AIDomesticate (AID)

AIDomesticate (AID) is a modular and extensible framework designed to simplify the creation and management of AI agents using LangChain and LLMs. The framework is built to support various maturity phases of AI agent development, ensuring a gradual and controlled transition from human-in-the-loop systems to fully autonomous operations.

Key Features

•	Modular Design: Easily create, extend, and integrate different AI agents, including Planners, Makers, and Supervisors.
•	Maturity Phases: Implement systems with distinct phases of maturity:
•	Phase 1: Human debugging for refining agent interactions.
•	Phase 2: Supervisor-led iteration with human approval for critical steps.
•	Phase 3: Full autonomy with minimal human intervention.
•	Specialist Supervisors: Utilize specialized supervisors for planning and execution tasks, enhanced by the Retrieval-Augmented Generation (RAG) approach for better context and accuracy.
•	Open Source: Licensed under the MIT License, encouraging collaborative development and contribution from the community.

Getting Started

Please refer to the Getting Started section of the documentation for detailed instructions.

Prerequisites

•	Node.js
•	OpenAI GPT-4 API key
•	LangChain library

Contributing to AIDomesticate

We welcome contributions to the AIDomesticate project! Please follow these guidelines to ensure a smooth process.

How to Contribute

1. Fork the repository.
2. Create a new branch for your feature or bugfix.
3. Make your changes.
4. Ensure that your code follows the project's coding standards.
5. Commit your changes with a clear message.
6. Push your branch to your forked repository.
7. Open a pull request against the main branch.

Reporting Issues

If you encounter any issues, please open an issue on GitHub with a detailed description and steps to reproduce the problem.

Code of Conduct

Please read and adhere to our Code of Conduct.

License

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

By using AIDomesticate, developers can focus on the core functionality of their AI agents while leveraging a robust framework for managing and iterating on their designs. Join us in building an innovative and collaborative AI ecosystem!