foxus/PROJECT_SUMMARY.md

Foxus - Local-First AI Coding Assistant

Project Overview

Foxus is a privacy-focused, fully offline coding assistant that provides AI-powered code completion, refactoring, bug fixing, and code explanation using locally running language models. Built with modern technologies, it offers a seamless development experience without sending your code to external servers.

Key Features

🔒 Privacy & Security

• Fully Local: All processing happens on your machine
• No Internet Required: Works completely offline
• Zero Data Collection: Your code never leaves your computer

🧠 AI-Powered Assistance

• Code Explanation: Understand complex code snippets
• Smart Refactoring: Improve code quality and maintainability
• Bug Detection & Fixing: Identify and resolve issues
• Code Completion: Intelligent autocomplete suggestions
• Documentation Generation: Auto-generate comments and docs

💻 Developer Experience

• Multi-Language Support: Python, JavaScript, TypeScript, Go, Java, Rust, and more
• Keyboard Shortcuts: Quick access to AI commands (/explain, /refactor, /fix)
• Modern UI: Clean, responsive interface with dark theme
• Project Context: Multi-file analysis and understanding

⚡ Performance & Compatibility

• Cross-Platform: Windows, Linux, and macOS support
• Lightweight: Built with Tauri for minimal resource usage
• Fast Response: Local models provide quick feedback
• Extensible: Easy to add new AI models and commands

Technology Stack

Frontend

• Framework: Tauri + React + TypeScript
• Editor: Monaco Editor (VS Code engine)
• Styling: Tailwind CSS
• State Management: Zustand
• Build Tool: Vite

Backend

• API: FastAPI (Python)
• LLM Integration: Ollama
• Models: CodeLlama, Deepseek-Coder, StarCoder
• File Handling: Python file system APIs

Desktop Application

• Framework: Tauri (Rust + Web Technologies)
• Bundle Size: ~15MB (significantly smaller than Electron)
• Performance: Native-level performance

Supported AI Models

Code-Specialized Models

1. CodeLlama 7B/13B - Meta's code generation model
2. Deepseek-Coder 6.7B - Advanced code understanding
3. StarCoder 7B - Multi-language code completion
4. CodeGemma 7B - Google's code model

Model Capabilities

• Code generation and completion
• Bug detection and fixing
• Code explanation and documentation
• Refactoring suggestions
• Multi-language understanding

Architecture Benefits

Local-First Approach

• Privacy: Code never leaves your machine
• Speed: No network latency
• Reliability: Works without internet
• Cost: No API fees or usage limits

Modular Design

• Extensible: Easy to add new features
• Maintainable: Clear separation of concerns
• Testable: Well-structured codebase
• Scalable: Can handle large projects

Use Cases

Individual Developers

• Learning: Understand unfamiliar code
• Productivity: Speed up coding with AI assistance
• Quality: Improve code through AI suggestions
• Debugging: Get help fixing complex issues

Teams & Organizations

• Code Reviews: AI-assisted code analysis
• Standards: Consistent code quality
• Documentation: Auto-generated code docs
• Training: Help junior developers learn

Enterprise

• Security: Keep sensitive code private
• Compliance: Meet data residency requirements
• Customization: Add domain-specific models
• Integration: Embed in existing workflows

Getting Started

Quick Setup (5 minutes)

1. Install Prerequisites: Node.js, Python, Rust, Ollama
2. Install Dependencies: npm install & pip install -r requirements.txt
3. Download AI Model: ollama pull codellama:7b-code
4. Start Services: Backend API & Frontend app
5. Start Coding: Open files and use AI commands

Development Workflow

1. Open Foxus: Launch the desktop application
2. Load Project: Open your code files
3. Select Code: Highlight code you want help with
4. Use AI Commands:
   • Ctrl+Shift+E - Explain code
   • Ctrl+Shift+R - Refactor code
   • Ctrl+Shift+F - Fix bugs
   • Ctrl+K - Command palette

