RAG (retrieval-augmented generation)

Retrieval-augmented generation (RAG) is a pattern where a system first searches a collection of documents for passages relevant to a question, then gives those passages to a language model to write the answer. It lets a model answer from private, current documents it was never trained on, and makes it possible to cite sources.