AI Tutor - RAG system
Last updated
Last updated
Our Retrieval-Augmented Generation (RAG) system is a robust framework designed to enhance the accessibility and usability of learning content. The system operates through three interconnected processes.
First, during the ingestion phase, the learning content is processed into structured text chunks, which are then stored in an OpenSearch index to enable efficient retrieval.
Next, in the retrieval phase, the system leverages the capabilities of OpenSearch to identify and retrieve the most relevant text chunks based on user queries, ensuring accuracy and relevance.
Finally, the answer generation phase utilizes a Large Language Model (LLM) to synthesize coherent and contextually appropriate responses, drawing from the retrieved content. This integrated approach ensures that users receive precise and informative answers tailored to their needs, making the system a powerful tool for knowledge exploration and learning.