Project Structure

foxus/
├── backend/                 # FastAPI Python backend
│   ├── app/
│   │   ├── api/            # API routes (ai, files, models)
│   │   ├── core/           # Configuration and settings
│   │   ├── models/         # Pydantic data models
│   │   └── services/       # Ollama integration
│   ├── main.py             # FastAPI entry point
│   └── requirements.txt    # Python dependencies
├── frontend/               # Tauri + React frontend
│   ├── src/
│   │   ├── components/     # React UI components
│   │   ├── stores/         # Zustand state management
│   │   ├── hooks/          # Custom React hooks
│   │   └── App.tsx         # Main application
│   ├── src-tauri/          # Tauri Rust backend
│   │   ├── src/main.rs     # Rust entry point
│   │   └── tauri.conf.json # Tauri configuration
│   └── package.json        # Node.js dependencies
├── docs/                   # Documentation
├── README.md               # Project overview
├── SETUP.md               # Installation guide
└── PROJECT_SUMMARY.md     # This file

Development Roadmap

Phase 1: MVP ✅

• Basic code editor interface
• Local AI model integration
• Core AI commands (explain, refactor, fix)
• Desktop application framework

Phase 2: Enhanced Features

• Advanced code completion
• Project-wide context awareness
• Custom AI prompts
• File tree and project management
• Settings and preferences

Phase 3: Advanced Capabilities

• Plugin system
• Custom model training
• Team collaboration features
• Integration with version control
• Advanced debugging assistance

Comparison with Alternatives

Feature	Foxus	GitHub Copilot	Cursor	Windsurf
Privacy	✅ Fully Local	❌ Cloud-based	❌ Cloud-based	❌ Cloud-based
Offline	✅ Yes	❌ No	❌ No	❌ No
Cost	✅ Free	💰 $10/month	💰 $20/month	💰 $15/month
Customization	✅ Full control	❌ Limited	❌ Limited	❌ Limited
Multi-language	✅ Yes	✅ Yes	✅ Yes	✅ Yes
Speed	⚡ Local	🌐 Network	🌐 Network	🌐 Network

Contributing

How to Contribute

1. Fork the repository
2. Create a feature branch
3. Implement your changes
4. Add tests if applicable
5. Submit a pull request

Areas for Contribution

• UI/UX Improvements: Better design and user experience
• AI Model Integration: Support for new models
• Language Support: Additional programming languages
• Performance: Optimization and speed improvements
• Documentation: Guides and examples

Technical Highlights

Performance Optimizations

• Tauri vs Electron: 10x smaller bundle size
• Local Processing: Zero network latency
• Efficient State Management: Zustand for minimal re-renders
• Code Splitting: Lazy loading for faster startup

Security Features

• No External Calls: All processing happens locally
• File System Sandboxing: Tauri security model
• Input Validation: Comprehensive API validation
• Error Handling: Graceful failure recovery

Future Vision

Foxus aims to become the de facto standard for privacy-conscious developers who want AI assistance without compromising their code security. The goal is to create an ecosystem where:

• Developers have full control over their AI assistant
• Organizations can maintain code privacy and compliance
• AI Models can be easily customized for specific domains
• Innovation happens locally without external dependencies

Getting Help

Documentation

• README.md: Quick project overview
• SETUP.md: Detailed installation guide
• API Documentation: Available at http://localhost:8000/docs

Community

• Issues: Report bugs and request features
• Discussions: Ask questions and share ideas
• Contributing: Help improve Foxus

Support

• Check troubleshooting in SETUP.md
• Review API logs for debugging
• Ensure Ollama is running properly
• Verify model availability

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Foxus represents the future of AI-assisted development: powerful, private, and fully under your control. Join us in building the next generation of coding tools that respect developer privacy while maximizing productivity.

🦊 Start coding smarter, not harder, with Foxus!