSS 2.00 GiB | node mem 258.9/858.0 GiB used (30.2%), avail 599.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:23:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:23:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:23:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:23:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:23:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:23:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:23:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:23:38] OK: RSS 1.88 GiB | node mem 385.4/858.0 GiB used (44.9%), avail 472.6 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:23:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:23:58] OK: RSS 2.00 GiB | node mem 258.8/858.0 GiB used (30.2%), avail 599.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:25:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:25:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:25:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:25:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:25:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:25:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:25:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:25:38] OK: RSS 1.88 GiB | node mem 385.5/858.0 GiB used (44.9%), avail 472.5 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:25:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:25:58] OK: RSS 2.00 GiB | node mem 258.8/858.0 GiB used (30.2%), avail 599.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:27:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:27:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:27:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:27:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.6%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:27:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:27:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:27:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:27:38] OK: RSS 1.88 GiB | node mem 385.5/858.0 GiB used (44.9%), avail 472.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:27:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:27:58] OK: RSS 2.00 GiB | node mem 258.8/858.0 GiB used (30.2%), avail 599.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:29:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:29:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:29:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:29:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.6%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:29:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:29:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:29:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:29:38] OK: RSS 1.88 GiB | node mem 385.5/858.0 GiB used (44.9%), avail 472.5 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:29:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:29:58] OK: RSS 2.00 GiB | node mem 258.8/858.0 GiB used (30.2%), avail 599.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:31:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:31:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:31:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:31:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:31:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:31:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:31:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:31:38] OK: RSS 1.88 GiB | node mem 385.5/858.0 GiB used (44.9%), avail 472.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:31:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:31:58] OK: RSS 2.00 GiB | node mem 258.8/858.0 GiB used (30.2%), avail 599.2 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:33:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:33:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:33:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:33:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:33:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:33:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:33:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:33:38] OK: RSS 1.88 GiB | node mem 385.5/858.0 GiB used (44.9%), avail 472.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:33:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:33:58] OK: RSS 2.00 GiB | node mem 258.8/858.0 GiB used (30.2%), avail 599.2 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:35:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:35:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:35:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:35:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:35:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:35:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:35:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:35:38] OK: RSS 1.88 GiB | node mem 385.5/858.0 GiB used (44.9%), avail 472.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:35:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:35:58] OK: RSS 2.00 GiB | node mem 258.8/858.0 GiB used (30.2%), avail 599.2 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:37:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:37:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:37:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:37:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:37:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:37:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:37:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:37:38] OK: RSS 1.88 GiB | node mem 385.5/858.0 GiB used (44.9%), avail 472.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:37:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:37:58] OK: RSS 2.00 GiB | node mem 258.7/858.0 GiB used (30.2%), avail 599.3 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:39:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:39:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:39:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:39:21] OK: RSS 2.14 GiB | node mem 390.7/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:39:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:39:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:39:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:39:38] OK: RSS 1.88 GiB | node mem 385.5/858.0 GiB used (44.9%), avail 472.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:39:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:39:58] OK: RSS 2.00 GiB | node mem 258.7/858.0 GiB used (30.1%), avail 599.3 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:41:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:41:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:41:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:41:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:41:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:41:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:41:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:41:38] OK: RSS 1.88 GiB | node mem 385.6/858.0 GiB used (44.9%), avail 472.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:41:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:41:58] OK: RSS 2.00 GiB | node mem 258.7/858.0 GiB used (30.2%), avail 599.3 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:43:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:43:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:43:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:43:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:43:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:43:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:43:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:43:38] OK: RSS 1.88 GiB | node mem 385.6/858.0 GiB used (44.9%), avail 472.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:43:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:43:58] OK: RSS 2.00 GiB | node mem 258.7/858.0 GiB used (30.1%), avail 599.3 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:45:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:45:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:45:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:45:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:45:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:45:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:45:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:45:38] OK: RSS 1.88 GiB | node mem 385.5/858.0 GiB used (44.9%), avail 472.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:45:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:45:58] OK: RSS 2.00 GiB | node mem 258.6/858.0 GiB used (30.1%), avail 599.3 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:47:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:47:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:47:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:47:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:47:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:47:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:47:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:47:38] OK: RSS 1.88 GiB | node mem 385.6/858.0 GiB used (44.9%), avail 472.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:47:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:47:58] OK: RSS 2.00 GiB | node mem 258.6/858.0 GiB used (30.1%), avail 599.4 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:49:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:49:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:49:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:49:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:49:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:49:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:49:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:49:38] OK: RSS 1.88 GiB | node mem 385.6/858.0 GiB used (44.9%), avail 472.