Fast Reader

Fast Reader is a Streamlit application designed to process and summarize PDF documents efficiently. It leverages OpenAI's language models to extract and summarize sections from textbooks or other structured documents.

Features

• Smart Structure Analysis: Analyzes textbook structure first for more accurate section detection
• Precise Section Extraction: Uses AI and binary search to accurately locate section ranges with validation
• Intelligent Chunking: Smart text segmentation that avoids breaking paragraphs or mathematical expressions
• Hierarchical Summarization: Tree-based approach enables summarizing very long sections without hitting token limits
• Multi-format Support: Handles math expressions (LaTeX), code blocks, and tables in summaries
• Batch Processing: Summarize single sections or entire chapter ranges
• Extracts sections from PDFs using AI and binary search to accurately locate section ranges.
• Summarizes text using OpenAI's language models with support for math, code, and tables.
• Provides a user-friendly interface for uploading PDFs and selecting sections to summarize.
• Supports batch summarization of multiple sections.

Key Improvements

Feature	Impact
Structure analysis first	More accurate section detection across different textbooks
Smarter chunking	Avoids breaking paragraphs or math, improves summarization quality
Tree summarization	Enables summarizing very long sections without hitting token limits
Section range validation	Catches embedded sub-sections you might have missed

Setup Instructions

Prerequisites

• Python 3.10+
• Streamlit
• PyMuPDF
• OpenAI Python Client

Installation

1. Clone the repository:

   git clone <repository-url>
   cd Fast_Reader

2. Create a virtual environment:

   python -m venv myenv
   source myenv/bin/activate

   On Windows use:

   myenv\Scripts\activate

3. Install the required packages:

   pip install -r requirements.txt

4. Set up your OpenAI API key:

   • Create a .env file in the root directory.
   • Add your OpenAI API key to the .env file:

     OPENAI_API_KEY=your_openai_api_key_here
     

Usage

1. Run the Streamlit app:

   streamlit run app.py

2. Open your web browser and go to http://localhost:8501 to access the app.

3. Upload a PDF document using the file uploader.

4. Enter the section range you wish to summarize and click "Process PDF".

5. Once sections are extracted, choose to summarize a single section or all sections in the range.

6. View and download the generated summaries.

Contribution Guidelines

We welcome contributions to improve Fast Reader! Please follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or bug fix:

   git checkout -b feature-name

3. Make your changes and commit them with descriptive messages.
4. Push your changes to your fork:

   git push origin feature-name

5. Open a pull request with a detailed description of your changes.

License

This project is licensed under the MIT License. See the LICENSE file for more information.

Acknowledgments

• Prototyped by Cursor.
• Thanks to OpenAI for providing the language models.
• Thanks to the Streamlit community for their support and resources.