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Graph-Based Retrieval Frameworks · Awesome GitHub Repositories

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Awesome GitHub RepositoriesGraph-Based Retrieval Frameworks

Architectures that utilize knowledge graphs to enhance context accuracy for language model generation.

Distinguishing note: Specifically targets graph-structured retrieval for LLM context, distinct from general database or search indexing.

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  • HKUDS/LightRAG

    HKUDS/LightRAG

    28,455View on GitHub↗

    LightRAG is a graph-based retrieval framework designed to build retrieval-augmented generation pipelines. It structures unstructured text into knowledge graphs, enabling multi-hop reasoning and complex query synthesis across large document collections. By integrating dense vector embeddings with structured knowledge graphs, the system facilitates both similarity-based and relationship-aware information retrieval. The framework distinguishes itself through a dual-level retrieval strategy that combines low-level keyword matching with high-level semantic graph traversal to capture both specific

    A structured data retrieval architecture that organizes information into knowledge graphs to improve context accuracy during language model generation.

    Pythongenaigptgpt-4
    28,455View on GitHub↗