rag-colls 0.2.0.10

rag-colls - Implement recent advanced RAG techniques

rag-colls

rag-colls a.k.a RAG Collections.

Simple and easy to use, production-ready advanced RAG techniques.

📑 Table of Contents

• 📖 Documentation
• 🔧 Installation
• 📚 Notebooks
• 🚀 Upcoming
• 🎉 Quickstart
• 💻 Develop Guidance
• ✨ Contributors
• ©️ License

📖 Documentation

Please visit documentation to get latest update.

🔧 Installation

• You can easily install it from pypi:

pip install -U rag-colls

• Docker - 🐳:

# Clone the repository
git clone https://github.com/hienhayho/rag-colls.git
cd rag-colls/

# Choose python version and setup OPENAI_API_KEY
export PYTHON_VERSION="3.10"
export OPENAI_API_KEY="your-openai-api-key-here"

# Docker build
DOCKER_BUILDKIT=1 docker build \
                -f docker/Dockerfile \
                --build-arg OPENAI_API_KEY="$OPENAI_API_KEY" \
                --build-arg PYTHON_VERSION="$PYTHON_VERSION" \
                -t rag-colls:$PYTHON_VERSION .

docker run -it --name rag_colls --shm-size=2G rag-colls:$PYTHON_VERSION

📚 Notebooks

We have provided some notebooks for example usage.

RAG Tech	Code	Guide	Tech Description
BasicRAG	BasicRAG	Colab	Integrate with Chromadb
ContextualRAG	ContextualRAG	Colab	Integrate with Chromadb and BM25s version

🚀 Upcoming

We are currently working on these projects and will be updated soon.

RAG Tech	Link
Graph-RAG	Blog, Paper
RAFT	Blog, Paper
RAG-RL	Paper

🎉 Quickstart

Please refer to example for more information.

💻 Develop Guidance

Please refer to DEVELOP.md for more information.

✨ Contributors

Ho Trong Hien

congtuong

Bao Tran Gia

Phan Thanh Dat

💎 Acknowledgement

This project is supported by UIT AIClub.

©️ LICENSE

rag-colls is under MIT LICENSE.