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🤝 Contributing to DreamBees MLX Studio

Thank you for your interest in contributing to DreamBees MLX Studio! We welcome contributions from developers, researchers, and designers to advance sovereign, on-device AI image generation for Apple Silicon.

This guide outlines our development standards, workflow, and pull request procedures (mirrored from top open-source projects like Hugging Face, PyTorch, and Ollama).

📜 Code of Conduct

We are committed to providing a welcoming, inclusive, and harassment-free community for everyone. Please treat all contributors with respect regardless of technical experience, background, or identity.

🛠️ Development Setup

Prerequisites

  • Apple Silicon Mac (M1, M2, M3, or M4) running macOS 13.0+
  • Node.js >= 20.0
  • Python >= 3.10

Fork & Clone

git clone https://github.com/YOUR_USERNAME/DreamBeesMLX.git
cd DreamBeesMLX
npm install

Dev Mode

npm run dev

🧪 Testing & Code Standards

Before submitting a pull request, ensure all verification checks pass cleanly:

1. TypeScript Verification

./node_modules/.bin/tsc --noEmit

2. Build MCP Server

npm run build:mcp

3. Run Automated MLX Metal Benchmark Suite

python3 tests/benchmarks/run_benchmarks.py

🔀 Pull Request Workflow

  1. Create a Feature Branch: 
    git checkout -b feature/your-feature-name
  2. Commit Changes: Use descriptive, atomic commit messages following conventional commits (feat:, fix:, docs:, perf:).
  3. Run Pre-Commit Verification: Ensure zero TypeScript errors and all tests pass.
  4. Submit PR: Open a pull request against the main branch with a clear summary of changes and visual screenshots for UI modifications.