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:49:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:49:58] OK: RSS 2.00 GiB | node mem 258.6/858.0 GiB used (30.1%), avail 599.4 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:51:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:51:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:51:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:51:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:51:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:51:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:51:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:51:38] OK: RSS 1.88 GiB | node mem 385.6/858.0 GiB used (44.9%), avail 472.4 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:51:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:51:58] OK: RSS 2.00 GiB | node mem 258.6/858.0 GiB used (30.1%), avail 599.4 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:53:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:53:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:53:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:53:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:53:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:53:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:53:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:53:38] OK: RSS 1.88 GiB | node mem 385.7/858.0 GiB used (45.0%), avail 472.3 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:53:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:53:58] OK: RSS 2.00 GiB | node mem 258.6/858.0 GiB used (30.1%), avail 599.3 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:55:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:55:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:55:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:55:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:55:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:55:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:55:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:55:38] OK: RSS 1.88 GiB | node mem 385.6/858.0 GiB used (44.9%), avail 472.3 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:55:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:55:58] OK: RSS 2.00 GiB | node mem 258.5/858.0 GiB used (30.1%), avail 599.4 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:57:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:57:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:57:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:57:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:57:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:57:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:57:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:57:38] OK: RSS 1.88 GiB | node mem 385.7/858.0 GiB used (45.0%), avail 472.3 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:57:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:57:58] OK: RSS 2.00 GiB | node mem 258.5/858.0 GiB used (30.1%), avail 599.5 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:59:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [08:59:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:59:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [08:59:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.6%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:59:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [08:59:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:59:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [08:59:38] OK: RSS 1.88 GiB | node mem 385.7/858.0 GiB used (45.0%), avail 472.3 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:59:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [08:59:58] OK: RSS 2.00 GiB | node mem 258.5/858.0 GiB used (30.1%), avail 599.4 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:01:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:01:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:01:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:01:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.5%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:01:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:01:29] OK: RSS 2.07 GiB | node mem 394.3/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:01:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:01:38] OK: RSS 1.88 GiB | node mem 385.7/858.0 GiB used (45.0%), avail 472.3 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:01:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:01:58] OK: RSS 2.00 GiB | node mem 258.5/858.0 GiB used (30.1%), avail 599.5 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:03:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:03:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:03:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:03:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:03:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:03:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:03:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:03:38] OK: RSS 1.88 GiB | node mem 385.7/858.0 GiB used (45.0%), avail 472.3 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:03:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:03:58] OK: RSS 2.00 GiB | node mem 258.5/858.0 GiB used (30.1%), avail 599.4 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:05:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:05:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:05:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:05:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:05:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:05:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:05:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:05:38] OK: RSS 1.88 GiB | node mem 385.7/858.0 GiB used (45.0%), avail 472.3 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:05:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:05:58] OK: RSS 2.00 GiB | node mem 258.5/858.0 GiB used (30.1%), avail 599.5 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:07:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:07:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:07:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:07:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.6%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:07:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:07:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:07:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:07:38] OK: RSS 1.88 GiB | node mem 385.7/858.0 GiB used (45.0%), avail 472.3 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:07:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:07:58] OK: RSS 2.00 GiB | node mem 258.5/858.0 GiB used (30.1%), avail 599.5 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:09:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:09:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:09:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:09:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.6%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:09:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:09:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:09:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:09:38] OK: RSS 1.88 GiB | node mem 385.7/858.0 GiB used (45.0%), avail 472.3 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:09:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:09:58] OK: RSS 2.00 GiB | node mem 258.5/858.0 GiB used (30.1%), avail 599.5 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:11:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:11:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:11:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:11:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.6%), avail 467.2 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:11:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:11:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:11:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:11:38] OK: RSS 1.88 GiB | node mem 385.7/858.0 GiB used (45.0%), avail 472.2 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:11:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:11:58] OK: RSS 2.00 GiB | node mem 258.5/858.0 GiB used (30.1%), avail 599.5 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:13:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:13:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:13:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:13:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:13:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:13:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:13:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:13:38] OK: RSS 1.88 GiB | node mem 385.8/858.0 GiB used (45.0%), avail 472.2 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:13:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:13:58] OK: RSS 2.00 GiB | node mem 258.4/858.0 GiB used (30.1%), avail 599.5 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:15:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:15:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:15:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:15:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:15:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:15:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:15:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:15:38] OK: RSS 1.88 GiB | node mem 385.8/858.0 GiB used (45.0%), avail 472.2 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:15:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:15:58] OK: RSS 2.00 GiB | node mem 258.4/858.0 GiB used (30.1%), avail 599.6 