Mixture-of-Agents Demo Powered by Groq

This Streamlit application showcases the Mixture of Agents (MOA) architecture proposed by Together AI, powered by Groq LLMs. It allows users to interact with a configurable multi-agent system for enhanced AI-driven conversations.

Source: Adaptation of Together AI Blog - Mixture of Agents

Features

Interactive chat interface powered by MOA
Configurable main model and layer agents
Real-time streaming of responses
Visualization of intermediate layer outputs
Customizable agent parameters through the UI

Installation

Clone the repository:

git clone https://github.com/skapadia3214/groq-moa.git
cd groq-moa

Install the required dependencies:
```
pip install -r requirements.txt
```
Set up your environment variables: Create a .env file in the root directory and add your Groq API key:
```
GROQ_API_KEY=your_api_key_here
```

Usage

Run the Streamlit app:
```
streamlit run app.py
```
Open your web browser and navigate to the URL provided by Streamlit (usually http://localhost:8501).
Use the sidebar to configure the MOA settings:
- Select the main model
- Set the number of cycles
- Customize the layer agent configuration
Start chatting with the MOA system using the input box at the bottom of the page.

Project Structure

app.py: Main Streamlit application file
moa/: Package containing the MOA implementation
- __init__.py: Package initializer
- moa.py: Core MOA agent implementation
- prompts.py: System prompts for the agents
main.py: CLI version of the MOA chat interface
requirements.txt: List of Python dependencies
static/: Directory for static assets (images, etc.)

Configuration

The MOA system can be configured through the Streamlit UI or by modifying the default configuration in app.py. The main configurable parameters are:

Main model: The primary language model used for generating final responses
Number of cycles: How many times the layer agents are invoked before the main agent
Layer agent configuration: A JSON object defining the system prompts, model names, and other parameters for each layer agent

Contributing

Contributions to this project are welcome! Please follow these steps to contribute:

Fork the repository
Create a new branch for your feature or bug fix
Make your changes and commit them with descriptive commit messages
Push your changes to your fork
Submit a pull request to the main repository

Please ensure that your code adheres to the project's coding standards and includes appropriate tests and documentation.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Acknowledgements

Groq for providing the underlying language models
Together AI for proposing the Mixture of Agents architecture and providing the conceptual image
Streamlit for the web application framework

Citation

This project implements the Mixture-of-Agents architecture proposed in the following paper:

@article{wang2024mixture,
  title={Mixture-of-Agents Enhances Large Language Model Capabilities},
  author={Wang, Junlin and Wang, Jue and Athiwaratkun, Ben and Zhang, Ce and Zou, James},
  journal={arXiv preprint arXiv:2406.04692},
  year={2024}
}

For more information about the Mixture-of-Agents concept, please refer to the original research paper and the Together AI blog post.

Contact

For questions or support, please open an issue on the GitHub repository or contact skapadia@groq.com directly.

SMAshhar/groq-moa