Definition

RAG

Retrieval-Augmented Generation gives a model your data at inference time instead of retraining it. Documents are chunked, converted to embeddings, and stored in a vector database; a user's question is embedded the same way, the nearest chunks are retrieved, and they are fed to the model alongside the question. The book's summary: it is a search engine wired into a language model, and it grounds answers in real documents.