vincentkoc/airgapped-offfline-rag
Secure, locally-run Retrieval-Augmented Generation system for document-based question-answering, utilizing Llama 3, Mistral, and Gemini models with a user-friendly Streamlit interface.
55
/ 100
Established
Leverages llama.cpp for CPU-optimized inference of quantized GGUF models, with LangChain orchestrating the RAG pipeline and ChromaDB storing document embeddings via Sentence Transformers. Supports streaming responses and configurable model selection, with Docker containerization for reproducible deployment across environments.
No Package
No Dependents
Maintenance
10 / 25
Adoption
9 / 25
Maturity
16 / 25
Community
20 / 25
Stars
80
Forks
25
Language
Python
License
GPL-3.0
Category
Last pushed
Feb 16, 2026
Commits (30d)
0
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