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FacetiousKnave · 06-02-2026, 08:59 AM

Hey everyone,

Like a many of you, I have a massive Calibre library (7,000+ DeDRM EPUBs).

Although I read a lot, sometimes I struggle to know what to read next, or what books address specific topics, or how those topics are addressed, how I can connect a current read to another one to follow a topic-related path.

So, in other words, I wanted a way to actually interact with that hoard of knowledge using AI—asking questions across hundreds of books at once, finding specific philosophical arguments, or cross-referencing authors—but I absolutely refused to upload my personal library to OpenAI or pay for a cloud subscription.

So, I built Ollama Pi Chat. It’s an open-source, local-first desktop app that acts as a secure wrapper for Ollama, but with a heavily engineered offline RAG (Retrieval-Augmented Generation) engine built specifically for massive EPUB libraries.

I'm going to try to explain how it works:

Point it at your Calibre Folder: You don’t need to move or convert your books. Just point the app’s indexer at your Calibre Library directory, and it will safely parse the raw text from your EPUBs. The app does not edit or touch your ebooks in any way, it only reads them.
Ultra-Compact Database (No Bloat): Most vector databases explode in size if you feed them thousands of books. I engineered this to use Matryoshka semantic compression (256-dimension vectors) and SQLite external-content tables. The result? You can index the mathematical meaning and text of 7,000+ books into a single database that is less than 10 GB.
100% Local & Private: It runs entirely on your hardware using Ollama and local embedding models. No internet required, no API keys, and your data never leaves your machine.
Bulletproof Indexing for “Omnibus” Books: If you have massive “Complete Works” EPUBs that usually crash standard parsers, this handles them smoothly using in-memory ZIP streams. Plus, the indexing job is 100% resumable. If you close your laptop halfway through indexing your library, it picks up exactly where it left off.

If you want to give it a try, the repository is here: https://github.com/DuckTapeKiller/ollama-pi-chat

Please note that this app only works on both Intel / Arm64 MacBooks.

06-02-2026, 08:59 AM	#1
FacetiousKnave Unconscionable Posts: 91 Karma: 25000 Join Date: Sep 2022 Location: Helsinki Device: Kindle	Talk to your Calibre Library Hey everyone, Like a many of you, I have a massive Calibre library (7,000+ DeDRM EPUBs). Although I read a lot, sometimes I struggle to know what to read next, or what books address specific topics, or how those topics are addressed, how I can connect a current read to another one to follow a topic-related path. So, in other words, I wanted a way to actually interact with that hoard of knowledge using AI—asking questions across hundreds of books at once, finding specific philosophical arguments, or cross-referencing authors—but I absolutely refused to upload my personal library to OpenAI or pay for a cloud subscription. So, I built Ollama Pi Chat. It’s an open-source, local-first desktop app that acts as a secure wrapper for Ollama, but with a heavily engineered offline RAG (Retrieval-Augmented Generation) engine built specifically for massive EPUB libraries. I'm going to try to explain how it works: Point it at your Calibre Folder: You don’t need to move or convert your books. Just point the app’s indexer at your Calibre Library directory, and it will safely parse the raw text from your EPUBs. The app does not edit or touch your ebooks in any way, it only reads them. Ultra-Compact Database (No Bloat): Most vector databases explode in size if you feed them thousands of books. I engineered this to use Matryoshka semantic compression (256-dimension vectors) and SQLite external-content tables. The result? You can index the mathematical meaning and text of 7,000+ books into a single database that is less than 10 GB. 100% Local & Private: It runs entirely on your hardware using Ollama and local embedding models. No internet required, no API keys, and your data never leaves your machine. Bulletproof Indexing for “Omnibus” Books: If you have massive “Complete Works” EPUBs that usually crash standard parsers, this handles them smoothly using in-memory ZIP streams. Plus, the indexing job is 100% resumable. If you close your laptop halfway through indexing your library, it picks up exactly where it left off. If you want to give it a try, the repository is here: https://github.com/DuckTapeKiller/ollama-pi-chat Please note that this app only works on both Intel / Arm64 MacBooks.