WhiskerRAG

A lightweight and flexible RAG (Retrieval-Augmented Generation) framework.

Features ✨

• [Perception] WhiskerRAG is a lightweight RAG (Retrieval-Augmented Generation) framework that enhances text generation through efficient information retrieval.

• [Flexibility] WhiskerRAG enables customization of vector databases and file embedding systems through a plugin architecture, allowing users to tailor the RAG system to their specific needs.

Project Structure 📁

├── server/       # FastAPI Backend server
    ├── api/      # API endpoints
    ├── plugins/  # Plugin modules
    ├── core/     # Core functionalities
├── web/      # Frontend client
├── docker/   # Docker images
└── lambda_task_subscriber/ # AWS Lambda functions

Prerequisites 🛠️

# Install AWS SAM CLI
python3 -m pip install aws-sam-cli

# Verify installation
sam --version

Installation 📦

[Installation instructions here]

Quick Start 🚀

[Quick start guide here]

Documentation 📚

[Documentation link here]

Contributing 🤝

Contributions are welcome! Please feel free to submit a Pull Request.

License 📄

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

---

⭐️ If you find this project useful, please consider giving it a star!