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+1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0b498be21feb1ce85d1db705d6be532963fad24b54a37c4f318259e6b0539b9f +size 11674552 diff --git a/playground/code/active_proaction_backup/new_eval_dataset/embed_new_tier_evalset_210_112_0306_03_output_feat_add_interest.csv b/playground/code/active_proaction_backup/new_eval_dataset/embed_new_tier_evalset_210_112_0306_03_output_feat_add_interest.csv new file mode 100644 index 0000000000000000000000000000000000000000..5e8f98ace6d856a1abdacf722a9475a7773f103f --- /dev/null +++ b/playground/code/active_proaction_backup/new_eval_dataset/embed_new_tier_evalset_210_112_0306_03_output_feat_add_interest.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f573ae63d8e741f232290a7e4183e8dbc2961f5e80a242480d0f9c737b2229f1 +size 112845449 diff --git a/playground/code/active_proaction_backup/new_eval_dataset/new_policy_7w_valid_add_attr.csv b/playground/code/active_proaction_backup/new_eval_dataset/new_policy_7w_valid_add_attr.csv new file mode 100644 index 0000000000000000000000000000000000000000..fbef6e19ba1f80af98ec1e81210eb8b6abeeb74b --- /dev/null +++ b/playground/code/active_proaction_backup/new_eval_dataset/new_policy_7w_valid_add_attr.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:61a54324140999b715872bb7c9742c6cb882b7f56b07d9eecf59982000a18f6a +size 123397969 diff --git a/playground/code/active_proaction_backup/new_eval_dataset/new_tier_evalset_210_112_0306_03.csv b/playground/code/active_proaction_backup/new_eval_dataset/new_tier_evalset_210_112_0306_03.csv new file mode 100644 index 0000000000000000000000000000000000000000..f1d4c338d10d68799431764aff71df4a1745584c --- /dev/null +++ b/playground/code/active_proaction_backup/new_eval_dataset/new_tier_evalset_210_112_0306_03.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3fd6eabac009e85f7bd7d244c25224b82e1f8d1e1d366aa2a498f505bd2d50dd +size 70648072 diff --git a/playground/qwen25vl_demo/inference/run_inference.py b/playground/qwen25vl_demo/inference/run_inference.py new file mode 100644 index 0000000000000000000000000000000000000000..1849860ed28a3714c41edc374d56a7f006459457 --- /dev/null +++ b/playground/qwen25vl_demo/inference/run_inference.py @@ -0,0 +1,195 @@ +""" +Qwen2.5-VL 批量 Inference 脚本 +数据来源: /mnt/hdfs/byte_tt_data_cu_vagcp/haogeng.liu/new_policy7w_v2_reformat/ +数据格式: parquet，每行含 messages（视频帧base64）+ extra_info（ASR/关键词等） +任务: 视频对比 / 视觉理解，对每条样本用 Qwen 做推理，保存结果 +""" + +import os, json, time, argparse +import pandas as pd +from pathlib import Path +from openai import OpenAI +from datetime import datetime +from tqdm import tqdm + +# ── 配置 ────────────────────────────────────────────────────────────────────── +DATA_DIR = Path("/mnt/hdfs/byte_tt_data_cu_vagcp/haogeng.liu/new_policy7w_v2_reformat") +OUT_DIR = Path("/mlx/users/jiashuo.fan/playground/qwen25vl_demo/inference/results") +VLLM_URL = "http://localhost:8000/v1" +MODEL = "qwen25vl" +MAX_TOKENS = 512 +TEMPERATURE = 0.7 + + +def build_messages_for_sample(row) -> list[dict]: + """将 parquet 一行转为 OpenAI 格式 messages。""" + msgs = row["messages"] + if isinstance(msgs, str): + msgs = json.loads(msgs) + + # 提取视频帧和文本 prompt（来自原始数据） + video_frames = [] + text_parts = [] + for turn in msgs: + if turn.get("role") != "user": + continue + content = turn.get("content", []) + if