An AI framework that combines the strengths of information retrieval systems with generative large language models (LLMs). It works by retrieving relevant information from external sources (like databases or documents) and feeding it into the LLM to generate more accurate, up-to-date, and contextually relevant responses. Essentially, RAG helps LLMs access and utilize information beyond their original training data.