Quote:
Originally Posted by SASSBS
I would love a way to have a model read my books and then answer questions.
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This is actually possible right now. I built an open-source tool called ARCHILLES that does exactly this: it indexes your Calibre library (and/or Zotero, Obsidian, a Folder) — full text, metadata, annotations — and makes everything semantically searchable.
ARCHILLES uses RAG (Retrieval-Augmented Generation), meaning the AI doesn't hallucinate from its general training data but retrieves actual passages from your books before answering. You ask a question, it finds the relevant paragraphs across your collection, and responds with proper citations — author, title, page number. It connects to the AI model of your choice via MCP (Model Context Protocol), so it works with Claude, ChatGPT, or local models.
Everything runs on your machine — no cloud, no data leaves your hard drive. It's MIT-licensed and on GitHub: github.com/kasssandr/archilles. Still early days, but the core is functional. Worth noting that this is a different approach from calibre's built-in Discuss feature, which sends individual books to an LLM for conversation. ARCHILLES works across your entire library at once, so you can ask questions that span multiple books and get cited answers from whichever sources are relevant.