isinstance(content, str): + text_parts.append(content) + continue + for item in content: + t = item.get("type") + if t == "video": + video_frames.extend(item.get("video", [])) + elif t == "text" and item.get("text"): + text_parts.append(item["text"]) + + # 构建 content + content = [] + # 最多取 8 帧（两段视频各4帧），限制在 limit-mm-per-prompt image=10 内 + for frame_b64 in video_frames[:8]: + # 帧已经是 base64 JPEG bytes，需要加 data URI 前缀 + if not frame_b64.startswith("data:"): + frame_b64 = f"data:image/jpeg;base64,{frame_b64}" + content.append({"type": "image_url", "image_url": {"url": frame_b64}}) + + # 构建推理 prompt + extra = row.get("extra_info", {}) + if isinstance(extra, str): + extra = json.loads(extra) + + tags = extra.get("video1", {}).get("mt_diversity_tier3_tags", "") + kwds = extra.get("video1", {}).get("key_words", "") + asr = extra.get("video1", {}).get("asr", "[]") + + prompt = ( + "请分析这些视频帧，完成以下任务（用JSON格式回答）：\n" + "1. 描述视频的主要内容和场景\n" + "2. 识别视频中的主要动作或事件\n" + "3. 如果有多个视频，分析它们之间的相似性\n\n" + f"参考信息 - 标签: {tags}, 关键词: {kwds}\n" + "请返回JSON: {\"description\": \"...\", \"actions\": [...], \"similarity\": \"...\"}" + ) + content.append({"type": "text", "text": prompt}) + + return [{"role": "user", "content": content}] + + +def run_inference_on_file(client: OpenAI, parquet_path: Path, out_path: Path, + max_samples: int = None, resume: bool = True): + """对单个 parquet 文件跑 inference，支持断点续跑。""" + df = pd.read_parquet(parquet_path) + if max_samples: + df = df.head(max_samples) + + # 断点续跑：读已有结果 + done_ids = set() + results = [] + if resume and out_path.exists(): + with open(out_path) as f: + for line in f: + try: + r = json.loads(line) + done_ids.add(r["sample_id"]) + results.append(r) + except: pass + print(f" [断点续跑] 已有 {len(done_ids)} 条结果") + + out_path.parent.mkdir(parents=True, exist_ok=True) + writer = open(out_path, "a" if resume else "w") + + try: + for idx, row in tqdm(df.iterrows(), total=len(df), desc=parquet_path.name): + sample_id = f"{parquet_path.stem}_{idx}" + if sample_id in done_ids: + continue + + t0 = time.time() + try: + messages = build_messages_for_sample(row) + resp = client.chat.completions.create( + model=MODEL, + messages=messages, + max_tokens=MAX_TOKENS, + temperature=TEMPERATURE, + ) + answer = resp.choices[0].message.content + status = "ok" + except Exception as e: + answer = f"ERROR: {e}" + status = "error" + + extra = row.get("extra_info", {}) + if isinstance(extra, str): + try: extra = json.loads(extra) + except: extra = {} + + record = { + "sample_id": sample_id, + "status": status, + "elapsed_s": round(time.time() - t0, 2), + "model": MODEL, + "answer": answer, + "tags": extra.get("video1", {}).get("mt_diversity_tier3_tags", ""), + "language": extra.get("language", ""), + "timestamp": datetime.now().isoformat(), + } + writer.write(json.dumps(record, ensure_ascii=False) + "\n") + writer.flush() + finally: + writer.close() + + return len(df) - len(done_ids) + + +def main(): + parser = argparse.ArgumentParser(description="Qwen2.5-VL Batch Inference") + parser.add_argument("--max-files", type=int, default=None, help="最多处理几个 parquet 文件") + parser.add_argument("--max-samples", type=int, default=None, help="每个文件最多跑几条") + parser.add_argument("--hours", type=float, default=24, help="最多跑几小时（默认24h）") + parser.add_argument("--vllm-url", default=VLLM_URL) + parser.add_argument("--no-resume", action="store_true", help="不断点续跑，重新开始") + args = parser.parse_args() + + client = OpenAI(base_url=args.vllm_url, api_key="EMPTY") + + # 验证服务可用 + try: + client.models.list() + print(f"✓ vLLM 服务正常: {args.vllm_url}") + except Exception as e: + print(f"✗ vLLM 不可达: {e}") + return + + parquet_files = sorted(DATA_DIR.glob("*.parquet")) + if args.max_files: + parquet_files = parquet_files[:args.max_files] + + print(f"找到 {len(parquet_files)} 个 parquet 文件，开始 inference...") + print(f"输出目录: {OUT_DIR}") + print(f"最大运行时间: {args.hours} 小时") + + deadline = time.time() + args.hours * 3600 + total_done = 0 + + for pf in parquet_files: + if time.time() > deadline: + print(f"\n已达时间限制 ({args.hours}h)，停止。共处理 {total_done} 条。") + break + + out_path = OUT_DIR / (pf.stem + "_results.jsonl") + print(f"\n处理: {pf.name} → {out_path.name}") + + n = run_inference_on_file( + client, pf, out_path, + max_samples=args.max_samples, + resume=not args.no_resume, + ) + total_done += n + print(f" 完成 {n} 条，累计 {total_done} 条") + + print(f"\n全部完成！共处理 {total_done} 条，结果在 {OUT_DIR}") + + +if __name__ == "__main__": + main() diff --git a/playground/qwen25vl_demo/lib/libnvidia-ml.so.1 b/playground/qwen25vl_demo/lib/libnvidia-ml.so.1 new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/playground/qwen25vl_demo/serve.sh b/playground/qwen25vl_demo/serve.sh new file mode 100644 index 0000000000000000000000000000000000000000..70706434a4da43524b2bfb76aee7c8519a1868c5 --- /dev/null +++ b/playground/qwen25vl_demo/serve.sh @@ -0,0 +1,35 @@ +#!/bin/bash +# Launch vLLM OpenAI-compatible server for Qwen2.5-VL-72B-Instruct +# Uses tensor parallelism across 8 H100 GPUs + +MODEL=${MODEL_PATH:-"Qwen/Qwen2.5-VL-72B-Instruct"} +PORT=${PORT:-8000} +HOST=${HOST:-"0.0.0.0"} +TENSOR_PARALLEL=${TP:-4} # qwen2_5_vl_7b: 28 heads, divisible by 4; for 72B use TP=8 + +export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 + +# Fix: libnvidia-ml.so.1 stub in container points to empty file; use real 535.129.03 lib +SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +export LD_LIBRARY_PATH="${SCRIPT_DIR}/lib:${LD_LIBRARY_PATH}" + +source /mlx/users/jiashuo.fan/miniconda3/bin/activate qwen25vl + +echo "Starting vLLM server..." +echo " Model: ${MODEL}" +echo " Tensor parallel: ${TENSOR_PARALLEL}" +echo " Listen: ${HOST}:${PORT}" + +python -m vllm.entrypoints.openai.api_server \ + --model "${MODEL}" \ + --tensor-parallel-size ${TENSOR_PARALLEL} \ + --max-model-len 32768 \ + --max-num-seqs 8 \ + --gpu-memory-utilization 0.92 \ + --trust-remote-code \ + --limit-mm-per-prompt '{"image":10,"video":2}' \ + --enable-auto-tool-choice \ + --tool-call-parser hermes \ + --host ${HOST} \ + --port ${PORT} \ + --served-model-name "qwen25vl" diff --git a/playground/qwen25vl_demo/serve_pm2.sh b/playground/qwen25vl_demo/serve_pm2.sh new file mode 100644 index 0000000000000000000000000000000000000000..1ec90a9727e09a3e329273e4cb5ec24dc2ceaafd --- /dev/null +++ b/playground/qwen25vl_demo/serve_pm2.sh @@ -0,0 +1,21 @@ +#!