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#python
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.
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v1.0.0
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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: 📦 Offline Deployment : For offline or air-gapped environments, see the Offline Deployment Guide for instructions on pre-installing all dependencies and cache files. The LightRAG Server is designed to provide Web UI and API support. The Web UI facilitates document indexing, knowledge graph exploration, and a simple RAG query interface. LightRAG Server also provide an Ollama compat... Install from PyPI Source: https://github.com/HKUDS/LightRAG Extracted from upstream docs: https://raw.githubusercontent.com/HKUDS/LightRAG/HEAD/README.md Source Agent Skill Exchange
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| Field | Description |
|---|---|
| format | Format tag (skill/v1) |
| skill_id | Unique skill ID |
| name | Skill name |
| version | Version |
| description | Description |
| category | Categories (array) |
| trigger_words | Trigger words |
| tags | Tags |
| source | Source |
| source_url | Source URL (this page) |
| exported_at | Exported at (set per download) |
| system_prompt | System prompt body |
| model_config | Model config: provider / model / temperature / max_tokens / top_p |
| examples | Examples |
| install_guide | Import guide for Coze / Dify / Claude / custom frameworks |
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