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Contributing to Neurix

Thanks for your interest in contributing to Neurix. This guide will help you get started.

Getting Started

  1. Fork the repository
  2. Clone your fork: 
    git clone https://github.com/your-username/neurix.git
cd neurix
  3. Install dependencies: 
    npm install
  4. Run the development server: 
    npx tauri dev

Prerequisites

  • Node.js 18+
  • Rust 1.77+
  • Tauri CLI v2 (cargo install tauri-cli)
  • Android SDK + NDK (for mobile builds)

Project Structure

src/                  # React frontend (TypeScript)
  pages/              # Page components
  components/         # Reusable UI components
  context/            # React context providers
  services/           # Tauri IPC service layer
  theme/              # Design tokens and theme

src-tauri/            # Rust backend
  src/commands/       # Tauri IPC command handlers
  src/inference/      # Model loading and token generation
  src/models/         # Model catalog, download, management
  src/chat/           # Chat history storage

Development Workflow

  1. Create a feature branch from main:

    git checkout -b feature/your-feature

  2. Make your changes. Run lint and type checks:

    npm run lint
npx tsc --noEmit
cargo check --manifest-path src-tauri/Cargo.toml

  3. Test on desktop:

    npx tauri dev

  4. Commit with a clear message describing what changed and why.

  5. Open a pull request against main.

Code Style

  • Frontend: Biome handles formatting and linting. Run npm run format before committing.
  • Backend: Standard Rust formatting. Run cargo fmt in src-tauri/.
  • Keep components small and focused.
  • Avoid unnecessary abstractions.

Reporting Issues

Open a GitHub issue with:

  • Steps to reproduce
  • Expected vs actual behavior
  • Device/OS info (especially for Android issues)
  • Screenshots if relevant

Adding New Models

To add a model to the catalog, edit src-tauri/src/models/catalog.rs. Requirements:

  • Must be available as GGUF Q4_K_M on HuggingFace
  • Must use a Llama-compatible architecture (works with candle's quantized_llama)
  • Should be under 4GB (phone-friendly)
  • Must have an accessible tokenizer.json (preferably in the GGUF repo)
  • Add the appropriate chat template to the ChatTemplate enum and format_prompt function

License

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