LLM-Implementation/private-rag-embeddinggemma
🔒 100% Private RAG Stack with EmbeddingGemma, SQLite-vec & Ollama - Zero Cost, Offline Capable
Implements semantic search through vector embeddings stored in SQLite with sub-millisecond query performance, then routes results to a local LLM via Ollama's API for context-aware generation. Uses EmbeddingGemma's configurable 256/768-dimension embeddings to balance speed and quality, with UV for dependency management and support for Jupyter notebooks in isolated virtual environments.
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Jupyter Notebook
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Last pushed
Sep 10, 2025
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