Retrieval-augmented generation (RAG)

A technique where relevant documents are fetched and added to the model's input so its answer can draw on them.

RAG systems search a knowledge base (often with embeddings), place the best matches in the prompt, and ask the model to answer from them. It helps keep answers current and lets them cite sources.