Retrieval-augmented generation - Wikipedia

Retrieval-augmented generation (RAG) is a technique that enables large language models (LLMs) to retrieve and incorporate new information.[1] With RAG, LLMs do not respond to user queries until they refer to a specified set of documents. These documents supplement information from the LLM's pre-existing training data.[2] This allows LLMs to use domain-specific and/or updated information that is no