HKUDS / LightRAG
git clone https://github.com/HKUDS/LightRAG.git
v1.5.7 Β· 1mo ago
[EMNLP2025] LightRAG: Simple and Fast Retrieval-Augmented Generation
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LanguagePython
LicenseMIT
Created2024-10-02 (2y ago)
Last pushtoday
Watchers297
OwnerOrganization
GitHub topics
doclinggenaigptgraphragknowledge-graphlarge-language-modelsllmmineruragragasretrieval-augmented-generation
Links
- GitHub: github.com/HKUDS/LightRAG
- Homepage: https://arxiv.org/abs/2410.05779
- Releases Β· Issues Β· Hacker News mentions
README excerpt
# π LightRAG: Simple and Fast Retrieval-Augmented Generation --- ## π News - [2026.07]π―[New Feature]: Add **Smart Heading** recognition feature for word documents. - [2026.05]π―[New Feature]: **Merge RagAnything into LightRAG**π. Multimodal content parsing and extraction via **MinerU / Docling** services. - [2026.05]π―[New Feature]: Introducing four selectable text chunking strategies: `Fix`, `Recursive`, `Vector`, and `Paragraph`. - [2026.05]π―[New Feature]: **Role-specific LLM configuration** support, 4 distinct roles: EXTRACT, QUERY, KEYWORDS, and VLM, with independent LLM settings. - [2026.03]π―[New Feature]: Integrated **OpenSearch** as a unified storage backend, providing comprehensive support for all four LightRAG storage. - [2026.03]π―[New Feature]: Introduced a setup wizard. Support for local deployment of embedding, reranking, and storage backends via Docker. - [2025.11]π―[New Feature]: Integrated **RAGAS for Evaluation** and **Langfuse for Tracing**. Updated the API to return retrieved contexts alongside query results to support context precision metrics. - [2025.10]π―[Scalability Enhancement]: Eliminated processing bottlenecks to support **Large-Scale Datasets Efficiently**. - [2025.09]π―[New Feature] Enhances knowledge graph extraction accuracy for **Open-Sourced LLMs** such as Qwen3-30B-A3B. - [2025.08]π―[New Feature] **Reranker** is now supported, significantly boosting performance for mixed queries (set as default query mode). - [2025.08]π―[New Feature] Added **Document Deletion** with automatic KG regeneration to ensure optimal query performance. - [2025.06]π―[New Release] Our team has released RAG-Anything β an **All-in-One Multimodal RAG** system for seamless processing of text, images, tables, and equations. - [2025.06]π―[New Feature] LightRAG now supports comprehensive multimodal data handling through RAG-Anything integration, enabling seamless document parsing and RAG capabilities across diverse formats including PDFs, images, Office documents, tables, and formulas. Please refer to the new multimodal section for details. - [2025.03]π―[New Feature] LightRAG now supports citation functionality, enabling proper source attribution and enhanced document traceability. - [2025.02]π―[New Feature] You can now use MongoDB as an all-in-one storage solution for unified data management. - [2025.02]π―[New Release] Our team has released VideoRAG-a RAG system for understanding extremely long-context videos - [2025.01]π―[New Release] Our team has released MiniRAG making RAG simpler with small models. - [2025.01]π―You can now use PostgreSQL as an all-in-one storage solution for data management. - [2024.11]π―[New Resource] A comprehensive guide to LightRAG is now available on LearnOpenCV. β explore in-depth tutorials and best practices. Many thanks to the blog author for this excellent contribution! - [2024.11]π―[New Feature] Introducing the LightRAG WebUI β an interface that allows you to insert, query, and visualize LightRAG knowledge through an intuitive web-