/bin/bash +# vLLM 启动脚本（供 PM2 调用，不使用 nohup） +DEMO_DIR="/mlx/users/jiashuo.fan/playground/qwen25vl_demo" +export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 +export LD_LIBRARY_PATH="$DEMO_DIR/lib:$LD_LIBRARY_PATH" + +source /mlx/users/jiashuo.fan/miniconda3/bin/activate qwen25vl + +exec python -m vllm.entrypoints.openai.api_server \ + --model /mnt/bn/bohanzhainas1/models/Qwen3-VL-32B-Instruct \ + --tensor-parallel-size 4 \ + --max-model-len 32768 \ + --max-num-seqs 8 \ + --gpu-memory-utilization 0.92 \ + --trust-remote-code \ + --limit-mm-per-prompt '{"image":10,"video":2}' \ + --enable-auto-tool-choice \ + --tool-call-parser hermes \ + --host 0.0.0.0 \ + --port 8000 \ + --served-model-name qwen25vl diff --git a/playground/qwen25vl_demo/server.log b/playground/qwen25vl_demo/server.log new file mode 100644 index 0000000000000000000000000000000000000000..ba53b4d99bc0ade21242da61c2c4e41f037f2dc1 --- /dev/null +++ b/playground/qwen25vl_demo/server.log @@ -0,0 +1,29 @@ +INFO 03-15 08:24:14 [importing.py:44] Triton is installed but 0 active driver(s) found (expected 1). Disabling Triton to prevent runtime errors. +INFO 03-15 08:24:14 [importing.py:68] Triton not installed or not compatible; certain GPU-related functions will not be available. +W0315 08:24:15.551000 19745 /mnt/bn/bohanzhainas1/mlx/users/jiashuo.fan/miniconda3/envs/qwen25vl/lib/python3.11/site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' +Traceback (most recent call last): + File "", line 198, in _run_module_as_main + File "", line 88, in _run_code + File "/mlx/users/jiashuo.fan/miniconda3/envs/qwen25vl/lib/python3.11/site-packages/vllm/entrypoints/openai/api_server.py", line 541, in + parser = make_arg_parser(parser) + ^^^^^^^^^^^^^^^^^^^^^^^ + File "/mlx/users/jiashuo.fan/miniconda3/envs/qwen25vl/lib/python3.11/site-packages/vllm/entrypoints/openai/cli_args.py", line 353, in make_arg_parser + parser = AsyncEngineArgs.add_cli_args(parser) + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/mlx/users/jiashuo.fan/miniconda3/envs/qwen25vl/lib/python3.11/site-packages/vllm/engine/arg_utils.py", line 2185, in add_cli_args + parser = EngineArgs.add_cli_args(parser) + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/mlx/users/jiashuo.fan/miniconda3/envs/qwen25vl/lib/python3.11/site-packages/vllm/engine/arg_utils.py", line 1241, in add_cli_args + vllm_kwargs = get_kwargs(VllmConfig) + ^^^^^^^^^^^^^^^^^^^^^^ + File "/mlx/users/jiashuo.fan/miniconda3/envs/qwen25vl/lib/python3.11/site-packages/vllm/engine/arg_utils.py", line 358, in get_kwargs + return copy.deepcopy(_compute_kwargs(cls)) + ^^^^^^^^^^^^^^^^^^^^ + File "/mlx/users/jiashuo.fan/miniconda3/envs/qwen25vl/lib/python3.11/site-packages/vllm/engine/arg_utils.py", line 270, in _compute_kwargs + default = default.default_factory() # type: ignore[call-arg] + ^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/mlx/users/jiashuo.fan/miniconda3/envs/qwen25vl/lib/python3.11/site-packages/pydantic/_internal/_dataclasses.py", line 121, in __init__ + s.__pydantic_validator__.validate_python(ArgsKwargs(args, kwargs), self_instance=s) + File "/mlx/users/jiashuo.fan/miniconda3/envs/qwen25vl/lib/python3.11/site-packages/vllm/config/device.py", line 56, in __post_init__ + raise RuntimeError( +RuntimeError: Failed to infer device type, please set the environment variable `VLLM_LOGGING_LEVEL=DEBUG` to turn on verbose logging to help debug the issue. diff --git a/playground/qwen25vl_demo/setup_env.sh b/playground/qwen25vl_demo/setup_env.sh new file mode 100644 index 0000000000000000000000000000000000000000..772242c3186ef878c3ca0c79433ed34e024807c7 --- /dev/null +++ b/playground/qwen25vl_demo/setup_env.sh @@ -0,0 +1,56 @@ +#!