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:17:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:17:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:17:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:17:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:17:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:17:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:17:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:17:38] OK: RSS 1.88 GiB | node mem 385.8/858.0 GiB used (45.0%), avail 472.2 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:17:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:17:58] OK: RSS 2.00 GiB | node mem 258.4/858.0 GiB used (30.1%), avail 599.5 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:19:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:19:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:19:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:19:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:19:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:19:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:19:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:19:38] OK: RSS 1.88 GiB | node mem 385.8/858.0 GiB used (45.0%), avail 472.1 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:19:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:19:58] OK: RSS 2.00 GiB | node mem 258.4/858.0 GiB used (30.1%), avail 599.5 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:21:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:21:14] OK: RSS 2.03 GiB | node mem 399.8/858.0 GiB used (46.6%), avail 458.2 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:21:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:21:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:21:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:21:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:21:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:21:38] OK: RSS 1.88 GiB | node mem 385.9/858.0 GiB used (45.0%), avail 472.1 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:21:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:21:58] OK: RSS 2.00 GiB | node mem 258.4/858.0 GiB used (30.1%), avail 599.6 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:23:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:23:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:23:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:23:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:23:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:23:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:23:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:23:38] OK: RSS 1.88 GiB | node mem 385.8/858.0 GiB used (45.0%), avail 472.1 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:23:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:23:58] OK: RSS 2.00 GiB | node mem 258.5/858.0 GiB used (30.1%), avail 599.5 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:25:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:25:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:25:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:25:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:25:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:25:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:25:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:25:38] OK: RSS 1.88 GiB | node mem 385.8/858.0 GiB used (45.0%), avail 472.1 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:25:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:25:58] OK: RSS 2.00 GiB | node mem 258.5/858.0 GiB used (30.1%), avail 599.4 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:27:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:27:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:27:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:27:21] OK: RSS 2.14 GiB | node mem 391.0/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:27:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:27:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:27:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:27:38] OK: RSS 1.88 GiB | node mem 385.9/858.0 GiB used (45.0%), avail 472.1 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:27:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:27:58] OK: RSS 2.00 GiB | node mem 258.5/858.0 GiB used (30.1%), avail 599.4 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:29:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:29:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:29:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:29:21] OK: RSS 2.14 GiB | node mem 391.0/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:29:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:29:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:29:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:29:38] OK: RSS 1.88 GiB | node mem 385.9/858.0 GiB used (45.0%), avail 472.1 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:29:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:29:58] OK: RSS 2.00 GiB | node mem 258.5/858.0 GiB used (30.1%), avail 599.5 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:31:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:31:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:31:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:31:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:31:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:31:29] OK: RSS 2.07 GiB | node mem 394.6/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:31:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:31:38] OK: RSS 1.88 GiB | node mem 385.8/858.0 GiB used (45.0%), avail 472.1 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:31:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:31:58] OK: RSS 2.00 GiB | node mem 258.5/858.0 GiB used (30.1%), avail 599.5 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:33:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:33:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:33:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:33:21] OK: RSS 2.14 GiB | node mem 391.0/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:33:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:33:29] OK: RSS 2.07 GiB | node mem 394.6/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:33:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:33:38] OK: RSS 1.88 GiB | node mem 385.8/858.0 GiB used (45.0%), avail 472.1 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:33:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:33:58] OK: RSS 2.00 GiB | node mem 258.4/858.0 GiB used (30.1%), avail 599.5 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:35:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:35:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:35:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:35:21] OK: RSS 2.14 GiB | node mem 391.0/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:35:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:35:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:35:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:35:38] OK: RSS 1.88 GiB | node mem 385.8/858.0 GiB used (45.0%), avail 472.1 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:35:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:35:58] OK: RSS 2.00 GiB | node mem 258.4/858.0 GiB used (30.1%), avail 599.5 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:37:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:37:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:37:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:37:21] OK: RSS 2.14 GiB | node mem 391.0/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:37:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:37:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:37:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:37:38] OK: RSS 1.88 GiB | node mem 385.8/858.0 GiB used (45.0%), avail 472.1 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:37:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:37:58] OK: RSS 2.00 GiB | node mem 258.4/858.0 GiB used (30.1%), avail 599.5 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:39:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:39:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:39:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:39:21] OK: RSS 2.14 GiB | node mem 391.0/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:39:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:39:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:39:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:39:38] OK: RSS 1.88 GiB | node mem 385.8/858.0 GiB used (45.0%), avail 472.1 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:39:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:39:58] OK: RSS 2.00 GiB | node mem 258.4/858.0 GiB used (30.1%), avail 599.5 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:41:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:41:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:41:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:41:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:41:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:41:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:41:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:41:38] OK: RSS 1.88 GiB | node mem 385.8/858.0 GiB used (45.0%), avail 472.1 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:41:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:41:58] OK: RSS 2.00 GiB | node mem 258.4/858.0 GiB used (30.1%), avail 599.6 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:43:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:43:14] OK: RSS 2.03 GiB | node mem 400.1/858.0 GiB used (46.6%), avail 457.9 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:43:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:43:21] OK: