LightRAG Hits 35K Stars — EMNLP 2025 Paper Delivers Simple, Fast RAG With Knowledge Graph Integration

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HKUDS/LightRAG has reached 35,472 GitHub stars as a lightweight retrieval-augmented generation framework that combines graph-based and vector-based retrieval in a single pipeline. The EMNLP 2025 paper demonstrates faster retrieval with better accuracy than heavier RAG frameworks by exploiting knowledge graph structure for context relevance. The Python library supports GPT-4, Gemini, and local models, making it a practical drop-in for developers building RAG applications without the complexity of full GraphRAG setups.