This is a simplified agentic workflow process based on the Mixture of Agents (MoA) system by Wang et al. (2024). "Mixture-of-Agents Enhances Large Language Model Capabilities".

This demo is a 3-layer MoA with 4 open-source Qwen2, Qwen 1.5, Mixtral, and dbrx models. Qwen2 acts as the aggregator in the final layer. Check out the links.txt for the link to the GSM8K benchmark and datasets. For more details, watch the full tutorial video on YouTube at the end of this page.

1. Export your Together AI API key as an environment variable using bash_profile or Zshrc and update your shell with the new variable. If you want to set up the key inside your Python script, follow the file integrate_api_key here.
2. git clone the MoA GitHub project https://github.com/togethercomputer/MoA.git into your project directory.
3. pip install -r requirements.txt from the MoA directory.
4. Run the Python file bot.py

For the detailed explanation of the Mixture of Agents (MoA) system and paper and how to run MoA AI agents locally watch this video: