autogen/python/packages/agbench/benchmarks/GAIA

• GAIA Benchmark
• • • Setup Environment Variables for AgBench
    • Running GAIA
  • References

GAIA Benchmark

This scenario implements the GAIA agent benchmark. Before you begin, make sure you have followed instruction in ../README.md to prepare your environment.

Setup Environment Variables for AgBench

Navigate to GAIA

cd benchmarks/GAIA

Update config.yaml to point to your model host, as appropriate. The default configuration points to 'gpt-4o'.

Now initialize the tasks.

python Scripts/init_tasks.py

Note: This will attempt to download GAIA from Hugginface, but this requires authentication.

The resulting folder structure should look like this:

.
./Downloads
./Downloads/GAIA
./Downloads/GAIA/2023
./Downloads/GAIA/2023/test
./Downloads/GAIA/2023/validation
./Scripts
./Templates
./Templates/TeamOne

Then run Scripts/init_tasks.py again.

Once the script completes, you should now see a folder in your current directory called Tasks that contains one JSONL file per template in Templates.

Running GAIA

Now to run a specific subset of GAIA use:

agbench run Tasks/gaia_validation_level_1__MagenticOne.jsonl

You should see the command line print the raw logs that shows the agents in action To see a summary of the results (e.g., task completion rates), in a new terminal run the following:

agbench tabulate Results/gaia_validation_level_1__MagenticOne/

References

GAIA: a benchmark for General AI Assistants <br/>
Grégoire Mialon, Clémentine Fourrier, Craig Swift, Thomas Wolf, Yann LeCun, Thomas Scialom <br/>
https://arxiv.org/abs/2311.12983