What is RAG (retrieval-augmented generation)?
RAG, or retrieval-augmented generation, is a method where the system first searches your own documents for relevant passages and then gives them to the model to write the answer. Answers stay grounded in your content, can cite their source and change when the documents change, without retraining a model.
Example
A staff assistant answers a leave question by quoting the current HR policy page and linking to it.
In one line
Retrieval-augmented generation: finding relevant passages in your own content and giving them to the model so answers are grounded and citable.
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