The problem: Traditional e-readers are passive. When you encounter something unclear, you have to context-switch to search for it. Your highlights and notes remain isolated, and you can't easily connect ideas across different books.
My solution: BookWith embeds an AI that maintains full context of what you're reading. It features:
- Context-aware AI chat: Ask questions about the current page/chapter and get instant answers
- AI podcast generation: Automatically converts book content into conversational podcasts using Google Cloud TTS
- Multi-layer memory system: Short-term (last 5 conversations), mid-term (summarized every 20), and long-term (vector search) memory that maintains continuity across reading sessions
- Smart annotations: 5-color highlighting system that AI can reference and analyze
Technical stack: Built as a fork of Flow (epub reader), with added LLM integration and vector database for semantic search. Supports multiple LLMs and languages (EN/JA/ZH).
Finnucane•1h ago
That seems like a maybe a wee bit of an overstatement of possibilities.
takigon•1h ago
What I meant from a technical perspective is that the system uses a Retrieval-Augmented Generation (RAG) approach. It has the entire book's content available in a vector database, and when you ask a question, it performs a semantic search to pull the most relevant passages in real-time to use as context for the LLM's answer.
So, from a user's perspective, the experience is designed to feel like you're conversing with an expert who can instantly recall any part of the book. I should have used more precise language. Thanks for keeping me honest!