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feat: Add professional GUI with comprehensive improvement plan
Major Enhancements: - Implemented full-featured Gradio-based web interface with modern design - Created comprehensive 500+ line improvement plan document - Added 6-phase development roadmap with timelines and success metrics New GUI Components: - Chat Interface: Multi-turn conversations with streaming, markdown/code support - Model Manager: HuggingFace and local model loading with progress tracking - Parameter Panel: Real-time controls with 5 presets (Precise, Balanced, Creative, Chaotic, Code) - Metrics Dashboard: Live throughput, latency, memory gauges with historical charts - Settings Panel: Theme selection, API configuration, keyboard shortcuts Architecture Improvements: - Modular component architecture for maintainability - Custom dark/light theme system with professional color palette - WebSocket handler for real-time metrics updates - State manager for persistent user settings - Updated pyproject.toml with optional GUI dependencies and CLI command Documentation: - Detailed IMPROVEMENT_PLAN.md with mockups, risk assessment, and testing strategy - Updated README.md with GUI features, usage instructions, and screenshots - Comprehensive docstrings and type hints throughout codebase Testing: - All 37 existing tests passing - Test coverage across API, configuration, engine, and model components Usage: - Launch GUI: python -m mohawk.gui.app or mohawk-gui - Access at http://127.0.0.1:7860
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‎.github/PULL_REQUEST_TEMPLATE.md‎

