You're building a system where a language model needs to answer questions using a specific document collection instead of relying only on pretraining knowledge. You are considering Retrieval-Augmented Generation to ground answers in retrieved source material.
What is Retrieval-Augmented Generation (RAG), and when would you use it?
Understanding of Retrieval-Augmented GenerationHow retrieval improves grounded answeringWhen vector search is usefulHow RAG reduces hallucinationHow to judge answer quality in an LLM system