curiousily/ragbase
Completely local RAG. Chat with your PDF documents (with open LLM) and UI to that uses LangChain, Streamlit, Ollama (Llama 3.1), Qdrant and advanced methods like reranking and semantic chunking.
The ingestor pipeline combines semantic and character-based chunking strategies for flexible document decomposition, while the retriever implements a multi-stage filtering approach using reranking and LLM-based chain filters before response generation. FastEmbed provides efficient local embedding generation, and the system supports swapping between Ollama-hosted models and Groq API inference without architectural changes. Built on LangChain abstractions, it integrates PDFium for robust PDF text extraction and Qdrant for vector storage, enabling completely offline operation or optional cloud inference.
122 stars. No commits in the last 6 months.
Stars
122
Forks
43
Language
Python
License
MIT
Category
Last pushed
Jul 26, 2024
Commits (30d)
0
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