Ship: The Full Chat-With-PDF Pipeline

shipping the RAG app

Part of: Chat With Your PDF

Every piece is built. Now wire chunking, embedding, retrieval, dedup, the similarity floor, and the grounded prompt into one pipeline someone else could run from scratch. Finish this lesson and Chat With Your PDF lands in your Portfolio . The full pipeline, end to end Nothing here is new. It's every earlier lesson's function called in the order you built them: ingest once per document, then ask once per question. The questions run cheap because the expensive chunking and embedding already happened. Wrap it in a small CLI One command, python chat pdf.py report.pdf, then a loop of questions. Ingest runs once. Every question after that reuses the same chunks and vectors. What "shipped" means here The same three checks from the playbook. It runs from a clean start with one command. It survives an empty document or a blank question without crashing (lesson 7's guards). And it refuses honestly instead of hallucinating when the document doesn't cover the question (lesson 6). Hit those three and you have a real deliverable. Into your Portfolio Finishing this lesson records Chat With Your PDF in your Portfolio tab. Keep one real document and a question-and-answer pair around as proof it ret

Challenge: Route the Question