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Contributing to SIA

Thank you for your interest in contributing to SIA (Self-Improving AI). This document provides guidelines for contributing to the project.

How to Contribute

Reporting Bugs

If you find a bug, please open an issue with:

  • A clear, descriptive title
  • Steps to reproduce the problem
  • Expected vs actual behavior
  • Python version and OS
  • Relevant logs or error messages

Feature Requests

Have an idea for a new feature or improvement? Open an issue and describe:

  • What you'd like to see added or changed
  • Why it would be useful
  • Any implementation ideas you have

Submitting Changes

  1. Fork the repository
  2. Create a branch from master (git checkout -b my-change)
  3. Make your changes
  4. Run the checks (see below)
  5. Commit with a clear message describing the change
  6. Push to your fork and open a pull request against master

Development Setup

# Clone your fork
git clone https://github.com/<your-username>/sia.git
cd sia

# Create a virtual environment
python3 -m venv .venv
source .venv/bin/activate

# Install in development mode with all extras
pip install -e ".[dev]"

Running Checks

All of these must pass before submitting a PR:

# Run tests
python -m pytest tests/ -v

# Lint
ruff check sia/ tests/

# Format check
ruff format --check sia/ tests/

# Type check
ty check sia/

To auto-fix lint and formatting issues:

ruff check --fix sia/ tests/
ruff format sia/ tests/

Adding a New Task

To add a new task for SIA to work on, create the following structure:

tasks/<task-name>/
  data/
    public/
      task.md          # Task specification (required)
      evaluate.py      # Evaluation script (recommended)
    private/
      <ground-truth>   # Private evaluation data
  reference/
    reference_target_agent.py      # Agent template (required)
    SAMPLE_TASK_DESCRIPTIONS.md    # Similar task examples (required)

See existing tasks (tasks/spaceship-titanic/, tasks/lawbench/) for examples. The test suite validates that all tasks follow this structure.

Code Style

  • We use ruff for linting and formatting (configured in pyproject.toml)
  • Line length limit is 120 characters
  • Use type hints where they aid clarity
  • Follow existing patterns in the codebase

License

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