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Multimodal Information Extractors · Awesome GitHub Repositories

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Awesome GitHub RepositoriesMultimodal Information Extractors

Engines designed to parse and structure information from mixed-media document formats.

Distinguishing note: Focuses on the parsing engine aspect of multimodal extraction, distinct from the broader extraction frameworks.

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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 processing engine that parses both text and visual data from diverse document formats to build comprehensive searchable knowledge bases.

    Pythongenaigptgpt-4
    28,455View on GitHub↗