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CONTRIBUTING.md

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Contributing to J.A.R.V.I.S.

First off — thank you for considering contributing. Whether it's a bug report, feature request, or a pull request, every contribution helps make the Jetson AI community stronger.

Quick Links

  • Issues — report bugs or request features
  • Discussions — ask questions, share your setup
  • Roadmap — see what's planned

Development Setup

# Clone
git clone https://github.com/steffenpharai/Jarvis.git && cd Jarvis

# Python environment
python3 -m venv venv && source venv/bin/activate
pip install --upgrade pip && pip install -r requirements.txt

# Download models
bash scripts/bootstrap_models.sh

# PWA frontend
cd pwa && npm install && npm run build && cd ..

# Verify everything works
ruff check .
pytest tests/unit/
python main.py --dry-run

Making Changes

  1. Fork the repo and create a branch from main
  2. Write code — follow the existing style (ruff handles formatting)
  3. Add tests — new features need tests in tests/unit/ or tests/e2e/
  4. Run the checks:
ruff check .              # Lint
pytest tests/unit/        # Unit tests (no hardware needed)
python main.py --dry-run  # Smoke test
  1. Submit a PR with a clear description of what and why

Code Style

  • Python 3.10+ — we use modern syntax (match/case, type hints, etc.)
  • Ruff for linting — ruff check . must pass with zero errors
  • Line length — 100 chars (configured in pyproject.toml)
  • Docstrings — Google style for public functions
  • Commit messages — imperative mood, concise ("Add vision depth fallback", not "Added stuff")

What We're Looking For

High-impact contributions

  • VLM integration (LLaVA, Qwen-VL) for native image understanding
  • ROS 2 bridge for robotics integration
  • Docker image for JetPack 6.x
  • Home Assistant integration
  • Multi-camera / multi-room support
  • Performance optimizations on 8GB RAM

Always welcome

  • Bug fixes with test coverage
  • Documentation improvements
  • New E2E tests for hardware scenarios
  • PWA UI/UX improvements
  • New Piper voice models

Hardware testing

If you have a Jetson Orin Nano, running the E2E tests and reporting results is incredibly valuable:

pytest tests/e2e/ -m e2e -v 2>&1 | tee e2e_results.txt

Share results in an issue or discussion!

Pull Request Guidelines

  • Keep PRs focused — one feature or fix per PR
  • Include before/after benchmarks for performance changes
  • Update README.md if adding user-facing features
  • All CI checks must pass (lint + unit tests)
  • E2E tests are run manually on hardware — note if your change affects them

Questions?

Open a Discussion. No question is too basic.

"I'm not saying I'll merge it immediately, sir, but I'll certainly give it my full attention."