CONTRIBUTING.md

Contributing to AI LectureForge

First off, thank you for considering contributing to AI LectureForge! It's people like you that make AI LectureForge such a great tool.

Code of Conduct

By participating in this project, you are expected to uphold our Code of Conduct:

• Use welcoming and inclusive language
• Be respectful of differing viewpoints and experiences
• Gracefully accept constructive criticism
• Focus on what is best for the community
• Show empathy towards other community members

How Can I Contribute?

Reporting Bugs

Before creating bug reports, please check the issue list as you might find out that you don't need to create one. When you are creating a bug report, please include as many details as possible:

• Use a clear and descriptive title
• Describe the exact steps which reproduce the problem
• Provide specific examples to demonstrate the steps
• Describe the behavior you observed after following the steps
• Explain which behavior you expected to see instead and why
• Include screenshots if possible

Suggesting Enhancements

If you have a suggestion for the project, we'd love to hear it. Enhancement suggestions are tracked as GitHub issues. When creating an enhancement suggestion, please include:

• A clear and descriptive title
• A detailed description of the proposed enhancement
• Examples of how the enhancement would be used
• Any potential drawbacks or challenges

Pull Requests

1. Fork the repo and create your branch from main
2. If you've added code that should be tested, add tests
3. If you've changed APIs, update the documentation
4. Ensure the test suite passes
5. Make sure your code follows the existing style
6. Issue that pull request!

Development Process

1. Create a new branch:

   git checkout -b feature/my-feature
   # or
   git checkout -b bugfix/my-bugfix
   

2. Make your changes and commit:

   git add .
   git commit -m "Description of changes"
   

3. Push to your fork:

   git push origin feature/my-feature
   

Style Guidelines

• Follow PEP 8 style guide for Python code
• Use descriptive variable names
• Comment your code when necessary
• Keep functions focused and modular
• Use type hints where possible

Testing

• Write unit tests for new features
• Ensure all tests pass before submitting PR
• Include both positive and negative test cases

Project Structure

transcript_transformer/
├── src/
│   ├── core/          # Core transformation logic
│   ├── utils/         # Utility functions
│   └── app.py         # Main application
├── tests/             # Test files
└── requirements.txt   # Project dependencies

Getting Help

If you need help, you can:

• Open an issue with your question
• Reach out to the maintainers
• Check the documentation

Thank you for contributing to AI LectureForge! 🎓✨