Documentation for DeepSeek-RAG-Chatbot Q&A How-to Guide
Using DeepSeek-RAG-Chatbot for document quizzing is very simple and consists of the following steps:
1. Uploading documents::
- After launching the app, find the "Upload Documents" sidebar on the left side of the Streamlit interface.
- Click the "Browse files" button to select local PDF, DOCX or TXT files.
- The system automatically splits the document into appropriately sized chunks of content
- Automatically generate vector embeddings and store them in the FAISS vector database
2. Formulation of questions::
- Type a question in the chat box, Chinese and English are supported
- Questions should be as specific and clear as possible, e.g., "What is the role of the GraphRAG mentioned in the documentation?"
- Avoid vague questions such as "Summarize," which may not yield the best answer.
3. Question-and-answer session::
- The system performs a hybrid search in the document collection (BM25 + FAISS)
- GraphRAG analyzes the entity relationships of retrieved content paragraphs
- Neural reordering technique for optimal ranking of results
- HyDE extends raw queries to cover more potential content
- DeepSeek R1 model generates final answers based on search results
4. Viewing the results::
- The answer is displayed progressively in the interface as a streaming output
- For complex questions, the system may provide relational answers based on knowledge graphs
- The original retrieved document passages can be checked to verify the accuracy of the responses
Tips: You can upload multiple files at the same time to build a more comprehensive knowledge base; for longer documents, the system may take a few minutes to complete the initial processing.
This answer comes from the articleDeepSeek-RAG-Chatbot: a locally running DeepSeek RAG chatbotThe
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