What is RAG (Retrieval-Augmented Generation)?

Retrieval-Augmented Generation (RAG) is a technique that helps language models generate higher-quality outputs by allowing them to look up external, up-to-date information first. Before generating a response, the model retrieves relevant facts from a specific knowledge source, like a company's internal documents or the live internet. This retrieved information is then used to create a more accurate and detailed answer, reducing the chances of the model providing incorrect or outdated information.