Retrieval Augmented Generation (RAG)
A technique that combines document retrieval with LLM generation to answer questions using external knowledge.
In more detail
RAG retrieves relevant documents from a knowledge base, then feeds them to an LLM for answer generation. This enables LLMs to access up-to-date information beyond training data and cite sources. Used for Q&A systems, customer support, and enterprise applications.
Examples
- Customer support chatbots with company docs
- Medical Q&A with research papers
- Legal document search and analysis
- News summarization with source retrieval
Related terms
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