Design and Evaluate a Retrieval-Augmented Generation Pipeline

Design of a Retrieval‑Augmented Generation Pipeline The pipeline answers natural‑language questions from a versioned, permission‑protected document collection. It explicitly separates: (1) indexing and chunking – how documents become searchable units; (2) retrieval with access control – how candidate evidence is gathered under latency and context‑size limits; (3) context assembly – how retrieved pieces are deduplicated, ordered, and fed to a large language model (LLM); (4)…