Adolfo Delorenzo
3804897e2b
Frontend Error Boundaries: - Created ErrorBoundary class for centralized error handling - Wraps critical functions (transcribe, translate, TTS) with error boundaries - Global error handlers for unhandled errors and promise rejections - Component-specific error recovery with fallback functions - User-friendly error notifications with auto-dismiss - Error logging to backend for monitoring - Prevents cascading failures from component errors Backend Error Handling: - Added error boundary decorator for Flask routes - Global Flask error handlers (404, 500, generic exceptions) - Frontend error logging endpoint (/api/log-error) - Structured error responses with component information - Full traceback logging for debugging - Production vs development error message handling Features: - Graceful degradation when components fail - Automatic error recovery attempts - Error history tracking (last 50 errors) - Component-specific error handling - Production error monitoring ready - Prevents full app crashes from isolated errors 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com> |
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| static | ||
| templates | ||
| venv | ||
| .gitignore | ||
| app.py | ||
| GPU_SUPPORT.md | ||
| health-monitor.py | ||
| package-lock.json | ||
| package.json | ||
| README_TYPESCRIPT.md | ||
| README.md | ||
| requirements.txt | ||
| setup-script.sh | ||
| tsconfig.json | ||
| tts_test_output.mp3 | ||
| tts-debug-script.py | ||
| whisper_config.py | ||
Voice Language Translator
A mobile-friendly web application that translates spoken language between multiple languages using:
- Gemma 3 open-source LLM via Ollama for translation
- OpenAI Whisper for speech-to-text
- OpenAI Edge TTS for text-to-speech
Supported Languages
- Arabic
- Armenian
- Azerbaijani
- English
- French
- Georgian
- Kazakh
- Mandarin
- Farsi
- Portuguese
- Russian
- Spanish
- Turkish
- Uzbek
Setup Instructions
-
Install the required Python packages:
pip install -r requirements.txt -
Make sure you have Ollama installed and the Gemma 3 model loaded:
ollama pull gemma3 -
Ensure your OpenAI Edge TTS server is running on port 5050.
-
Run the application:
python app.py -
Open your browser and navigate to:
http://localhost:8000
Usage
- Select your source language from the dropdown menu
- Press the microphone button and speak
- Press the button again to stop recording
- Wait for the transcription to complete
- Select your target language
- Press the "Translate" button
- Use the play buttons to hear the original or translated text
Technical Details
- The app uses Flask for the web server
- Audio is processed client-side using the MediaRecorder API
- Whisper for speech recognition with language hints
- Ollama provides access to the Gemma 3 model for translation
- OpenAI Edge TTS delivers natural-sounding speech output
Mobile Support
The interface is fully responsive and designed to work well on mobile devices.