The retrieval-augmented generation (RAG) architecture is a combination of the retrieval element and generative language models. Once a user formulates a query, the system retrieves information from a connected information source and provides this information to the generative model, which forms a response on the basis of the retrieved context. To summarize, the RAG definition can be presented as follows: the AI system looks for relevant information to give the answer to a question. The term ”RAG” is especially helpful for companies that need the integration of AI in their proprietary documents, guidelines, product information, and so on. The ability to change the information source makes RAG more flexible for businesses.
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