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Finish the document-agent path: split your library, retrieve the closest passages for a question, then generate an answer grounded in those passages.
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Retrieval Augmented Generation
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Retrieval Augmented Generation
Contract
- Put your API key in the practice file (fine for local learning)
- Create an authenticated client
- Keep a small library of passages (already split)
- Embed passages + question; pick the top matches by similarity
- Call the chat model with those passages + the question; print both
rag_demo.py
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Example console
Sample run — exact text can vary
Question: How do we reset a contractor's laptop before they leave? Retrieved top 2 passages: score=0.8124 Wipe a loaner computer before return: sign out of accounts, erase the disk with WipePro, then tag the device as ready. score=0.4011 Contractors must return badges at the lobby. Lost badges are reported to Security the same day. Generated answer: Sign out of accounts, erase the disk with WipePro, then tag the device as ready.