Retrieval augmented generation (RAG)

Retrieval Augmented Generation (RAG) is a technique in generative AI that combines the retrieval of relevant information from a large dataset with a generative model to produce more accurate and contextually relevant outputs. It first retrieves documents or data that are relevant to a given query and then uses this information to guide the generation process in creating responses or content.