RAG

RAG-TA: RAG-based Intelligent Teaching Assistant System The RAG Intelligent Teaching Assistant System is an intelligent teaching assistance platform based on Multimodal Retrieval-Augmented Generation (Multimodal RAG), specifically designed for educational scenarios. The system integrates the following core functions: 🤖 Intelligent Question Answering System Multimodal Understanding: Supports complex question answering with text and images, capable of understanding charts, formulas, and image content in course materials. Contextual Retrieval: Precise semantic retrieval based on the ChromaDB vector database. Hybrid Retrieval: Combines dense vector retrieval and sparse retrieval (BM25) to improve retrieval accuracy. Source Tracing: Automatically annotates the source file and page number of the answer, ensuring information traceability. 📚 Knowledge Base Management Multi-format Support: Supports various formats including PDF, PPTX, DOCX, TXT, MD, and images. Intelligent Indexing: Automatically extracts text and image content to build a multimodal vector index. Incremental Updates: Intelligently detects file changes and updates only the changed parts, improving efficiency. Folder Management: Supports hierarchical directory structure for easy organization of course materials. 💬 Conversation Management History: Complete conversation history saving and management. Multiple Answer Options: Supports multiple answer versions for the same question, allowing users to switch between them. Folder Classification: Supports conversation folder management for easy course classification. Thinking Mode: Visualizes the AI reasoning process to help understand the answer logic. 🖼️ Multimodal Interaction Image Understanding: Automatically extracts and describes image content in PDFs/PPTXs. Real-time Upload: Supports users uploading images and documents for instant question answering. Visual Question Answering: Provides comprehensive answers combining image content and text knowledge.

Dec 12, 2025