/bin/bash +# Setup conda environment for Qwen2.5-VL-72B-Instruct +# CUDA 12.6, 8x H100 + +set -e + +CONDA=/mlx/users/jiashuo.fan/miniconda3/bin/conda +ENV_NAME=qwen25vl +ENV_PATH=/mlx/users/jiashuo.fan/miniconda3/envs/${ENV_NAME} + +echo "=========================================" +echo "Creating conda env: ${ENV_NAME}" +echo "=========================================" + +$CONDA create -n ${ENV_NAME} python=3.11 -y + +echo "=========================================" +echo "Installing PyTorch 2.5.1 (CUDA 12.6)" +echo "=========================================" + +$CONDA run -n ${ENV_NAME} pip install torch==2.5.1 torchvision==0.20.1 torchaudio==2.5.1 \ + --index-url https://download.pytorch.org/whl/cu124 + +echo "=========================================" +echo "Installing vLLM (supports Qwen2.5-VL)" +echo "=========================================" + +$CONDA run -n ${ENV_NAME} pip install vllm>=0.7.0 + +echo "=========================================" +echo "Installing Transformers & dependencies" +echo "=========================================" + +$CONDA run -n ${ENV_NAME} pip install \ + transformers>=4.49.0 \ + accelerate>=1.2.0 \ + qwen-vl-utils \ + pillow \ + requests \ + openai \ + gradio>=5.0.0 \ + numpy \ + decord \ + av \ + httpx + +echo "=========================================" +echo "Installing Flash Attention 2" +echo "=========================================" + +$CONDA run -n ${ENV_NAME} pip install flash-attn --no-build-isolation + +echo "=========================================" +echo "Done! Activate with:" +echo " source /mlx/users/jiashuo.fan/miniconda3/bin/activate ${ENV_NAME}" +echo "=========================================" diff --git a/playground/qwen25vl_demo/start.sh b/playground/qwen25vl_demo/start.sh new file mode 100644 index 0000000000000000000000000000000000000000..8c80e6fbaffe5e9baef33fa6a21f8fe170a4a4d4 --- /dev/null +++ b/playground/qwen25vl_demo/start.sh @@ -0,0 +1,121 @@ +#!/bin/bash +# 一键启动 Qwen vLLM + OpenClaw Gateway (via PM2) + +DEMO_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +VLLM_LOG="$DEMO_DIR/server.log" +GATEWAY_LOG="$DEMO_DIR/gateway.log" +VLLM_PORT=8000 +GATEWAY_PORT=18789 +TOKEN="qwen-local-token" +PM2="/home/tiger/.nvm/versions/node/v22.22.1/bin/pm2" + +GREEN='\033[0;32m'; YELLOW='\033[1;33m'; RED='\033[0;31m'; NC='\033[0m' +log() { echo -e "${GREEN}[✓]${NC} $1"; } +info() { echo -e "${YELLOW}[…]${NC} $1"; } +err() { echo -e "${RED}[✗]${NC} $1"; } + +echo "" +echo " ╔══════════════════════════════════════╗" +echo " ║ Qwen2.5-VL + OpenClaw 启动脚本 ║" +echo " ╚══════════════════════════════════════╝" +echo "" + +# ── 停止旧进程 ── +info "停止旧进程..." +"$PM2" delete all 2>/dev/null || true +pkill -f "vllm.entrypoints.openai.api_server" 2>/dev/null || true +pkill -f "openclaw-gateway" 2>/dev/null || true +pkill -f "openclaw" 2>/dev/null || true +sleep 3 + +# ── 启动 PM2 应用 ── +info "通过 PM2 启动所有服务..." +export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 +export LD_LIBRARY_PATH="$DEMO_DIR/lib:$LD_LIBRARY_PATH" +cd "$DEMO_DIR" +"$PM2" start ecosystem.config.js 2>&1 +sleep 3 + +# ── 等待 vLLM 就绪 ── +info "等待 vLLM 模型加载（约3~5分钟）..." +WAIT_SECONDS=0 +while true; do + if curl -sf --max-time 3 http://localhost:${VLLM_PORT}/health > /dev/null 2>&1; then + log "vLLM 就绪！