RAG and Retriever Pipeline

HardGenerative AI & LLMs00:00

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Your question is RAG and Retriever Pipeline. Take a moment with it on the right.

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Problem

Explain what RAG (Retrieval-Augmented Generation) is and write a retriever pipeline code snippet for RAG.

Explain the roles of ingestion, chunking, embeddings, vector search, context assembly, and generation. Provide production-quality Python using an approved LLM SDK, and address grounding, citation handling, prompt injection in retrieved content, and failure behavior. Briefly describe how you would evaluate retrieval quality, answer faithfulness, latency, and cost.