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RAG for your documents

RAG for your documents

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    • A
      license
      A
      quality
      D
      maintenance
      Enables searching and retrieving documents from a local folder to ground LLM answers in your files.
      2
      MIT
    • F
      license
      Not graded
      quality
      D
      maintenance
      Enables retrieval-augmented generation by allowing LLMs to search documents in a local folder using vector similarity, supporting multiple file formats.
      -
    • A
      license
      A
      quality
      C
      maintenance
      Local offline semantic search over documents (txt, md, pdf, docx, pptx, csv). Indexes folders into a LanceDB vector database with multilingual embeddings and supports hybrid vector + keyword search via Reciprocal Rank Fusion. No API keys, no cloud, no Docker required.
      4
      30
      AGPL 3.0
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to run semantic search over a local folder of text files, returning the best-matching passages ranked by cosine similarity, each with its source filename and score. Runs locally with no API keys, external services, or vector database.
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables assistants such as Claude Desktop to call document search over a folder of markdown as a tool, returning grounded answers with citations or measured refusals when the evidence is insufficient.
      MIT