Retrieval-Augmented Generation (RAG)

Retrieval-Augmented Generation (RAG) is a technique that combines information retrieval with generative modeling. In RAG, a model first retrieves relevant information from a knowledge base or documents, and then uses this information to generate more accurate and contextually relevant responses. It typically involves integrating a retriever component (for fetching relevant data) and a generator component (for producing text based on the retrieved data).