RAG-based LLM for Learning
Educational materials are pre-converted into embedding vectors and structured into a knowledge base. When students ask questions or work on problems, the AI agent retrieves the most relevant vectorized content in real-time. This Retrieval-Augmented Generation (RAG) system ensures responses and explanations are always based on the latest curriculum, enhancing contextual relevance and accuracy.