| --- |
| license: apache-2.0 |
| pretty_name: agentx-mini |
| task_categories: |
| - text-generation |
| tags: |
| - llm |
| - inference |
| - agentic |
| - benchmarking |
| - kv-cache |
| - multi-turn |
| - subagents |
| size_categories: |
| - n<1K |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: traces.jsonl |
| --- |
| |
| # agentx-mini |
|
|
| **agentx-mini** is a smaller workload for benchmarking local LLM servers, derived from |
| [semianalysisai/cc-traces-weka-062126-256k](https://huggingface.co/datasets/semianalysisai/cc-traces-weka-062126-256k). |
| It contains **200 sessions and 9,439 model calls**, including **1,363 subagent calls**. |
|
|
| Changes from the original dataset: |
|
|
| - Divide input and output lengths by **8**, rounding each output up. Hash IDs stay the same; logical blocks shrink from 64 to 8 tokens. |
| - Divide active request time by **8** and shorten idle gaps. Replay uses a **1-second idle cap**. |
| - Keep complete sessions with **less than 10,000 requested output tokens**, counting all subagents and auxiliary calls. |
| - Preserve request grouping, spawn/join dependencies, shared prompt content, and reference overlaps. Actual replay overlap depends on server speed. |
|
|
| ## Stats |
|
|
| ```text |
| traces: 200 |
| main_turns: 8,076 |
| subagent_groups: 76 |
| subagent_inner_requests: 1,363 |
| total_model_requests: 9,439 |
| total_input_tokens: 126,413,728 |
| total_output_tokens: 962,854 |
| ``` |
|
|
| Main turns are top-level calls. Input totals include repeated prefixes; actual |
| prefill depends on the server's prefix caching. Rendered prompts add |
| tokenizer/chat-template overhead. |
|
|
| ## Files and reproduction |
|
|
| `traces.jsonl` contains the scaled Weka records; `stats.txt` contains their totals. |
| AgentX Harness handles prompt synthesis and replay using the target model's tokenizer. |
|
|
| To rebuild agentx-mini using [distill.py](distill.py): |
|
|
| ```sh |
| pip install huggingface-hub orjson |
| python distill.py --output rebuilt |
| ``` |
|
|
| ## Run agentx-mini with AgentX Harness |
|
|
| Requires Python 3.11–3.13. Install in a dedicated virtual environment, following |
| the [AgentX Harness README](https://github.com/SemiAnalysisAI/agentx-harness#install-and-run-agentx): |
|
|
| ```bash |
| python3 -m venv .venv |
| source .venv/bin/activate |
| pip install agentx-harness==1.0.7 |
| ``` |
|
|
| **Set the block size for agentx-mini.** AgentX 1.0.7 needs an adjustment for this |
| dataset's 8-token blocks. In the activated virtual environment, locate the |
| installed plugin configuration: |
|
|
| ```bash |
| python -c 'from pathlib import Path; import aiperf.plugin; print(Path(aiperf.plugin.__file__).with_name("plugins.yaml"))' |
| ``` |
|
|
| Open that file. Under `public_dataset_loader` → `weka_hf` → `metadata`, change |
| `default_block_size: 64` to `default_block_size: 8`. This setting applies to all |
| `weka_hf` datasets in this environment; reinstalling the harness can reset it. |
|
|
| 1. **Download agentx-mini** into a local directory. |
| 2. **Start your local LLM server** and load your model, for example using |
| `llama-server`. It must expose an OpenAI-compatible API. Enable parallel |
| request slots to exercise subagents. Allow up to 32,000 tokens per request |
| for input plus output, with additional room for chat-template overhead. |
| Keep the server running during the benchmark. |
| 3. **Configure AgentX.** Save the configuration below as `benchmark.yaml` beside |
| `traces.jsonl`. Replace the served model name, tokenizer, and server URL with |
| your server's settings. Set `hf_weka_dataset` to the **absolute path** of the |
| downloaded dataset directory (run `pwd` there to get it). |
|
|
| ```yaml |
| random_seed: 42 |
| benchmark: |
| models: [YOUR_SERVED_MODEL_NAME] |
| tokenizer: |
| name: YOUR_TOKENIZER |
| endpoint: |
| urls: [http://127.0.0.1:8000] |
| streaming: true |
| extra: {ignore_eos: true} |
| use_legacy_max_tokens: true |
| datasets: |
| - name: default |
| type: public |
| dataset: weka_hf |
| hf_weka_dataset: /absolute/path/to/agentx-mini |
| sampling: sequential |
| trace_idle_gap_cap_seconds: 1 |
| phases: |
| - name: profiling |
| type: concurrency |
| timing_mode: agentic_replay |
| concurrency: 1 |
| duration: 1200 |
| trajectory_start_min_ratio: 0 |
| trajectory_start_max_ratio: 0 |
| ``` |
|
|
| Run from that directory: |
|
|
| ```bash |
| agentx profile \ |
| --config benchmark.yaml \ |
| --output-artifact-dir ./results/agentx-mini |
| ``` |
|
|
| **Automatic download:** instead of downloading first, set `hf_weka_dataset` to |
| `SocialLocalMobile/agentx-mini` and run the same command. |
|
|
| ## License |
|
|
| [Apache 2.0](LICENSE), matching the source dataset published by SemiAnalysis |
| from its Claude Code proxy traces. The dataset, script, and documentation in |
| this repository are distributed under these terms. |
|
|
| **Modified files:** `traces.jsonl` is a scaled and filtered derivative of source |
| revision [`8fecd2f`](https://huggingface.co/datasets/semianalysisai/cc-traces-weka-062126-256k/tree/8fecd2fc56694469f758f0afbbb6335ad3043740); |
| `stats.txt` is regenerated, and this README and `.gitattributes` are adapted for |
| agentx-mini. The data changes are listed above. References to SemiAnalysis |
| identify the source and do not imply endorsement. |
|
|
