| name | LightRAG Graph-Based Retrieval-Augmented Generation Framework |
| slug | lightrag-graph-rag-framework |
| description | LightRAG is a Python-based retrieval-augmented generation framework that builds knowledge graphs from documents for more connected, contextual retrieval. Published at EMNLP 2025, it enables graph-powered RAG with support for multiple storage backends and LLM providers. |
| github_stars | 33160 |
| verification | security_reviewed |
| source | https://github.com/HKUDS/LightRAG |
| category | Data Extraction & Transformation |
| framework | Multi-Framework |
| tool_ecosystem | {"github_repo":"hkuds/lightrag","github_stars":33160} |
LightRAG Graph-Based Retrieval-Augmented Generation Framework
LightRAG is a Python-based retrieval-augmented generation framework that builds knowledge graphs from documents for more connected, contextual retrieval. Published at EMNLP 2025, it enables graph-powered RAG with support for multiple storage backends and LLM providers.
Installation
Use the upstream install or setup path that matches your environment:
- Note: You can also use pip if you prefer, but uv is recommended for better performance and more reliable dependency management.
- uv tool install "lightrag-hku[api]"
- git clone https://github.com/HKUDS/LightRAG.git
- make dev
Requirements and caveats from upstream:
-
- [2026.03]🎯[New Feature]: Introduced a setup wizard. Support for local deployment of embedding, reranking, and storage backends via Docker.
-
python -m venv .venv
Basic usage or getting-started notes:
Source
