📚 RAG (Retrieval-Augmented Generation)
TL;DR
• Fetch relevant documents first, then let the model answer from them
• Fixes: stale knowledge, hallucination on private data, citation needs
• Modern stack: hybrid search (vector + keyword) + reranking
The core idea
RAG = retrieve relevant chunks from your knowledge base (vector and/or keyword search), insert them into the prompt, instruct the model to answer only from them with citations. It grounds answers in your data and stays current without retraining.
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