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Contributing to DTAT OCR

Thank you for your interest in contributing to DTAT OCR! This document provides guidelines and information for contributors.

Getting Started

Development Setup

  1. Clone the repository:

    git clone https://github.com/NotADevIAmaMeatPopsicle/DTAT-OCR.git
cd DTAT-OCR

  2. Create a virtual environment:

    uv venv --python 3.12 --seed
source .venv/bin/activate  # Linux/Mac
.venv\Scripts\activate     # Windows

  3. Install dependencies:

    uv pip install -r requirements.txt

  4. Initialize the database:

    python worker.py init

  5. Run the development server:

    python -m uvicorn api:app --host 0.0.0.0 --port 8000 --reload

Running Tests

# Process a test document
python worker.py process samples/sample_paper.pdf --json

# Check system health
curl http://localhost:8000/health

How to Contribute

Reporting Bugs

  1. Check if the bug has already been reported in Issues
  2. If not, create a new issue with:
    • Clear description of the bug
    • Steps to reproduce
    • Expected vs actual behavior
    • System information (OS, Python version, GPU if applicable)

Suggesting Features

  1. Open an issue with the "enhancement" label
  2. Describe the feature and its use case
  3. Discuss implementation approach if you have ideas

Submitting Changes

  1. Fork the repository
  2. Create a feature branch: git checkout -b feature/my-feature
  3. Make your changes
  4. Test your changes thoroughly
  5. Commit with clear messages: git commit -m "Add feature X"
  6. Push to your fork: git push origin feature/my-feature
  7. Open a Pull Request

Pull Request Guidelines

  • Keep PRs focused on a single change
  • Update documentation if needed
  • Add tests for new functionality
  • Ensure all existing tests pass
  • Follow the existing code style

Architecture Decision Records (ADRs)

For significant architectural changes, please:

  1. Read existing ADRs in docs/adr/
  2. Create a new ADR using docs/adr/template.md
  3. Include the ADR in your PR for discussion

Code Style

  • Follow PEP 8 for Python code
  • Use type hints where practical
  • Keep functions focused and documented
  • Prefer clarity over cleverness

Licensing

By contributing, you agree that your contributions will be licensed under the MIT License.

Questions?

Feel free to open an issue for any questions about contributing.