Ollama-Ebook-Summary

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ollama-ebook-summary is an Open Source research & education tool that creates comprehensive bulleted notes and summaries from books and long texts. It processes EPUB and PDF files by splitting them into manageable chunks for summarization.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is ollama-ebook-summary?

ollama-ebook-summary is an open-source AI tool designed for generating comprehensive bulleted notes and summaries from long texts, including ebooks in EPUB and PDF formats. It intelligently extracts chapters and sections, splitting them into approximately 2000-token chunks to optimize LLM reasoning performance. Unlike RAG systems, it applies the same summarization questions to every part of the document, ensuring thorough coverage. The tool is built with Python 3.11.9 and supports local LLMs like Ollama and HuggingFace models. It provides scripts for converting ebooks to chunked CSV or TXT files and generating summaries, with options for semi-manual processing for more control over chunking.

Best used for

Ideal for students and professors who need to quickly summarize academic papers, create detailed study notes from textbooks, and generate concise overviews of lengthy documents. Especially valuable for those who prefer to use local LLMs for privacy or performance reasons.

Common actions

summarize text

generate notes

process documents

extract information

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Capabilities

Key features

Bulleted notes generation
Long text summarization
EPUB/PDF processing
Text chunking
Local LLM support
Customizable prompts

Target Audience

studentprofessor

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What types of documents can ollama-ebook-summary process?

The tool primarily processes EPUB and PDF files, especially those with Table of Contents metadata. It can also work with text files where each line represents a separate text chunk, allowing for flexible input options.

What LLMs are compatible with ollama-ebook-summary?

ollama-ebook-summary is designed to work with local LLMs, specifically supporting models from Ollama and HuggingFace. Users can download pre-configured models like Mistral Instruct v0.2 Bulleted Notes and Mistral 7b 0.3 for title generation.

How does the tool handle long texts for summarization?

It splits documents into approximately 2000-token chunks. This chunking strategy is based on research suggesting optimal reasoning performance for LLMs within this token range, ensuring effective summarization of lengthy content.

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Academic Research Study Assistants Knowledge Management Course Creation Scientific Computing Language Learning

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