RAG (Retrieval-Augmented Generation)
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An architecture where an LLM answers using documents retrieved from a corpus, reducing fabrication by grounding responses in sources.
The pipeline: ingest → chunk (+ metadata/ACL) → retrieve (hybrid search) → generate with citations. The parts that decide quality are retrieval and evaluation, not the model choice.