(用时 ${WAIT_SECONDS}s)" + break + fi + if ! "$PM2" list 2>/dev/null | grep -q "vllm-qwen.*online"; then + err "vLLM 进程异常退出，查看日志: $VLLM_LOG" + tail -20 "$VLLM_LOG" + exit 1 + fi + printf "." + sleep 10 + WAIT_SECONDS=$((WAIT_SECONDS + 10)) + if [ $WAIT_SECONDS -gt 600 ]; then + err "vLLM 等待超时 (600s)" + exit 1 + fi +done +echo "" + +# ── 等待 Gateway 就绪 ── +info "等待 OpenClaw Gateway..." +WAIT_SECONDS=0 +while [ $WAIT_SECONDS -lt 60 ]; do + if curl -sf --max-time 3 http://localhost:${GATEWAY_PORT}/__openclaw__/health > /dev/null 2>&1; then + log "OpenClaw Gateway 就绪！" + break + fi + sleep 3 + WAIT_SECONDS=$((WAIT_SECONDS + 3)) +done +if [ $WAIT_SECONDS -ge 60 ]; then + err "Gateway 未能在60秒内就绪，查看日志: $GATEWAY_LOG" +fi + +# ── 启动 bore 公网隧道 ── +info "启动 bore 公网隧道 (bore.pub:$GATEWAY_PORT + bore.pub:18788)..." +pkill -f "run_bore.sh\|bore local" 2>/dev/null || true +sleep 1 +nohup bash "$DEMO_DIR/run_bore.sh" >> "$DEMO_DIR/bore.log" 2>&1 & +echo $! > "$DEMO_DIR/.bore.pid" +BORE_BIN="/home/tiger/.nvm/versions/node/v22.22.1/bin/bore" +# vLLM API 隧道（18788） +nohup bash -c "while true; do \"$BORE_BIN\" local 8000 --to bore.pub --port 18788; sleep 5; done" >> "$DEMO_DIR/bore8000.log" 2>&1 & +echo $! > "$DEMO_DIR/.bore8000.pid" +# Open WebUI 隧道（18787） +nohup bash -c "while true; do \"$BORE_BIN\" local 18790 --to bore.pub --port 18787; sleep 5; done" >> "$DEMO_DIR/bore_webui.log" 2>&1 & +echo $! > "$DEMO_DIR/.bore_webui.pid" +sleep 8 +if grep -q "listening at bore.pub" "$DEMO_DIR/bore.log" 2>/dev/null; then + log "bore 隧道就绪：bore.pub:$GATEWAY_PORT (gateway) + bore.pub:18788 (vLLM) + bore.pub:18787 (WebUI)" +else + info "bore 隧道可能未就绪，查看: $DEMO_DIR/bore.log" +fi + +# ── 保存 PM2 状态 ── +"$PM2" save 2>/dev/null +log "PM2 状态已保存" + +# ── 完成 ── +SERVER_IP=$(hostname -I | awk '{print $1}') +echo "" +echo " ╔══════════════════════════════════════════════════════════╗" +echo " ║ 启动完成！ ║" +echo " ╠══════════════════════════════════════════════════════════╣" +printf " ║ vLLM API: http://%-37s║\n" "$SERVER_IP:$VLLM_PORT/v1" +printf " ║ Gateway: ws://%-38s║\n" "$SERVER_IP:$GATEWAY_PORT" +printf " ║ Token: %-43s║\n" "$TOKEN" +echo " ╠══════════════════════════════════════════════════════════╣" +echo " ║ Mac 端配置（运行一次）： ║" +echo " ║ bash mac_setup.sh ║" +echo " ║ Mac 端连接（SSH隧道）： ║" +printf " ║ ssh -fN -L %d:localhost:%d tiger@%s ║\n" "$GATEWAY_PORT" "$GATEWAY_PORT" "$SERVER_IP" +echo " ║ openclaw tui ║" +echo " ╠══════════════════════════════════════════════════════════╣" +echo " ║ 日志: tail -f $VLLM_LOG" +echo " ║ 监控: pm2 monit" +echo " ║ 停止: bash stop.sh" +echo " ╚══════════════════════════════════════════════════════════╝" +echo "" diff --git a/playground/qwen25vl_demo/stop.sh b/playground/qwen25vl_demo/stop.sh new file mode 100644 index 0000000000000000000000000000000000000000..0eb081c68ea53689e59298103e2a94aec4529fc7 --- /dev/null +++ b/playground/qwen25vl_demo/stop.sh @@ -0,0 +1,14 @@ +#!