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InsightSummarizer

AI-driven tool that generates concise and coherent summaries of books, extracting key insights to help you grasp the essence quickly and efficiently.

Install / Use

/learn @zjnbwxq/InsightSummarizer
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

📚 InsightSummarizer: Unlock Core Insights Effortlessly

InsightSummarizer is an AI-powered text summarization tool that condenses lengthy documents into concise, easy-to-digest summaries. Whether you're dealing with books, articles, or reports, InsightSummarizer helps you grasp the essential points quickly, saving you time and enhancing understanding.

Features

  • Chapter-wise Summarization: Generate summaries for individual chapters, focusing on specific sections of interest.
  • Entire Document Summarization: Summarize the whole content when documents lack clear divisions.
  • Advanced Natural Language Processing (NLP): Powered by cutting-edge NLP techniques to intelligently extract the most relevant information.
  • User-Friendly Interface: An intuitive interface makes the summarization process seamless for users of all technical backgrounds.
  • Email Notifications: Receive summarized content directly in your inbox for convenience.

How It Works

InsightSummarizer leverages the T5-small pretrained model from HuggingFace Transformers to generate accurate and coherent summaries. The process involves:

  1. Text Segmentation: The document is divided into chunks, either by chapters or as a whole.
  2. Tokenization: Chunks are tokenized using T5Tokenizer for compatibility with the T5 model.
  3. Summary Generation: The tokenized text is processed by the T5ForConditionalGeneration model to produce summary token IDs.
  4. Decoding: Summary tokens are decoded back into human-readable text using the T5Tokenizer's decode() function.

Getting Started

Prerequisites

  • Python 3.x
  • Required Python packages listed in requirements.txt

Installation

  1. Clone the Repository

    git clone https://github.com/zjnbwxq/InsightSummarizer.git
    
  2. Navigate to the Project Directory

    cd InsightSummarizer
    
  3. Install Dependencies

    pip install -r requirements.txt
    

Usage

Command-Line Interface (CLI)

Run InsightSummarizer via CLI:

python3 summarizer_cli.py --path <path-to-your-document>

Web Interface with Flask

  1. Configure Email Settings

    Update sender_address and sender_pass in mail.py with your email credentials.

  2. Start the Flask Server

    python3 app.py
    
  3. Access the Web Application

    Open your browser and navigate to http://localhost:5000.

Contributing

Contributions are welcome! If you'd like to enhance InsightSummarizer, please submit a pull request or open an issue. Your feedback and support are greatly appreciated.

License

InsightSummarizer is released under the MIT License.


Made by Xiaoqi Weng from Birmingham with Love❤️

Related Skills

View on GitHub
GitHub Stars51
CategoryDevelopment
Updated6mo ago
Forks12

Languages

Python

Security Score

87/100

Audited on Sep 24, 2025

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