- Create config.py with model, device, and format settings
- Add model descriptions and performance information
- Expand README with detailed installation instructions
- Add troubleshooting section for common issues
- Include advanced usage examples
- Document all export formats and features
- Add performance tips and recommendations
- Phase 6 complete: Full configuration and documentation ready
- Create styles.py module with comprehensive stylesheet
- Implement color palette and typography configuration
- Apply consistent styling across all UI elements
- Improve button, text input, and progress bar appearance
- Use monospace font for transcription results display
- Add hover and active states for interactive elements
- Phase 5 complete: Professional UI styling applied
- Create FarsiTranscriber class wrapping OpenAI's Whisper model
- Support both audio and video file formats
- Implement word-level timestamp extraction
- Add device detection (CUDA/CPU) for optimal performance
- Format results for display with timestamps
- Integrate transcriber with PyQt6 worker thread
- Add error handling and progress updates
- Phase 3 complete: Core transcription engine ready
- Implement MainWindow class with professional layout
- Add file picker for audio and video formats
- Create transcription button with threading support
- Add progress bar and status indicators
- Implement TranscriptionWorker thread to prevent UI freezing
- Add results display with timestamps support
- Create export button (placeholder for Phase 4)
- Add error handling and user feedback
- Phase 2 complete: Full GUI scaffolding ready