RSS 2.14 GiB | node mem 391.0/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:43:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:43:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:43:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:43:38] OK: RSS 1.88 GiB | node mem 385.9/858.0 GiB used (45.0%), avail 472.1 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:43:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:43:58] OK: RSS 2.00 GiB | node mem 258.4/858.0 GiB used (30.1%), avail 599.6 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:45:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:45:14] OK: RSS 2.03 GiB | node mem 400.1/858.0 GiB used (46.6%), avail 457.9 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:45:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:45:21] OK: RSS 2.14 GiB | node mem 391.0/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:45:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:45:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:45:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:45:38] OK: RSS 1.88 GiB | node mem 385.9/858.0 GiB used (45.0%), avail 472.1 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:45:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:45:58] OK: RSS 2.00 GiB | node mem 258.4/858.0 GiB used (30.1%), avail 599.6 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:47:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:47:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 457.9 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:47:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:47:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:47:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:47:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:47:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:47:38] OK: RSS 1.88 GiB | node mem 385.9/858.0 GiB used (45.0%), avail 472.1 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:47:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:47:58] OK: RSS 2.00 GiB | node mem 258.4/858.0 GiB used (30.1%), avail 599.6 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:49:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:49:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 457.9 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:49:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:49:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:49:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:49:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:49:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:49:38] OK: RSS 1.88 GiB | node mem 386.0/858.0 GiB used (45.0%), avail 472.0 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:49:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:49:58] OK: RSS 2.00 GiB | node mem 258.4/858.0 GiB used (30.1%), avail 599.6 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:51:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:51:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 457.9 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:51:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:51:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:51:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:51:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:51:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:51:38] OK: RSS 1.88 GiB | node mem 386.0/858.0 GiB used (45.0%), avail 472.0 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:51:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:51:58] OK: RSS 2.00 GiB | node mem 258.4/858.0 GiB used (30.1%), avail 599.6 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:53:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:53:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 457.9 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:53:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:53:21] OK: RSS 2.14 GiB | node mem 391.0/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:53:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:53:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:53:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:53:38] OK: RSS 1.88 GiB | node mem 386.0/858.0 GiB used (45.0%), avail 472.0 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:53:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:53:58] OK: RSS 2.00 GiB | node mem 258.3/858.0 GiB used (30.1%), avail 599.6 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:55:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:55:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 457.9 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:55:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:55:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:55:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:55:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:55:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:55:38] OK: RSS 1.88 GiB | node mem 386.0/858.0 GiB used (45.0%), avail 472.0 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:55:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:55:58] OK: RSS 2.00 GiB | node mem 258.3/858.0 GiB used (30.1%), avail 599.6 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:57:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:57:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:57:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:57:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:57:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:57:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:57:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:57:38] OK: RSS 1.88 GiB | node mem 386.0/858.0 GiB used (45.0%), avail 472.0 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:57:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:57:58] OK: RSS 2.00 GiB | node mem 258.3/858.0 GiB used (30.1%), avail 599.7 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:59:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [09:59:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:59:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [09:59:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:59:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [09:59:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:59:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [09:59:38] OK: RSS 1.88 GiB | node mem 386.0/858.0 GiB used (45.0%), avail 472.0 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:59:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [09:59:58] OK: RSS 2.00 GiB | node mem 258.2/858.0 GiB used (30.1%), avail 599.7 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:01:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:01:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:01:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:01:21] OK: RSS 2.14 GiB | node mem 391.0/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:01:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:01:29] OK: RSS 2.07 GiB | node mem 394.6/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:01:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:01:38] OK: RSS 1.88 GiB | node mem 386.0/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:01:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:01:58] OK: RSS 2.00 GiB | node mem 258.3/858.0 GiB used (30.1%), avail 599.7 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:03:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:03:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:03:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:03:21] OK: RSS 2.14 GiB | node mem 391.0/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:03:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:03:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:03:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:03:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:03:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:03:58] OK: RSS 2.00 GiB | node mem 258.3/858.0 GiB used (30.1%), avail 599.7 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:05:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:05:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:05:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:05:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:05:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:05:30] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:05:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:05:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:05:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:05:58] OK: RSS 2.00 GiB | node mem 258.2/858.0 GiB used (30.1%), avail 599.7 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:07:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:07:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:07:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:07:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:07:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:07:30] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:07:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:07:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:07:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:07:58] OK: RSS 2.00 GiB | node mem 258.1/858.0 GiB used (30.1%), avail 599.8 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:09:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:09:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:09:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:09:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:09:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:09:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:09:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:09:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:09:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:09:58] OK: