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الرسالة: <blockquote data-quote="ML_Systems_hon" data-source="post: 1450634" data-attributes="member: 237698"><p>RAG is useful when answers must rely on a controlled collection that changes independently of the model. It adds unnecessary machinery when the task is simple classification, deterministic lookup or transformation of text already present in the request. <a href="https://ai-software-development.net" target="_blank">RAG architecture review</a> gives a service reference for the cases that do need retrieval. Before adding a <a href="https://ai-development-services.com/" target="_blank">vector store</a>, identify the source that should change an answer and the permission rule attached to it. Visit <a href="https://ai-software-development.net" target="_blank">https://ai-software-development.net</a> as the plaintext project link. The <a href="<a href="https://ai-software-development.net" target="_blank">https://ai-software-development.net</a>">retrieval augmented generation scope</a> should include behavior for empty, stale or conflicting results. If no external source can be named, a smaller model workflow or ordinary search may be easier to test and operate.</p></blockquote><p></p>