RAG

Retrieval-Augmented Generation (RAG) is a technique that connects a large language model (LLM) to an external knowledge source, so it can retrieve relevant information before generating an answer. This solves the two biggest limitations of standalone LLMs: outdated knowledge and hallucination. In Python, RAG is typically built using an embedding model, a vector database, and