RSS 2.00 GiB | node mem 258.1/858.0 GiB used (30.1%), avail 599.8 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:11:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:11:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:11:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:11:21] OK: RSS 2.14 GiB | node mem 391.0/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:11:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:11:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:11:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:11:38] OK: RSS 1.88 GiB | node mem 386.0/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:11:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:11:58] OK: RSS 2.00 GiB | node mem 258.1/858.0 GiB used (30.1%), avail 599.9 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:13:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:13:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:13:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:13:21] OK: RSS 2.14 GiB | node mem 391.0/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:13:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:13:30] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:13:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:13:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:13:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:13:58] OK: RSS 2.00 GiB | node mem 258.1/858.0 GiB used (30.1%), avail 599.9 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:15:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:15:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:15:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:15:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:15:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:15:30] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:15:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:15:38] OK: RSS 1.88 GiB | node mem 386.0/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:15:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:15:58] OK: RSS 2.00 GiB | node mem 258.1/858.0 GiB used (30.1%), avail 599.9 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:17:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:17:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:17:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:17:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:17:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:17:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:17:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:17:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:17:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:17:58] OK: RSS 1.99 GiB | node mem 258.0/858.0 GiB used (30.1%), avail 599.9 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:19:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:19:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:19:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:19:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:19:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:19:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:19:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:19:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:19:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:19:58] OK: RSS 1.99 GiB | node mem 258.1/858.0 GiB used (30.1%), avail 599.9 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:21:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:21:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:21:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:21:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:21:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:21:30] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:21:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:21:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:21:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:21:58] OK: RSS 1.99 GiB | node mem 258.1/858.0 GiB used (30.1%), avail 599.9 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:23:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:23:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:23:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:23:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:23:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:23:30] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:23:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:23:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:23:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:23:58] OK: RSS 1.99 GiB | node mem 258.1/858.0 GiB used (30.1%), avail 599.9 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:25:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:25:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:25:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:25:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:25:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:25:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:25:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:25:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.8 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:25:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:25:58] OK: RSS 1.99 GiB | node mem 258.0/858.0 GiB used (30.1%), avail 599.9 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:27:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:27:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:27:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:27:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:27:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:27:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:27:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:27:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.8 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:27:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:27:58] OK: RSS 1.99 GiB | node mem 258.0/858.0 GiB used (30.1%), avail 599.9 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:29:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:29:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:29:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:29:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:29:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:29:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.4 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:29:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:29:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.8 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:29:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:29:58] OK: RSS 1.99 GiB | node mem 258.0/858.0 GiB used (30.1%), avail 599.9 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:31:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:31:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:31:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:31:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:31:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:31:30] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:31:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:31:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.8 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:31:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:31:58] OK: RSS 1.99 GiB | node mem 258.0/858.0 GiB used (30.1%), avail 600.0 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:33:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:33:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:33:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:33:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:33:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:33:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:33:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:33:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:33:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:33:58] OK: RSS 1.99 GiB | node mem 258.0/858.0 GiB used (30.1%), avail 600.0 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:35:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:35:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:35:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:35:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:35:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:35:29] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:35:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:35:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:35:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:35:58] OK: RSS 1.99 GiB | node mem 258.0/858.0 GiB used (30.1%), avail 600.0 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:37:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:37:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:37:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:37:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:37:29] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:37:29] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:37:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:37:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:37:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:37:58] OK: RSS 1.99 GiB | node mem 257.9/858.0 GiB used (30.1%), avail 600.0 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:39:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:39:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:39:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:39:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:39:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:39:30] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:39:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:39:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.8 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:39:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:39:58] OK: RSS 1.99 GiB | node mem 257.9/858.0 GiB used (30.1%), avail 600.0 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:41:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:41:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:41:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:41:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:41:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:41:30] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:41:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:41:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:41:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:41:58] OK: RSS 1.99 GiB | node mem 257.9/858.0 GiB used (30.1%), avail 600.