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Adolfo Delorenzo 08791d2fed Add offline translation caching for seamless offline experience
- Implemented TranslationCache class with IndexedDB storage
- Cache translations automatically with 30-day expiration
- Added cache management UI in settings modal
  - Shows cache count and size
  - Toggle to enable/disable caching
  - Clear cache button
- Check cache first before API calls (when enabled)
- Automatic cleanup when reaching 1000 entries limit
- Show "(cached)" indicator for cached translations
- Works completely offline after translations are cached

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-06-02 21:56:31 -06:00
static Add offline translation caching for seamless offline experience 2025-06-02 21:56:31 -06:00
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.gitignore Major improvements: TypeScript, animations, notifications, compression, GPU optimization 2025-06-02 21:18:16 -06:00
app.py Major improvements: TypeScript, animations, notifications, compression, GPU optimization 2025-06-02 21:18:16 -06:00
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whisper_config.py Major improvements: TypeScript, animations, notifications, compression, GPU optimization 2025-06-02 21:18:16 -06:00

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

  1. Install the required Python packages:

    pip install -r requirements.txt
    
  2. Make sure you have Ollama installed and the Gemma 3 model loaded:

    ollama pull gemma3
    
  3. Ensure your OpenAI Edge TTS server is running on port 5050.

  4. Run the application:

    python app.py
    
  5. Open your browser and navigate to:

    http://localhost:8000
    

Usage

  1. Select your source language from the dropdown menu
  2. Press the microphone button and speak
  3. Press the button again to stop recording
  4. Wait for the transcription to complete
  5. Select your target language
  6. Press the "Translate" button
  7. 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.