Retrieval-Augmented Generation (RAG) is a technique that enhances LLM responses. Before generating an answer, the system searches for and retrieves up-to-date, relevant information from an external knowledge base (such as data from a lakehouse). This allows responses to be more accurate, reliable, and based on real-time data.
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