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:43:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:43:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:43:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:43:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:43:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:43:30] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:43:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:43:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:43:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:43:58] OK: RSS 1.99 GiB | node mem 257.8/858.0 GiB used (30.1%), avail 600.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:45:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:45:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:45:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:45:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:45:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:45:30] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:45:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:45:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:45:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:45:58] OK: RSS 1.99 GiB | node mem 257.8/858.0 GiB used (30.0%), avail 600.2 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:47:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:47:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:47:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:47:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:47:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:47:30] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:47:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:47:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:47:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:47:58] OK: RSS 1.99 GiB | node mem 257.8/858.0 GiB used (30.0%), avail 600.2 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:49:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:49:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:49:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:49:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:49:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:49:30] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:49:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:49:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:49:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:49:58] OK: RSS 1.99 GiB | node mem 257.8/858.0 GiB used (30.1%), avail 600.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:51:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:51:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:51:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:51:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:51:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:51:30] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:51:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:51:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:51:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:51:58] OK: RSS 1.99 GiB | node mem 257.8/858.0 GiB used (30.0%), avail 600.1 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:53:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:53:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:53:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:53:21] OK: RSS 2.14 GiB | node mem 390.8/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:53:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:53:30] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:53:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:53:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:53:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:53:58] OK: RSS 1.99 GiB | node mem 257.8/858.0 GiB used (30.0%), avail 600.2 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:55:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:55:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:55:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:55:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:55:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:55:30] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:55:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:55:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:55:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:55:58] OK: RSS 1.99 GiB | node mem 257.8/858.0 GiB used (30.0%), avail 600.2 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:57:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:57:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:57:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:57:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:57:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:57:30] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.6 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:57:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:57:38] OK: RSS 1.88 GiB | node mem 386.0/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:57:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:57:58] OK: RSS 1.99 GiB | node mem 257.8/858.0 GiB used (30.0%), avail 600.2 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:59:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [10:59:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:59:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [10:59:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:59:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [10:59:30] OK: RSS 2.07 GiB | node mem 394.4/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:59:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [10:59:38] OK: RSS 1.88 GiB | node mem 386.0/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:59:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [10:59:58] OK: RSS 1.99 GiB | node mem 257.7/858.0 GiB used (30.0%), avail 600.2 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [11:01:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [11:01:14] OK: RSS 2.03 GiB | node mem 400.0/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [11:01:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [11:01:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [11:01:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [11:01:30] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [11:01:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [11:01:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [11:01:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [11:01:58] OK: RSS 1.99 GiB | node mem 257.7/858.0 GiB used (30.0%), avail 600.2 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [11:03:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [11:03:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [11:03:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [11:03:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [11:03:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [11:03:30] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [11:03:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [11:03:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [11:03:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [11:03:58] OK: RSS 1.99 GiB | node mem 257.7/858.0 GiB used (30.0%), avail 600.3 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [11:05:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [11:05:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [11:05:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [11:05:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [11:05:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [11:05:30] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [11:05:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [11:05:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [11:05:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [11:05:58] OK: RSS 1.99 GiB | node mem 257.7/858.0 GiB used (30.0%), avail 600.3 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [11:07:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [11:07:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [11:07:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [11:07:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [11:07:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [11:07:30] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [11:07:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [11:07:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.8 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [11:07:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [11:07:58] OK: RSS 1.99 GiB | node mem 257.7/858.0 GiB used (30.0%), avail 600.3 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [11:09:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [11:09:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.0 