173 lines
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5.8 KiB
Markdown
173 lines
No EOL
5.8 KiB
Markdown
<div align="center">
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<div style="margin: 20px 0;">
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<img src="./assets/logo.png" width="120" height="120" alt="LightRAG Logo" style="border-radius: 20px; box-shadow: 0 8px 32px rgba(0, 217, 255, 0.3);">
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</div>
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# 🚀 LightRAG: Specialized Production Fork
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<div align="center">
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<img src="https://img.shields.io/badge/Release-Specialized%20Fork-00d9ff?style=for-the-badge&logo=git&logoColor=white&labelColor=1a1a2e">
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<a href="https://github.com/HKUDS/LightRAG"><img src="https://img.shields.io/badge/Upstream-HKUDS%2FLightRAG-7289da?style=for-the-badge&logo=github&logoColor=white&labelColor=1a1a2e"></a>
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</div>
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<div align="center">
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<div style="width: 100%; height: 2px; margin: 20px 0; background: linear-gradient(90deg, transparent, #00d9ff, transparent);"></div>
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</div>
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<p align="center">
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<b>A production-ready fork of LightRAG featuring S3 storage integration, a modernized Web UI, and a robust API.</b>
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</p>
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</div>
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## 🔱 About This Fork
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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:
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- **☁️ S3 Storage Integration**: Native support for S3-compatible object storage (AWS, MinIO, Cloudflare R2) for scalable document and artifact management.
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- **🖥️ Modern Web UI**: A completely redesigned interface featuring:
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- **S3 Browser**: Integrated file management system.
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- **File Viewers**: Built-in PDF and text viewers.
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- **Enhanced Layout**: Resizable panes and improved UX.
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- **🔌 Robust API**: Expanded REST endpoints supporting multipart uploads, bulk operations, and advanced search parameters.
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- **🛡️ Code Quality**: Comprehensive type hinting (Pyright strict), Ruff formatting, and extensive test coverage for critical paths.
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---
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## 📖 Introduction to LightRAG
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**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.
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<details>
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<summary><b>Algorithm Flowchart</b></summary>
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*Figure 1: LightRAG Indexing Flowchart ([Source](https://learnopencv.com/lightrag/))*
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</details>
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## ⚡ Quick Start
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### 1. Installation
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This project uses [uv](https://docs.astral.sh/uv/) for fast and reliable package management.
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**Option A: Install from PyPI**
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```bash
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uv pip install "lightrag-hku[api]"
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```
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**Option B: Install from Source (Recommended for this Fork)**
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```bash
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git clone https://github.com/YourUsername/LightRAG.git
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cd LightRAG
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uv sync --extra api
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source .venv/bin/activate
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```
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### 2. Running the Server (UI + API)
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The easiest way to experience the enhancements in this fork is via the LightRAG Server.
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1. **Configure Environment**:
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```bash
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cp env.example .env
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# Edit .env to add your API keys (OpenAI/Azure/etc.) and S3 credentials
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```
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2. **Start the Server**:
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```bash
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lightrag-server
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```
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3. **Access the UI**:
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Open [http://localhost:9600](http://localhost:9600) to view the Knowledge Graph, upload files via the S3 browser, and perform queries.
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### 3. Python API Example
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You can also use LightRAG directly in your Python code:
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```python
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import os
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import asyncio
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from lightrag import LightRAG, QueryParam
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from lightrag.llm.openai import gpt_4o_mini_complete, openai_embed
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WORKING_DIR = "./rag_storage"
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if not os.path.exists(WORKING_DIR):
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os.mkdir(WORKING_DIR)
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async def main():
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# Initialize LightRAG
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rag = LightRAG(
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working_dir=WORKING_DIR,
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embedding_func=openai_embed,
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llm_model_func=gpt_4o_mini_complete,
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)
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await rag.initialize_storages()
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# Insert Document
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await rag.ainsert("LightRAG is a retrieval-augmented generation framework.")
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# Query
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print(await rag.aquery(
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"What is LightRAG?",
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param=QueryParam(mode="hybrid")
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))
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if __name__ == "__main__":
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asyncio.run(main())
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```
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## 📦 Features & Architecture
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### Storage Backends
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LightRAG supports multiple storage backends. This fork adds robust S3 support for document storage.
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| Type | Implementations |
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|------|-----------------|
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| **KV Storage** | JsonKVStorage, PGKVStorage, RedisKVStorage, MongoKVStorage |
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| **Vector Storage** | NanoVectorDB, PGVector, Milvus, Chroma, Qdrant, Faiss |
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| **Graph Storage** | NetworkX, Neo4J, AGE (PostgreSQL), Memgraph |
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| **Object Storage** | **S3Storage (New)**, LocalFileStorage |
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### Specialized API Routes
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This fork exposes additional endpoints:
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- `POST /documents/upload`: Multipart file upload (supports PDF, TXT, MD).
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- `GET /storage/list`: List files in S3/Local storage.
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- `GET /storage/content`: Retrieve file content.
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## 🛠️ Configuration
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See `env.example` for a complete list of configuration options. Key variables for this fork:
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```ini
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# S3 Configuration (Optional)
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S3_ENDPOINT_URL=https://<accountid>.r2.cloudflarestorage.com
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S3_ACCESS_KEY_ID=<your_access_key>
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S3_SECRET_ACCESS_KEY=<your_secret_key>
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S3_BUCKET_NAME=lightrag-docs
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```
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## 📚 Documentation
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- [API Documentation](./lightrag/api/README.md)
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- [Offline Deployment](./docs/OfflineDeployment.md)
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- [Docker Deployment](./docs/DockerDeployment.md)
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## 🤝 Contribution
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Contributions are welcome! Please ensure you:
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1. Install development dependencies: `uv sync --extra test`
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2. Run tests before submitting: `pytest tests/`
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3. Format code: `ruff format .`
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## 📜 License
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This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
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---
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<div align="center">
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<sub>Fork maintained by <a href="https://github.com/clssck">clssck</a>. Based on the excellent work by the <a href="https://github.com/HKUDS">HKUDS</a> team.</sub>
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</div> |