unimdgen 0.6.1

Generates markdown repositories for university mathematics modules based on raw material provided by the university.

Module Content Generation Tool

Overview

The Module Content Generation Tool is designed to automate the creation of educational content, specifically tailored for university modules. Utilizing Python, it generates markdown files for module pages, classes, summaries, and revision materials, streamlining the process of content creation for educators and students alike.

Features

• Automated Markdown Generation: Creates markdown files for module overviews, class content, summary questions, summary notes, practice tests, and flashcards.
• Comprehensive Data Handling: Parses and generates content from various data sources, including lecture slides, notes, and PDFs, ensuring a wide range of educational materials are covered.
• Customizable Output: Offers flexibility in the generated content, allowing for adjustments to fit specific module requirements or teaching styles.
• Enhanced Logging and Error Handling: Incorporates advanced logging for monitoring the generation process and robust error handling mechanisms for a smooth operation.

Getting Started

Prerequisites

Ensure you have Python 3.8 or higher installed on your system. Dependencies include:

• fitz for PDF reading,
• Jinja2 for templating markdown files,
• OpenAI for utilizing GPT models in content generation.

Installation

1. Clone the repository to your local machine.
2. Install the required dependencies:

   pip install -r requirements.txt
   

Usage

1. Place your input files (lecture slides, notes, etc.) in the designated input directory, ensuring to number classes as "1.pdf", "2.pdf", etc.
2. Run main.py to start the content generation process:

   python main.py
   

3. Follow the prompts and logs for any required manual inputs or corrections.
4. Generated markdown files will be available in the output directory, ready for review and use.

Contributing

Contributions to the Module Content Generation Tool are welcome. Please follow the standard fork, branch, and pull request workflow.

License

Distributed under the MIT License. See LICENSE for more information.

Acknowledgments

• Utilizes GPT models from OpenAI for content generation.
• Inspired by the need for efficient educational content creation.