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [11:09:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [11:09:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [11:09:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [11:09:30] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [11:09:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [11:09:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.9 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [11:09:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [11:09:58] OK: RSS 1.99 GiB | node mem 257.7/858.0 GiB used (30.0%), avail 600.3 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [11:11:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [11:11:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [11:11:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [11:11:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [11:11:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [11:11:30] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [11:11:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [11:11:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.8 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [11:11:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [11:11:58] OK: RSS 1.99 GiB | node mem 257.6/858.0 GiB used (30.0%), avail 600.3 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [11:13:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [11:13:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [11:13:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [11:13:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [11:13:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [11:13:30] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [11:13:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [11:13:38] OK: RSS 1.88 GiB | node mem 386.2/858.0 GiB used (45.0%), avail 471.8 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [11:13:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [11:13:58] OK: RSS 1.99 GiB | node mem 257.6/858.0 GiB used (30.0%), avail 600.3 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [11:15:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [11:15:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [11:15:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [11:15:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.1 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [11:15:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [11:15:30] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [11:15:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [11:15:38] OK: RSS 1.88 GiB | node mem 386.1/858.0 GiB used (45.0%), avail 471.8 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [11:15:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [11:15:58] OK: RSS 1.99 GiB | node mem 257.6/858.0 GiB used (30.0%), avail 600.3 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [11:17:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [11:17:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [11:17:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [11:17:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [11:17:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [11:17:30] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [11:17:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [11:17:38] OK: RSS 1.88 GiB | node mem 386.2/858.0 GiB used (45.0%), avail 471.8 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [11:17:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [11:17:58] OK: RSS 1.99 GiB | node mem 257.6/858.0 GiB used (30.0%), avail 600.3 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [11:19:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [11:19:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [11:19:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [11:19:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [11:19:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [11:19:30] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [11:19:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [11:19:38] OK: RSS 1.88 GiB | node mem 386.2/858.0 GiB used (45.0%), avail 471.8 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [11:19:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [11:19:58] OK: RSS 1.99 GiB | node mem 257.6/858.0 GiB used (30.0%), avail 600.3 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [11:21:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [11:21:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [11:21:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [11:21:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [11:21:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [11:21:30] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [11:21:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [11:21:38] OK: RSS 1.88 GiB | node mem 386.2/858.0 GiB used (45.0%), avail 471.8 GiB +(skyrl_entrypoint pid=1712105) [fd-monitor] [11:21:58] OK: 64 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(skyrl_entrypoint pid=1712105) [fd-monitor] [11:21:58] OK: RSS 1.99 GiB | node mem 257.6/858.0 GiB used (30.0%), avail 600.4 GiB +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [11:23:14] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508398, ip=10.128.34.179) [fd-monitor] [11:23:14] OK: RSS 2.03 GiB | node mem 399.9/858.0 GiB used (46.6%), avail 458.1 GiB +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [11:23:21] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1496555, ip=10.128.34.183) [fd-monitor] [11:23:21] OK: RSS 2.14 GiB | node mem 390.9/858.0 GiB used (45.6%), avail 467.0 GiB +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [11:23:30] OK: 47 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=1508077, ip=10.128.34.178) [fd-monitor] [11:23:30] OK: RSS 2.07 GiB | node mem 394.5/858.0 GiB used (46.0%), avail 463.5 GiB +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [11:23:38] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) +(RolloutCoordinator pid=3946333, ip=10.128.56.73) [fd-monitor] [11:23:38] OK: RSS 1.88 GiB | node mem 386.3/858.0 GiB used (45.0%), avail 471.7 GiB +Error executing job with overrides: ['+terminal_bench_config=terminal_bench', 'trainer.strategy=fsdp2', 'trainer.algorithm.advantage_estimator=rloo_n', 'trainer.algorithm.use_kl_loss=false', 'trainer.algorithm.kl_loss_coef=0.0', 'trainer.algorithm.eps_clip_low=0.2', 'trainer.algorithm.eps_clip_high=0.2', 'trainer.algorithm.loss_reduction=seq_mean_token_sum_norm_global', 'trainer.algorithm.use_tis=true', 'trainer.algorithm.tis_imp_ratio_cap=2.0', 'trainer.epochs=2', 'trainer.max_steps=80', 'trainer.update_epochs_per_batch=1', 'trainer.train_batch_size=64', 'trainer.policy_mini_batch_size=64', 'trainer.eval_batch_size=64', 'trainer.micro_forward_batch_size_per_gpu=4', 'trainer.micro_train_batch_size_per_gpu=1', 'trainer.max_prompt_length=999999', 'trainer.eval_interval=999999', 'trainer.eval_before_train=false', 'trainer.ckpt_interval=2', 'trainer.resume_mode=latest', 'trainer.hf_save_interval=5', '++trainer.hf_hub_repo_id=laion/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san', '++trainer.hf_hub_private=false', '++trainer.hf_hub_revision=main', '++trainer.enable_db_registration=false', 'trainer.project_name=OpenThoughts-Agent', 'trainer.log_level=INFO', 'trainer.tracker_commit_each_step=true', 'trainer.logger=console', 'trainer.run_name=rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san', 'trainer.ckpt_path=/e/data1/datasets/playground/ot-baf/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/checkpoints', 'trainer.export_path=/e/data1/datasets/playground/ot-baf/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/exports', 'trainer.policy.optimizer_config.lr=8e-6', 'trainer.policy.optimizer_config.weight_decay=0.0', 'trainer.policy.optimizer_config.adam_betas=[0.9,0.999]', 'trainer.policy.optimizer_config.max_grad_norm=0.9', 'trainer.policy.fsdp_config.cpu_offload=false', 'trainer.policy.fsdp_config.reshard_after_forward=true', 'trainer.policy.fsdp_config.fsdp_size=4', 'trainer.policy.model.path=/e/data1/datasets/playground/ot-baf/hf_hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', 'trainer.ref.fsdp_config.cpu_offload=false', 'trainer.ref.fsdp_config.reshard_after_forward=true', 'trainer.ref.fsdp_config.fsdp_size=4', 'trainer.placement.colocate_all=false', 'trainer.placement.policy_num_nodes=2', 'trainer.placement.ref_num_nodes=2', 'trainer.placement.policy_num_gpus_per_node=4', 'trainer.placement.ref_num_gpus_per_node=4', 'trainer.fully_async.max_staleness_steps=16', 'trainer.fully_async.num_parallel_generation_workers=338', 'generator.backend=vllm', 'generator.timeout_multiplier=1.0', 'generator.model_dtype=bfloat16', 'generator.inference_engine_tensor_parallel_size=1', 'generator.num_inference_engines=48', 'generator.n_samples_per_prompt=8', 'generator.eval_n_samples_per_prompt=8', 'generator.gpu_memory_utilization=0.75', 'generator.max_num_seqs=24', 'generator.max_num_batched_tokens=65536', 'generator.enable_prefix_caching=true', 'generator.enable_chunked_prefill=true', 'generator.run_engines_locally=true', 'generator.weight_sync_backend=nccl', 'generator.async_engine=true', 'generator.batched=false', 'generator.enable_http_endpoint=true', 'generator.enable_ray_prometheus_stats=false', 'generator.vllm_stats_interval=1', 'generator.append_eos_token_after_stop_str_in_multi_turn=true', 'generator.max_turns=999999', 'generator.sampling_params.max_generate_length=4096', 'generator.sampling_params.temperature=1.0', 'generator.sampling_params.top_p=1.0', 'generator.sampling_params.top_k=-1', '++generator.engine_init_kwargs.max_model_len=32768', '++generator.engine_init_kwargs.custom_chat_template_chat_completion_path=chat_templates/qwen3_thinking_acc.jinja2', '++generator.engine_init_kwargs.served_model_name=0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', 