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Generic synopsis: A beginner’s guide to building a Retrieval-Augmented Generation (RAG) pipeline. Explains embeddings, vector databases, and retrievers; shows how to ingest and chunk data, index it, and connect a retriever to an LLM for grounded answers. Walks through code, evaluation and latency tips, and deployment/guardrail basics.