mirror of
https://github.com/microsoft/agent-framework.git
synced 2026-06-16 21:04:09 +08:00
Eric Zhu
70 lines
1.9 KiB
Markdown
70 lines
1.9 KiB
Markdown
# Agent Framework Lab - GAIA
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The GAIA benchmark can be used for evaluating agents and workflows built using the Agent Framework.
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It includes built-in benchmarks as well as utilities for running custom evaluations.
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> **Note**: This module is part of the consolidated `agent-framework-lab` package. Install the package with the `gaia` extra to use this module.
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## Setup
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Install from source with GAIA dependencies:
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```bash
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git clone https://github.com/microsoft/agent-framework.git
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cd agent-framework/python/packages/lab
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pip install -e ".[gaia]"
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```
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Set up Hugging Face token:
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```bash
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export HF_TOKEN="hf\*..." # must have access to gaia-benchmark/GAIA
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```
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## Create an evaluation script
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Create a Python script (e.g., `run_gaia.py`) with the following content:
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```python
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from agent_framework.lab.gaia import GAIA, Task, Prediction, GAIATelemetryConfig
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async def run_task(task: Task) -> Prediction:
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return Prediction(prediction="answer here", messages=[])
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async def main() -> None:
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# Optional: Enable telemetry for detailed tracing
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telemetry_config = GAIATelemetryConfig(
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enable_tracing=True,
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trace_to_file=True,
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file_path="gaia_traces.jsonl"
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)
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runner = GAIA(telemetry_config=telemetry_config)
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await runner.run(run_task, level=1, max_n=5, parallel=2)
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```
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See the [gaia_sample.py](./samples/gaia_sample.py) for more detail.
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### Run the evaluation
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Run the evaluation script using `uv`:
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```bash
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uv run python run_gaia.py
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```
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By default, the script will first look for cached GAIA data in the `data_gaia_hub` directory,
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and download it if not found.
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The result will be saved to `gaia_results_<timestamp>.jsonl`.
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**Don't run the script inside this directory because it will confuse the local `agent_framework` namespace
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package with the real one.**
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## View results
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We provide a console viewer for reading GAIA results:
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```bash
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uv run gaia_viewer "gaia_results_<timestamp>.jsonl" --detailed
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```
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