/bin/bash +# 停止所有服务 +DEMO_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +PM2="/home/tiger/.nvm/versions/node/v22.22.1/bin/pm2" +GREEN='\033[0;32m'; NC='\033[0m' + +"$PM2" delete all 2>/dev/null && echo -e "${GREEN}[✓]${NC} PM2 服务已停止" || true +pkill -f "vllm.entrypoints.openai.api_server" 2>/dev/null || true +pkill -f "openclaw-gateway" 2>/dev/null || true +pkill -f "openclaw" 2>/dev/null || true +pkill -f "run_bore.sh\|bore local" 2>/dev/null && echo -e "${GREEN}[✓]${NC} bore 隧道已停止" || true +pkill -f "gpu_stress" 2>/dev/null || true +rm -f "$DEMO_DIR/.vllm.pid" "$DEMO_DIR/.gateway.pid" "$DEMO_DIR/.monitor.pid" "$DEMO_DIR/.bore.pid" "$DEMO_DIR/.bore8000.pid" +echo "Done." diff --git a/playground/qwen25vl_demo/stress.log b/playground/qwen25vl_demo/stress.log new file mode 100644 index 0000000000000000000000000000000000000000..51b21802990e9e8c9a45ab79cbc8bfe7f29d6fa3 --- /dev/null +++ b/playground/qwen25vl_demo/stress.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:35663d0fb271d51755bd81a9899ffff72683601a78879c67854c88eb16cb2103 +size 139525383 diff --git a/playground/qwen25vl_demo/watchdog_cron.sh b/playground/qwen25vl_demo/watchdog_cron.sh new file mode 100644 index 0000000000000000000000000000000000000000..25ace7f8dcfaa8ea371d2cf067fa1bf5c73a130d --- /dev/null +++ b/playground/qwen25vl_demo/watchdog_cron.sh @@ -0,0 +1,12 @@ +#!/bin/bash +DEMO_DIR="/mlx/users/jiashuo.fan/playground/qwen25vl_demo" +OPENCLAW_BIN="/home/tiger/.nvm/versions/node/v22.22.1/bin/openclaw" +TOKEN="qwen-local-token" + +# Check gateway only (vLLM auto-restart handled by monitor.sh) +if ! pgrep -f "openclaw-gateway" > /dev/null 2>&1; then + echo "[$(date)] Gateway not running, restarting..." + nohup "$OPENCLAW_BIN" gateway run --token "$TOKEN" --bind lan --force \ + >> "$DEMO_DIR/gateway.log" 2>&1 & + echo $! > "$DEMO_DIR/.gateway.pid" +fi diff --git a/playground/qwen25vl_demo/webui.log b/playground/qwen25vl_demo/webui.log new file mode 100644 index 0000000000000000000000000000000000000000..0439c74e5464357359b6f27a25c7b85351650b0c --- /dev/null +++ b/playground/qwen25vl_demo/webui.log @@ -0,0 +1,294 @@ +2026-03-14 20:55:16: INFO [alembic.runtime.migration] Context impl SQLiteImpl. +2026-03-14 20:55:16: INFO [alembic.runtime.migration] Will assume non-transactional DDL. +2026-03-14 20:55:17: INFO [alembic.runtime.migration] Running upgrade -> 7e5b5dc7342b, init +2026-03-14 20:55:17: INFO [alembic.runtime.migration] Running upgrade 7e5b5dc7342b -> ca81bd47c050, Add config table +2026-03-14 20:55:17: INFO [alembic.runtime.migration] Running upgrade ca81bd47c050 -> c0fbf31ca0db, Update file table +2026-03-14 20:55:17: INFO [alembic.runtime.migration] Running upgrade c0fbf31ca0db -> 6a39f3d8e55c, Add knowledge table +2026-03-14 20:55:17: INFO [alembic.runtime.migration] Running upgrade 6a39f3d8e55c -> 242a2047eae0, Update chat table +2026-03-14 20:55:17: INFO [alembic.runtime.migration] Running upgrade 242a2047eae0 -> 1af9b942657b, Migrate tags +2026-03-14 20:55:17: INFO [alembic.runtime.migration] Running upgrade 1af9b942657b -> 3ab32c4b8f59, Update tags +2026-03-14 20:55:18: INFO [alembic.runtime.migration] Running upgrade 3ab32c4b8f59 -> c69f45358db4, Add folder table +2026-03-14 20:55:18: INFO [alembic.runtime.migration] Running upgrade c69f45358db4 -> c29facfe716b, Update file table path +2026-03-14 20:55:18: INFO [alembic.runtime.migration] Running upgrade c29facfe716b -> af906e964978, Add feedback table +2026-03-14 20:55:18: INFO [alembic.runtime.migration] Running upgrade af906e964978 -> 4ace53fd72c8, Update folder table and change DateTime to BigInteger for timestamp fields +2026-03-14 20:55:18: INFO [alembic.runtime.migration] Running upgrade 4ace53fd72c8 -> 922e7a387820, Add group table +2026-03-14 20:55:18: