RAG involves taking the input from the user and searching for the relevant information through an externally connected database. Once the relevant information is retrieved, it is provided to the language model to generate its output based on that information. A normal RAG model involves the use of three main systems that include document store, retrieval system, and response generator. This technology enables AI-powered applications to work on external information sources without needing to train the model with new data each time.
