The project's Streamlit visualization simplifies the complex technical process into three steps: document uploading, automated processing, and natural language questioning. The left navigation bar of the interface integrates file management functions and supports batch uploading of documents in 10+ formats. The central chat area uses Markdown rendering technology to stream formatted answers in real time. Interaction design introduces contextual memory function and supports multiple rounds of conversation up to 8K tokens.
The system provides pre-set question templates and query suggestions for users who are not technical experts. The interface response is specially optimized to maintain operation feedback within 1.5 seconds under 4G network environment. The background monitoring panel can view the underlying information such as search paths and knowledge graph fragments to meet the debugging needs of advanced users. Tests show that non-technical people can master all core functions after 5 minutes of learning.
This answer comes from the articleDeepSeek-RAG-Chatbot: a locally running DeepSeek RAG chatbotThe
