This project provides a Streamlit demo of the Mixture-of-Agents (MOA) architecture, leveraging Groq LLMs for enhanced conversational AI. It targets developers and researchers interested in exploring advanced multi-agent system configurations for complex task execution and response generation. The benefit lies in a user-friendly interface for experimenting with and visualizing MOA's capabilities.

How It Works

The application implements the MOA architecture, where a primary agent orchestrates a series of "layer" agents. Each layer agent, configured with specific prompts and models, processes the input sequentially, refining the output before it reaches the main agent for the final response. This layered approach aims to improve the quality and coherence of AI-generated text by breaking down complex tasks into manageable steps.

Quick Start & Requirements

• Install dependencies: pip install -r requirements.txt
• Set Groq API key: Create a .env file with GROQ_API_KEY=your_api_key_here.
• Run the app: streamlit run app.py
• Requires Python 3.x and a Groq API key.
• Official docs: https://github.com/skapadia3214/groq-moa

Highlighted Details

• Interactive Streamlit UI for configuring main model, cycles, and layer agents.
• Real-time response streaming and visualization of intermediate layer outputs.
• Implements the Mixture-of-Agents architecture as proposed in arXiv:2406.04692.
• Includes both a Streamlit app and a CLI version (main.py).

Maintenance & Community

The project is maintained by skapadia3214. Contributions are welcome via pull requests. Contact is available via GitHub issues or directly at skapadia@groq.com.

Licensing & Compatibility

Licensed under the MIT License. This permissive license allows for commercial use and integration into closed-source projects.

Limitations & Caveats

The project is presented as a demo and may not be production-ready. Configuration is primarily through the UI or direct code modification, with limited explicit error handling for invalid configurations.