DeepSeek-RAG-Chatbot is a GitHub open source project created by developer SaiAkhil066, whose core model is based on DeepSeek R1. The project innovatively integrates the Retrieval Augmented Generation (RAG) technological framework, and realizes the intelligent processing of documents in privacy-sensitive scenarios through a localized deployment scheme. The technical architecture utilizes a hybrid retrieval system (BM25+FAISS), a neural reordering module, and a knowledge graph (GraphRAG) to ensure the accuracy and contextual relevance of the information extracted from uploaded documents. Typical application scenarios include corporate confidential document analysis, personal knowledge base management, and other environments that require data offline.
The project provides two deployment methods, Docker containerization and Streamlit interactive interface, and supports multi-format document processing such as PDF/DOCX/TXT. The technology stack includes a local model runtime environment supported by Ollama, and the DeepSeek R1 model provides 1.5B/7B/32B parameter scale options. The system automatically performs chunking, vector embedding generation and FAISS index construction when documents are uploaded, providing a structured data base for subsequent intelligent Q&A.
This answer comes from the articleDeepSeek-RAG-Chatbot: a locally running DeepSeek RAG chatbotThe
