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* Python: add first-pass feature usage telemetry Add the 128-bit feature accumulator, package-local indexes, activation markers, and destination-scoped User-Agent emission for the initial Python implementation slice. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Copilot-Session: 346bf168-b668-4c4a-a8db-a67282ee5e5f * Python: track declarative feature usage Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Copilot-Session: 346bf168-b668-4c4a-a8db-a67282ee5e5f * Python: complete feature usage telemetry Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Copilot-Session: 346bf168-b668-4c4a-a8db-a67282ee5e5f * Python: report core version in User-Agent Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Copilot-Session: 346bf168-b668-4c4a-a8db-a67282ee5e5f * Python: configure Lab telemetry import path Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Copilot-Session: 346bf168-b668-4c4a-a8db-a67282ee5e5f * Python: preserve telemetry transport behavior Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Copilot-Session: 346bf168-b668-4c4a-a8db-a67282ee5e5f * Python: preserve caller-owned Foundry transports Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Copilot-Session: 346bf168-b668-4c4a-a8db-a67282ee5e5f * Python: remove stale Anthropic test import Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Copilot-Session: 346bf168-b668-4c4a-a8db-a67282ee5e5f --------- Copilot-Session: 346bf168-b668-4c4a-a8db-a67282ee5e5f
Agent Framework Lab - GAIA
The GAIA benchmark can be used for evaluating agents and workflows built using the Agent Framework. It includes built-in benchmarks as well as utilities for running custom evaluations.
Note
: This module is part of the consolidated
agent-framework-labpackage. Install the package with thegaiaextra to use this module.
Setup
Install the agent-framework-lab package with GAIA dependencies:
pip install "agent-framework-lab[gaia]"
Set up Hugging Face token:
export HF_TOKEN="hf\*..." # must have access to gaia-benchmark/GAIA
Create an evaluation script
Create a Python script (e.g., run_gaia.py) with the following content:
from agent_framework.lab.gaia import GAIA, Task, Prediction, GAIATelemetryConfig
async def run_task(task: Task) -> Prediction:
return Prediction(prediction="answer here", messages=[])
async def main() -> None:
# Optional: Enable telemetry for detailed tracing
telemetry_config = GAIATelemetryConfig(
enable_tracing=True,
trace_to_file=True,
file_path="gaia_traces.jsonl"
)
runner = GAIA(telemetry_config=telemetry_config)
await runner.run(run_task, level=1, max_n=5, parallel=2)
See the gaia_sample.py for more detail.
View results
We provide a console viewer for reading GAIA results:
uv run gaia_viewer "gaia_results_<timestamp>.jsonl" --detailed