A Production RAG Pipeline for PDFs: Relational Parsing, TOC Retrieval, Typed Answers

A production-ready RAG pipeline requires upgrading four core components beyond a baseline implementation. Document parsing is enhanced to create a relational set of data including a table of contents, page metadata, and line-by-line text, instead of a flat file. Question parsing is improved to handle user errors like typos and to structure the query into a formal brief. Retrieval leverages the document's structure, like the table of contents, for more precise context gathering, and generation produces typed, citable answers with an audit trail rather than just a raw string.