We present Workforce, a hierarchical multi-agent framework that decouples planning from execution through a modular architecture with a domain-agnostic Planner, Coordinator, and specialized Workers. This enables cross-domain transfer by allowing worker modification without full system retraining. On the GAIA benchmark, Workforce achieves state-of-the-art 69.70% accuracy, outperforming commercial systems.

This repository contains inference part code for the OWL framework (Workforce).

The framework is based on camel-0.2.46 version with minor modifications. To reproduce Workforce inference performance on GAIA benchmark (69.70% - Claude-3.7 accuracy on GAIA benchmark, pass@1, and 60.61% - GPT-4o accuracy on GAIA benchmark, pass@3), follow the steps below:

1. Create a Python 3.11 Conda environment:

conda create -n owl python=3.11

2. Install the required packages:

pip install -r requirements.txt

3. Set up envionment variables:

copy .env.example to .env and set the environment variables, and set the keys in .env file.

4. Run the inference:

• For reproducing results using GPT-4o, run:

python run_gaia_workforce.py

• For reproducing results using Claude-3.7, run:

python run_gaia_workforce_claude.py

You can modify test_idx variable to specify the test case.