- Fixed preview endpoint to work with both Kokoro and Piper engines
- Improved voice model download with curl fallback and SSL handling
- Added better error messages when models are missing
- Created PIPER_SETUP.md with manual download instructions
- Added test_piper_direct.py for testing Piper installation
- Updated README with voice model download requirements
Note: Piper voice models require manual download from GitHub releases
due to HuggingFace URL structure. See PIPER_SETUP.md for instructions.
- Created PiperTTSService with pitch shifting (-12 to +12 semitones)
- Created UnifiedTTSService to manage multiple TTS engines
- Added engine selection endpoints (GET/POST /api/tts/engines)
- Added voices listing endpoint (GET /api/tts/voices)
- Added pitch_adjustments parameter to TTS generation
- Created install_piper.sh for easy Piper installation
- Updated backend README with multi-engine documentation
- Created comprehensive PIPER_TTS_GUIDE.md
- Added TTS_ENGINE environment variable for engine selection
- Updated requirements.txt with piper-tts and pydub
This allows users to choose between Kokoro (high quality) and Piper
(fast with pitch control) TTS engines at runtime.
Features:
- Voice preview button to test voices before generation
- Age category selection (young, teen, adult, old)
- Age categories adjust voice speed automatically:
- Young: 1.15x (faster, energetic)
- Teen: 1.08x (slightly faster)
- Adult: 1.0x (normal)
- Old: 0.85x (slower, measured)
- Preview caching to avoid regenerating same voice
- Backend /api/tts/preview endpoint for voice samples
- Frontend previewVoice API function
This allows users to hear how each voice sounds and adjust
character ages to make them sound younger or older.
- Added ScriptRequest, ScriptResponse, and ScriptSegment Pydantic models
- Created /api/tts/script POST endpoint in main.py
- Integrated with TTSService to generate script segments using AI
- Added generate_script_segments method to TTSService
- Returns segments with unique IDs for frontend tracking
- Handles errors gracefully when AI segmentation fails
- Falls back to pattern-based segmentation when Ollama unavailable
- Added comprehensive tests for the endpoint
- Validates: Requirements 15.1, 15.2
- Add POST /api/tts endpoint with full request validation
- Validate text, language code, speed range, and roles list
- Integrate TTSService to generate multi-voice audiobooks
- Fix Kokoro pipeline generator handling to properly collect audio
- Stream audio response with correct Content-Type (audio/wav)
- Add Content-Disposition header with filename (audiobook.wav)
- Handle errors gracefully with appropriate HTTP status codes
- Add comprehensive test suite for endpoint validation
Requirements: 6.1, 6.7, 6.8, 9.5
- Created RoleDetector class with colon and bracket pattern extraction
- Implemented role deduplication logic
- Added fallback to default 'Narrator' role when no patterns found
- Created /api/tts/roles endpoint using RoleDetector
- Added comprehensive test suite for role detection
- All tests passing (7/7)
Requirements: 2.1, 2.2, 2.3, 2.4, 2.5, 2.6
- Created FastAPI application with CORS middleware
- Defined Pydantic models (RoleDetectionRequest, RolesResponse, TTSRequest, ErrorResponse)
- Implemented /api/health endpoint
- Set up error handling middleware for validation and general exceptions
- Configured logging with INFO level
- Added test script to verify API functionality
- Validates Requirements: 9.1, 9.2, 9.4
- Created backend directory with FastAPI project structure
- Created frontend directory with React + TypeScript + Vite
- Configured Python virtual environment and installed dependencies (fastapi, uvicorn, kokoro, soundfile, python-multipart)
- Verified espeak-ng system dependency is installed
- Configured Node.js project with TypeScript, React, and Vite
- Set up Tailwind CSS for styling
- Set up environment variable configuration for both projects
- Created comprehensive README documentation
Requirements: 9.6, 10.2, 11.1