INFO [alembic.runtime.migration] Running upgrade 922e7a387820 -> 57c599a3cb57, Add channel table +2026-03-14 20:55:18: INFO [alembic.runtime.migration] Running upgrade 57c599a3cb57 -> 7826ab40b532, Update file table +2026-03-14 20:55:18: INFO [alembic.runtime.migration] Running upgrade 7826ab40b532 -> 3781e22d8b01, Update message & channel tables +2026-03-14 20:55:19: INFO [alembic.runtime.migration] Running upgrade 3781e22d8b01 -> 9f0c9cd09105, Add note table +2026-03-14 20:55:19: INFO [alembic.runtime.migration] Running upgrade 9f0c9cd09105 -> d31026856c01, Update folder table data +2026-03-14 20:55:19: INFO [alembic.runtime.migration] Running upgrade d31026856c01 -> 018012973d35, Add indexes +2026-03-14 20:55:19: INFO [alembic.runtime.migration] Running upgrade 018012973d35 -> 3af16a1c9fb6, update user table +2026-03-14 20:55:19: INFO [alembic.runtime.migration] Running upgrade 3af16a1c9fb6 -> 38d63c18f30f, Add oauth_session table +2026-03-14 20:55:20: INFO [alembic.runtime.migration] Running upgrade 38d63c18f30f -> a5c220713937, Add reply_to_id column to message +2026-03-14 20:55:20: INFO [alembic.runtime.migration] Running upgrade a5c220713937 -> 37f288994c47, add_group_member_table +2026-03-14 20:55:20: INFO [alembic.runtime.migration] Running upgrade 37f288994c47 -> 2f1211949ecc, Update messages and channel member table +2026-03-14 20:55:20: INFO [alembic.runtime.migration] Running upgrade 2f1211949ecc -> b10670c03dd5, Update user table +2026-03-14 20:55:21: INFO [alembic.runtime.migration] Running upgrade b10670c03dd5 -> 90ef40d4714e, Update channel and channel members table +2026-03-14 20:55:21: INFO [alembic.runtime.migration] Running upgrade 90ef40d4714e -> 3e0e00844bb0, Add knowledge_file table +2026-03-14 20:55:22: INFO [alembic.runtime.migration] Running upgrade 3e0e00844bb0 -> 6283dc0e4d8d, Add channel file table +2026-03-14 20:55:22: INFO [alembic.runtime.migration] Running upgrade 6283dc0e4d8d -> 81cc2ce44d79, Update channel file and knowledge table +2026-03-14 20:55:22: INFO [alembic.runtime.migration] Running upgrade 81cc2ce44d79 -> c440947495f3, Add chat_file table +2026-03-14 20:55:22: INFO [alembic.runtime.migration] Running upgrade c440947495f3 -> 374d2f66af06, Add prompt history table +2026-03-14 20:55:23: INFO [alembic.runtime.migration] Running upgrade 374d2f66af06 -> 8452d01d26d7, Add chat_message table +2026-03-14 20:55:23: INFO [alembic.runtime.migration] Running upgrade 8452d01d26d7 -> f1e2d3c4b5a6, Add access_grant table +2026-03-14 20:55:23: INFO [alembic.runtime.migration] Running upgrade f1e2d3c4b5a6 -> a1b2c3d4e5f6, Add skill table +2026-03-14 20:55:24: INFO [alembic.runtime.migration] Running upgrade a1b2c3d4e5f6 -> b2c3d4e5f6a7, add scim column to user table +2026-03-14 20:55:24: WARNI [open_webui.env] +2026-03-14 20:55:24: +2026-03-14 20:55:24: WARNING: CORS_ALLOW_ORIGIN IS SET TO '*' - NOT RECOMMENDED FOR PRODUCTION DEPLOYMENTS. +2026-03-14 20:55:24: +2026-03-14 20:58:13: WARNI [langchain_community.utils.user_agent] USER_AGENT environment variable not set, consider setting it to identify your requests. +2026-03-14 21:00:22: Creating knowledge table +2026-03-14 21:00:22: Migrating data from document table to knowledge table +2026-03-14 21:00:22: Converting 'chat' column to JSON 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