RAG-DeepSeek

Public

Efficiently search and retrieve information from PDF documents using a Retrieval-Augmented Generation (RAG) approach. This project leverages DeepSeek-R1 (1.5B) for advanced language understanding, FAISS for high-speed vector search, and Hugging Face’s ecosystem for enhanced NLP capabilities. With an intuitive Streamlit interface and Ollama for mode

deepseek-r1 faiss-cpu faiss-vector-database huggingface langchain ollama rag retrival-augmented-generation streamlit

Creat：2025-01-31T22:16:58

Update：2025-02-06T03:26:38

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