RAG (Retrieval-Augmented Generation)

RAG is a technique where the language model answers using documents retrieved in real time, rather than its memory alone. Relevant passages are searched, injected into the context, and the model generates an answer grounded in those sources.

RAG reduces hallucinations and lets the model answer over fresh or private data.