'data.train_data=["/e/scratch/jureap59/feuer1/tasks/exp_rpt_pymethods2test-large"]', 'data.val_data=[]', '+terminal_bench_config.trials_dir=/e/data1/datasets/playground/ot-baf/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/trace_jobs', '+terminal_bench_config.harbor.name=terminus-2', '+terminal_bench_config.harbor.max_episodes=999999', '+terminal_bench_config.harbor.enable_summarize=false', '+terminal_bench_config.harbor.store_all_messages=true', '+terminal_bench_config.harbor.trajectory_config.raw_content=true', '+terminal_bench_config.harbor.enable_episode_logging=false', '+terminal_bench_config.harbor.record_terminal_session=false', '+terminal_bench_config.harbor.enable_pane_logging=false', '+terminal_bench_config.harbor.strict_json_parser=true', '+terminal_bench_config.harbor.interleaved_thinking=true', '+terminal_bench_config.harbor.extra_body.chat_template_kwargs.enable_thinking=true', '+terminal_bench_config.harbor.override_timeout_sec=900', '+terminal_bench_config.harbor.override_cpus=1', '+terminal_bench_config.harbor.override_memory_mb=2048', '+terminal_bench_config.harbor.override_storage_mb=2048', '+terminal_bench_config.harbor.auto_snapshot=true', '+terminal_bench_config.harbor.verifier_override_timeout_sec=120', '+terminal_bench_config.harbor.max_retries=3', '+terminal_bench_config.harbor.min_wait_sec=60.0', '+terminal_bench_config.harbor.max_wait_sec=600.0', '+terminal_bench_config.harbor.wait_multiplier=2.0', '+terminal_bench_config.harbor.exclude_exceptions=["VerifierTimeoutError","VerifierRuntimeError","RewardFileNotFoundError","RewardFileEmptyError","VerifierOutputParseError"]', '+terminal_bench_config.harbor.n_concurrent_trials=675', '+terminal_bench_config.harbor.log_level=INFO', '+terminal_bench_config.harbor.enable_reward_shaping=true', '+terminal_bench_config.harbor.reward_shaper=composite_loop', '+terminal_bench_config.harbor.loop_outcome_shaper=original', '+terminal_bench_config.harbor.loop_shaping.outcome_weight=1.0', '+terminal_bench_config.harbor.loop_shaping.total_shaping_cap=0.3', '+terminal_bench_config.harbor.loop_shaping.terminate.enabled=true', '+terminal_bench_config.harbor.loop_shaping.terminate.green_bonus=0.3', '+terminal_bench_config.harbor.loop_shaping.terminate.red_penalty=0.3', '+terminal_bench_config.harbor.loop_shaping.terminate.noterm_penalty=0.2', '+terminal_bench_config.harbor.loop_shaping.antithrash.enabled=true', '+terminal_bench_config.harbor.loop_shaping.antithrash.per_repeat_penalty=0.02', '+terminal_bench_config.harbor.loop_shaping.antithrash.cap=0.1', '+terminal_bench_config.harbor.collect_rollout_details=true', '+terminal_bench_config.harbor.enable_error_classification=true', '+terminal_bench_config.harbor.mask_exceptions=["DaytonaError","EnvironmentStartTimeoutError","NetworkError","ConnectionError","RewardFileNotFoundError","RewardFileEmptyError","AgentEnvironmentTimeoutError","ContextLengthExceededError"]', '+terminal_bench_config.harbor.default_error_treatment=zero', '+terminal_bench_config.harbor.passthrough_exceptions=["AgentTimeoutError"]', '+terminal_bench_config.harbor.zero_exceptions=[]', '+terminal_bench_config.model_info.max_input_tokens=32000', '+terminal_bench_config.model_info.max_output_tokens=4096', '+terminal_bench_config.archiving.enabled=false', '+terminal_bench_config.trace_upload.enabled=true', '+terminal_bench_config.trace_upload.repo_org=DCAgent', '+terminal_bench_config.trace_upload.episodes=last', '+terminal_bench_config.trace_upload.dataset_type=SFT', '+terminal_bench_config.trace_upload.cleanup=true'] +Traceback (most recent call last): + File "", line 198, in _run_module_as_main + File "", line 88, in _run_code + File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/examples/terminal_bench/entrypoints/main_tbench.py", line 142, in + main() + File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/hydra/main.py", line 94, in decorated_main + _run_hydra( + File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/hydra/_internal/utils.py", line 394, in _run_hydra + _run_app( + File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/hydra/_internal/utils.py", line 457, in _run_app + run_and_report( + File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/hydra/_internal/utils.py", line 223, in run_and_report + raise ex + File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/hydra/_internal/utils.py", line 220, in run_and_report + return func() + ^^^^^^ + File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/hydra/_internal/utils.py", line 458, in + lambda: hydra.run( + ^^^^^^^^^^ + File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/hydra/_internal/hydra.py", line 132, in run + _ = ret.return_value + ^^^^^^^^^^^^^^^^ + File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/hydra/core/utils.py", line 260, in return_value + raise self._return_value + File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/hydra/core/utils.py", line 186, in run_job + ret.return_value = task_function(task_cfg) + ^^^^^^^^^^^^^^^^^^^^^^^ + File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/examples/terminal_bench/entrypoints/main_tbench.py", line 132, in main + ray.get(skyrl_entrypoint.remote(cfg)) + File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/ray/_private/auto_init_hook.py", line 22, in auto_init_wrapper + return fn(*args, **kwargs) + ^^^^^^^^^^^^^^^^^^^ + File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/ray/_private/client_mode_hook.py", line 104, in wrapper + return func(*args, **kwargs) + ^^^^^^^^^^^^^^^^^^^^^ + File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/ray/_private/worker.py", line 2967, in get + values, debugger_breakpoint = worker.get_objects( + ^^^^^^^^^^^^^^^^^^^ + File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/ray/_private/worker.py", line 1017, in get_objects + raise value +ray.exceptions.NodeDiedError: Task failed because the node it was running on is dead or unavailable. Node IP: 10.128.34.177, node ID: 53bb45a0396f584a1d90d4f7b15281adc33510f232c8d3753c55797f. This can happen if the node was preempted, had a hardware failure, or its raylet crashed unexpectedly. To see node death information, use `ray list nodes --filter node_id=53bb45a0396f584a1d90d4f7b15281adc33510f232c8d3753c55797f`, check the Ray dashboard cluster page, search the node ID in the GCS logs, or use `ray logs raylet.out -ip 10.128.34.177`. +Stopping Ray cluster... + Collecting Ray logs from worker jpbo-055-18... +Ray cluster stopped +[RLJobRunner] Crash detected (exit!=0) — preserving Ray logs to /e/data1/datasets/playground/ot-baf/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/ray_logs BEFORE trace upload (so a wall-clock kill can't lose crash evidence)... + WARNING: Failed to collect logs from jpbo-055-18 + Collecting Ray logs from worker jpbo-055-19... + WARNING: Failed to collect logs from jpbo-055-19 + Collecting Ray logs from worker jpbo-055-21... + WARNING: Failed to collect logs from jpbo-055-21 + Collecting Ray logs from worker jpbo-055-22... + Collecting Ray logs from worker jpbo-055-18... + WARNING: Failed to collect logs from jpbo-055-18 + Collecting Ray logs from worker jpbo-055-19... + WARNING: Failed to collect logs from jpbo-055-22 + Collecting Ray logs from worker jpbo-055-23... + WARNING: Failed to collect logs from jpbo-055-19 + Collecting Ray logs from worker jpbo-055-21... + WARNING: Failed to collect logs from jpbo-055-21 + Collecting Ray logs from worker jpbo-055-22... + WARNING: Failed to collect logs from jpbo-055-22 + Collecting Ray logs from worker jpbo-055-23... + WARNING: Failed to collect logs from jpbo-055-23 + Collecting Ray logs from worker jpbo-055-25... + WARNING: Failed to collect logs from jpbo-055-23 + Collecting Ray logs from worker jpbo-055-25... + WARNING: Failed to collect logs from jpbo-055-25 + WARNING: Failed to collect logs from jpbo-055-25 + Collecting Ray logs from worker jpbo-102-17... + Collecting Ray logs from worker jpbo-102-17... + WARNING: Failed to collect logs from jpbo-102-17 + WARNING: Failed to collect logs from jpbo-102-17 + Collecting Ray logs from worker jpbo-102-18... + Collecting Ray logs from worker jpbo-102-18... + WARNING: Failed to collect logs from jpbo-102-18 + Collecting Ray logs from worker jpbo-102-19... + WARNING: Failed to collect logs from jpbo-102-18 + Collecting Ray logs from worker jpbo-102-19... + WARNING: Failed to collect logs from jpbo-102-19 + WARNING: Failed to collect logs from jpbo-102-19 + Collecting Ray logs from worker jpbo-102-20... + Collecting Ray logs from worker jpbo-102-20... + WARNING: Failed to collect logs from jpbo-102-20 + Collecting Ray logs from worker jpbo-102-25... + WARNING: Failed to collect logs from jpbo-102-20 + Collecting Ray logs from worker jpbo-102-25... + WARNING: Failed to collect logs from jpbo-102-25 + WARNING: Failed to collect logs from jpbo-102-25 + Collecting Ray logs from worker jpbo-102-28... + Collecting Ray logs from worker jpbo-102-28... + WARNING: Failed to collect logs from jpbo-102-28 + WARNING: Failed to collect logs from jpbo-102-28 + Collecting Ray logs from worker jpbo-102-30... + Collecting Ray logs from worker jpbo-102-30... + WARNING: Failed to collect logs from jpbo-102-30 + WARNING: Failed to collect logs from jpbo-102-30 +Ray log preservation complete +[RLJobRunner] Crash-time Ray log preservation complete. +[RLJobRunner] Launching trace upload (training exit code: 1): + repo_id: DCAgent/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san + job_dir: /e/data1/datasets/playground/ot-baf/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san + episodes: last + log: /e/data1/datasets/playground/ot-baf/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san/logs/rl__56GPU_seqnorm_tis_untrunc_symclip_loopshape__exp_rpt_pymethods2test-large__GLM-4_7-swesmith-san_trace_upload.log +[RLJobRunner] Waiting for trace upload to complete...