# 🚀 LightRAG: Specialized Production Fork

A production-ready fork of LightRAG featuring S3 storage integration, a modernized Web UI, and a robust API.

## 🔱 About This Fork This repository is a specialized fork of [LightRAG](https://github.com/HKUDS/LightRAG), designed to bridge the gap between research and production. While preserving the core "Simple and Fast" philosophy, we have added critical infrastructure components: - **☁️ S3 Storage Integration**: Native support for S3-compatible object storage (AWS, MinIO, Cloudflare R2) for scalable document and artifact management. - **🖥️ Modern Web UI**: A completely redesigned interface featuring: - **S3 Browser**: Integrated file management system. - **File Viewers**: Built-in PDF and text viewers. - **Enhanced Layout**: Resizable panes and improved UX. - **🔌 Robust API**: Expanded REST endpoints supporting multipart uploads, bulk operations, and advanced search parameters. - **🛡️ Code Quality**: Comprehensive type hinting (Pyright strict), Ruff formatting, and extensive test coverage for critical paths. --- ## 📖 Introduction to LightRAG **LightRAG** incorporates graph structures into text indexing and retrieval processes. This innovative framework employs a dual-level retrieval system that enhances comprehensive information retrieval from low-level entities to high-level broader topics.

Algorithm Flowchart

![LightRAG Indexing Flowchart](https://learnopencv.com/wp-content/uploads/2024/11/LightRAG-VectorDB-Json-KV-Store-Indexing-Flowchart-scaled.jpg) *Figure 1: LightRAG Indexing Flowchart ([Source](https://learnopencv.com/lightrag/))*

## ⚡ Quick Start ### 1. Installation This project uses [uv](https://docs.astral.sh/uv/) for fast and reliable package management. **Option A: Install from PyPI** ```bash uv pip install "lightrag-hku[api]" ``` **Option B: Install from Source (Recommended for this Fork)** ```bash git clone https://github.com/YourUsername/LightRAG.git cd LightRAG uv sync --extra api source .venv/bin/activate ``` ### 2. Running the Server (UI + API) The easiest way to experience the enhancements in this fork is via the LightRAG Server. 1. **Configure Environment**: ```bash cp env.example .env # Edit .env to add your API keys (OpenAI/Azure/etc.) and S3 credentials ``` 2. **Start the Server**: ```bash lightrag-server ``` 3. **Access the UI**: Open [http://localhost:9600](http://localhost:9600) to view the Knowledge Graph, upload files via the S3 browser, and perform queries. ### 3. Python API Example You can also use LightRAG directly in your Python code: ```python import os import asyncio from lightrag import LightRAG, QueryParam from lightrag.llm.openai import gpt_4o_mini_complete, openai_embed WORKING_DIR = "./rag_storage" if not os.path.exists(WORKING_DIR): os.mkdir(WORKING_DIR) async def main(): # Initialize LightRAG rag = LightRAG( working_dir=WORKING_DIR, embedding_func=openai_embed, llm_model_func=gpt_4o_mini_complete, ) await rag.initialize_storages() # Insert Document await rag.ainsert("LightRAG is a retrieval-augmented generation framework.") # Query print(await rag.aquery( "What is LightRAG?", param=QueryParam(mode="hybrid") )) if __name__ == "__main__": asyncio.run(main()) ``` ## 📦 Features & Architecture ### Storage Backends LightRAG supports multiple storage backends. This fork adds robust S3 support for document storage. | Type | Implementations | |------|-----------------| | **KV Storage** | JsonKVStorage, PGKVStorage, RedisKVStorage, MongoKVStorage | | **Vector Storage** | NanoVectorDB, PGVector, Milvus, Chroma, Qdrant, Faiss | | **Graph Storage** | NetworkX, Neo4J, AGE (PostgreSQL), Memgraph | | **Object Storage** | **S3Storage (New)**, LocalFileStorage | ### Specialized API Routes This fork exposes additional endpoints: - `POST /documents/upload`: Multipart file upload (supports PDF, TXT, MD). - `GET /storage/list`: List files in S3/Local storage. - `GET /storage/content`: Retrieve file content. ## 🛠️ Configuration See `env.example` for a complete list of configuration options. Key variables for this fork: ```ini # S3 Configuration (Optional) S3_ENDPOINT_URL=https://.r2.cloudflarestorage.com S3_ACCESS_KEY_ID= S3_SECRET_ACCESS_KEY= S3_BUCKET_NAME=lightrag-docs ``` ## 📚 Documentation - [API Documentation](./lightrag/api/README.md) - [Offline Deployment](./docs/OfflineDeployment.md) - [Docker Deployment](./docs/DockerDeployment.md) ## 🤝 Contribution Contributions are welcome! Please ensure you: 1. Install development dependencies: `uv sync --extra test` 2. Run tests before submitting: `pytest tests/` 3. Format code: `ruff format .` ## 📜 License This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details. ---

_{Fork maintained by clssck. Based on the excellent work by the HKUDS team.}