This project extracts content from ebooks (epub, PDF) and splits them into ~2000 token chunks to maximize LLM reasoning performance on long texts. Rather than using RAG-style retrieval, it applies the same summarization prompts to every document segment, aggregating the results into comprehensive bulleted summaries. It integrates with Ollama for local LLM inference or HuggingFace models.