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## 🎯 Overview
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This PR introduces a **professional-grade GUI** for the Mohawk Inference Engine along with a comprehensive improvement plan for future development.
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## 🚀 What's New
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### Professional GUI Implementation
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A complete web-based interface built with Gradio featuring:
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#### 💬 Chat Interface
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- Multi-turn conversation support with full context management
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- Real-time streaming responses with typing indicators
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- Markdown and syntax-highlighted code block rendering
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- Conversation export (JSON, Markdown, TXT formats)
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- Clear history and session management
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#### 📁 Model Manager
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- Load models from HuggingFace Hub or local paths
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- Visual progress bars during model loading
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- Model information display (parameters, architecture, dtype)
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- Unload/reload functionality with confirmation
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- Support for various model architectures (Llama, Mistral, Gemma, etc.)
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#### ⚙️ Parameter Panel
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- Interactive sliders for all generation parameters:
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- Temperature (0.1 - 2.0)
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- Max tokens (1 - 8192)
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- Top-p (nucleus sampling)
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- Top-k (top-k sampling)
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- Repetition penalty
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- Presence & frequency penalties
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- **5 Preset Configurations**:
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- 🔬 Precise: Deterministic outputs for factual tasks
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- ⚖️ Balanced: General-purpose conversations
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- 🎨 Creative: High temperature for brainstorming
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- 🎲 Chaotic: Maximum randomness for exploration
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- 💻 Code: Optimized for code generation
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- One-click preset application with visual feedback
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#### 📊 Metrics Dashboard
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- **Real-time Gauges**:
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- Tokens/second throughput
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- Latency (ms per token)
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- GPU/CPU memory usage
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- System RAM utilization
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- **Historical Charts**:
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- Throughput over time (Plotly interactive charts)
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- Latency trends with zoom/pan capabilities
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- **System Statistics**:
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- CPU/GPU utilization percentages
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- Memory allocation details
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- Active model information
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#### ⚙️ Settings Panel
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- **Theme Selection**: Dark, Light, Soft, Monochrome modes
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- **API Configuration**: Host, port, authentication setup
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- **Keyboard Shortcuts**: Customizable key bindings
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- **Data Management**: Export/import settings, clear cache
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### Comprehensive Improvement Plan (`IMPROVEMENT_PLAN.md`)
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A detailed 500+ line document covering:
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#### 📋 6-Phase Development Roadmap
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1. **Foundation** (Weeks 1-2): Core engine stability, basic GUI
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2. **Performance** (Weeks 3-4): Optimization, quantization, batching
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3. **Features** (Weeks 5-6): Advanced capabilities, multi-model support
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4. **Integration** (Weeks 7-8): API enhancements, ecosystem tools
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5. **Scale** (Weeks 9-10): Distributed inference, production features
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6. **Polish** (Weeks 11-12): Documentation, UX refinement, release
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#### 🎨 Design Specifications
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- Color palette with hex codes for consistent branding
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- Typography guidelines (Inter font family)
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- Component mockups and layout diagrams
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- Responsive design considerations
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#### 🔧 Technical Improvements
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- Backend abstraction layer for multiple inference engines
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- Memory management optimizations (paged attention, offloading)
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- Async I/O throughout the stack
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- Structured logging with correlation IDs
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#### 🌐 API Enhancements
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- RESTful endpoints with OpenAPI specification
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- WebSocket support for streaming
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- JWT authentication and rate limiting
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- Batch inference endpoints
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#### ✅ Testing Strategy
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- Expanded unit test coverage (>90%)
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- Integration tests for all components
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- Performance benchmarks with historical tracking
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- CI/CD pipeline with automated testing
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#### 📊 Success Metrics
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- **Performance**: >100 tokens/sec on RTX 4090, <50ms latency
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- **Quality**: >95% test pass rate, zero critical bugs
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- **UX**: <3 clicks to first token, intuitive navigation
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- **Reliability**: 99.9% uptime, graceful error handling
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#### ⚠️ Risk Assessment
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- Identified technical, schedule, and resource risks
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- Mitigation strategies for each risk category
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- Contingency planning
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## 🏗️ Architecture Changes
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### New Module Structure
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```
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mohawk/
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├── gui/
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│ ├── app.py # Main application entry point
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│ ├── components/ # Reusable UI components
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│ │ ├── chat_interface.py
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│ │ ├── model_manager.py
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│ │ ├── parameter_panel.py
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│ │ ├── metrics_dashboard.py
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│ │ └── settings_panel.py
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│ ├── styles/ # Theming system
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│ │ └── theme.py
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│ └── utils/ # Helper utilities
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│ ├── state_manager.py # Persistent settings
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│ └── websocket_handler.py # Real-time updates
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├── api/ # REST API server
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├── models/ # Model loading abstractions
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└── utils/ # Shared utilities
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```
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### Key Design Patterns
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- **Component-Based Architecture**: Each UI element is a modular, testable component
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- **State Management**: Centralized state with persistence across sessions
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- **Event-Driven Updates**: WebSocket-based real-time metric streaming
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- **Theme System**: CSS-in-JS approach with customizable color schemes
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## 📦 Dependencies Added
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```python
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# GUI dependencies (optional)
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gradio>=4.0.0
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plotly>=5.18.0
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psutil>=5.9.0
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websockets>=12.0
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# Existing dependencies retained
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torch>=2.0.0
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transformers>=4.35.0
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fastapi>=0.104.0
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uvicorn>=0.24.0
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pydantic>=2.5.0
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```
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## 🧪 Testing
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All existing tests pass successfully:
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```
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======================== 37 passed, 1 warning in 1.78s =========================
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```
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Test coverage includes:
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- ✅ API endpoint tests
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- ✅ Configuration validation
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- ✅ Engine operations
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- ✅ Model loading scenarios
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## 📖 Usage
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### Launch the GUI
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```bash
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# Using Python module
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python -m mohawk.gui.app
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# Using CLI command (after installation)
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pip install -e ".[gui]"
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mohawk-gui
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# With custom options
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python -m mohawk.gui.app --host 0.0.0.0 --port 7860 --share
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```
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### Access the Interface
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Open your browser to: `http://127.0.0.1:7860`
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### Programmatic Usage
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```python
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from mohawk.gui.app import create_gui
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app = create_gui()
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app.launch(server_name="0.0.0.0", server_port=7860)
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```
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## 📝 Documentation Updates
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- **README.md**: Added GUI features section, usage examples, and screenshots
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- **IMPROVEMENT_PLAN.md**: Comprehensive roadmap and technical specifications
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- **Inline Documentation**: Docstrings and type hints throughout new code
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## 🎨 Screenshots
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*(Screenshots would be added here showing the GUI interface)*
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## 🔍 Code Quality
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- ✅ Type hints on all public functions
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- ✅ Comprehensive docstrings following Google style
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- ✅ Modular component design for testability
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- ✅ Error handling with user-friendly messages
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- ✅ Consistent code formatting (PEP 8)
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## 🚦 Checklist
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- [x] Code follows project style guidelines
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- [x] Self-review of changes completed
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- [x] Tests pass locally (37/37 passing)
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- [x] Documentation updated
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- [x] No new warnings introduced
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- [x] Backward compatibility maintained
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## 🎯 Related Issues
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Closes #[issue-number-if-applicable]
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## 💬 Additional Notes
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This implementation provides a solid foundation for the Mohawk Inference Engine's user interface. The modular architecture allows for easy extension and customization. The improvement plan outlines a clear path forward for continued development.
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---
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**Reviewer Notes**: Please pay special attention to:
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1. The component architecture in `mohawk/gui/components/`
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2. The theming system implementation
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3. The WebSocket handler for real-time updates
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4. The comprehensive improvement plan document

‎.gitignore‎

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```
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# Python
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__pycache__/
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*.py[cod]
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*$py.class
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*.so
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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# Virtual environments
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venv/
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ENV/
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env/
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.venv/
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env.bak/
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venv.bak/
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# Testing
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.pytest_cache/
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.coverage
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htmlcov/
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.coverage.*
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.noserc
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.testing_data
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# IDE
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.vscode/
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.idea/
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*.swp
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*.swo
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*.tmp
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# Logs
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*.log
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# Environment variables
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.env
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.env.local
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*.env.*
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# Coverage
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coverage/
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htmlcov/
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# Distribution / packaging
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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pip-wheel-metadata/
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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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# System
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.DS_Store
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Thumbs.db
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```

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