LLM-Implementation/private-rag-embeddinggemma

🔒 100% Private RAG Stack with EmbeddingGemma, SQLite-vec & Ollama - Zero Cost, Offline Capable

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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.

No commits in the last 6 months.

Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 5 / 25
Maturity 9 / 25
Community 17 / 25

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11

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9

Language

Jupyter Notebook

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Last pushed

Sep 10, 2025

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