RAG (Retrieval-Augmented Generation)

Retrieval-Augmented Generation (RAG) is a technique where an AI system first retrieves relevant information from an external source and then uses that information to generate its response. Instead of relying solely on the model’s existing knowledge, it can work with documents, databases or other up-to-date information. RAG is commonly used to create more relevant and grounded AI applications.