Niez-Gharbi/PDF-RAG-with-Llama2-and-Gradio
Build your own Custom RAG Chatbot using Gradio, Langchain and Llama2
Implements document-grounded retrieval augmentation using ChromaDB for vector storage and semantic search, enabling the chatbot to cite specific PDF pages in responses. The architecture chains LangChain's conversational retrieval pipeline with Hugging Face embeddings for context-aware question answering. Supports configurable model selection via YAML, allowing swapping between different Llama2 variants and embedding providers without code changes.
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Language
Python
License
Apache-2.0
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Last pushed
Jan 26, 2024
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