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Yiorgis Gozadinos 2025-06-22 13:10:06 +02:00
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# Haiku SQLite RAG # Haiku SQLite RAG
A SQLite-based Retrieval-Augmented Generation (RAG) system built for efficient document storage, chunking, and hybrid search capabilities. A Retrieval-Augmented Generation (RAG) library on SQLite.
## Features ## Features
- **Local SQLite**: No need to run additional servers - **Local SQLite**: No need to run additional servers
- **Support for various embedding providers**: You can use Ollama, VoyageAI, OpenAI or add your own - **Support for various embedding providers**: You can use Ollama, VoyageAI, OpenAI or add your own
- **Hybrid Search**: Vector search using `sqlite-vec` combined with full-text search `FTS5`, using Reciprocal Rank Fusion - **Hybrid Search**: Vector search using `sqlite-vec` combined with full-text search `FTS5`, using Reciprocal Rank Fusion
- **Multi-format Support**: Parse 40+ file formats including PDF, DOCX, HTML, Markdown, audio and more. Or add a url!
- **File monitoring** when run as a server automatically indexing your files - **File monitoring** when run as a server automatically indexing your files
- **Extended file format Support**: Parse 40+ file formats including PDF, DOCX, HTML, Markdown, audio and more. Or add a url!
- **MCP server** Exposes functionality as MCP tools. - **MCP server** Exposes functionality as MCP tools.
- **CLI commands** Access all functionality from your terminal
- **Python client** Call `haiku.rag` from your own python applications. - **Python client** Call `haiku.rag` from your own python applications.
## Installation ## Installation