- Created PIPER_FINAL_SUMMARY.md with complete delivery overview
- Documented all 6 git commits and files created/modified
- Listed testing checklist and verification steps
- Provided clear comparison between Kokoro and Piper
- Included setup instructions and support resources
Piper TTS integration is complete and production-ready with
comprehensive documentation and error handling.
- Added proper error handling for missing voice models in preview endpoint
- Return 404 with helpful message when Piper models not found
- Added user-friendly alert in frontend when preview fails
- Added prominent warning in UI when Piper is selected about manual setup
- Check for empty audio before returning to prevent decode errors
Users now get clear feedback when Piper voice models are missing
instead of cryptic 'media could not be decoded' errors.
- Created PIPER_STATUS.md explaining current state and manual setup
- Documented why automatic download doesn't work
- Provided clear step-by-step setup instructions
- Listed alternative (Kokoro TTS) for users who prefer zero-setup
- Added troubleshooting for common errors
Piper TTS is fully functional but requires one-time manual voice model download.
- 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 PIPER_TTS_INTEGRATION.md with complete integration summary
- Added test_engine_selection.py for testing engine switching
- Documented engine comparison, usage examples, and pitch guidelines
- Listed all modified/created files and git commits
- Included next steps for optional enhancements
Task 26 completed: Piper TTS integration with engine selection UI
- Added engine selection buttons (Kokoro vs Piper) in VoiceAssignmentSection
- Implemented getEngines(), setEngine(), and getVoices() API client functions
- Engine selector dynamically loads available voices for selected engine
- Added visual feedback for active engine with descriptions
- Piper engine shows pitch control capability notice
- Voice dropdowns update automatically when switching engines
- Audio cache clears when switching engines for clean state
Users can now easily switch between Kokoro (high quality) and
Piper (fast with pitch control) directly from the UI.
- 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.
- Clear all cached previews for a role when age changes
- Clear all cached previews for a role when voice changes
- Now preview correctly reflects the selected age speed modifier
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.
- Move Google Fonts import before Tailwind directives
- Fix PostCSS build warning
- Ensure proper CSS compilation
NOTE: Dev server must be restarted for changes to take effect
- Add generous padding and spacing throughout (p-10, p-12)
- Constrain content width with max-w-4xl and max-w-5xl
- Increase font sizes for better hierarchy (text-3xl, text-lg)
- Add gradient backgrounds to cards and elements
- Implement smooth transitions and hover states
- Create professional progress stepper with labels
- Add shadow effects with color-matched glows
- Increase button padding and font sizes
- Add gradient borders on hover
- Implement proper visual breathing room
- Create polished, premium aesthetic
- Add smooth cubic-bezier transitions
- Improve form input styling with focus rings
- Create professional card hover effects
- Add animated gradient backgrounds with floating particles
- Implement advanced glass morphism with enhanced blur effects
- Add Google Fonts Inter for professional typography
- Create sophisticated button animations with ripple effects
- Add progress indicator dots showing current step
- Implement card hover effects with smooth transforms
- Add animated gradient text with shimmer effects
- Create premium loading spinners with dual rings
- Add character counter to textarea
- Implement numbered badges for roles and segments
- Add gradient backgrounds to all cards and sections
- Create pulsing glow animations for important elements
- Add emoji icons throughout for visual appeal
- Implement responsive grid layouts for settings
- Add detailed subtitles and descriptions to sections
- Create success celebration with bouncing animation
- Add shadow effects with color-matched glows
- Implement smooth transitions and cubic-bezier easing
- Add visual hierarchy with varied font weights
- Create immersive, modern user experience
- Add purple/indigo gradient background throughout app
- Implement glass morphism effects on all cards
- Add gradient buttons with smooth hover animations
- Integrate emoji icons for better visual communication
- Enhance typography with improved font stack
- Add loading spinners and smooth transitions
- Improve color scheme with modern purple/indigo palette
- Add glowing shadows and depth effects
- Maintain responsive design and touch-friendly interactions
Updated the speaker detection prompt to explicitly instruct the AI to:
- Identify narrative text and assign it to 'Narrator'
- Detect character dialogue and list character names
- Include BOTH Narrator and characters when story has mixed content
This ensures stories with narrative descriptions get proper voice
assignments for both the narrator and speaking characters.
Example: Story with 'Once upon a time...' narrative and dialogue from
Lily, Benny, Sammy now correctly detects all 4 roles.
- Changed 'Generate Audiobook' button to 'Next: Review Script'
- Added 'Skip Review & Generate' button as alternative
- Updated button handlers to call handleGenerateScript and handleSkipReview
- Updated button styling: primary button now blue for review, green for skip
- Maintains backward compatibility with optional onSkipReview prop
Requirements: 15.1, 15.8
- Add 'review' phase to application state
- Add scriptSegments state variable for storing AI-generated segments
- Add isGeneratingScript loading state for script generation
- Implement handleGenerateScript() to call API and transition to review phase
- Implement handleSkipReview() to bypass review and go directly to generation
- Implement handleSegmentChange() to update speaker assignments in segments
- Update handleGenerate() to use edited segments when available
- Wire up ScriptReviewSection component in review phase
- Update phase transitions: input → assignment → review → generated
- Add loading indicator for script generation
Validates Requirements: 15.1, 15.3, 15.6, 15.7, 15.8
Task: 22. Update App component for script review workflow
- Created ScriptReviewSection component with script segment display
- Added speaker dropdown for each segment to allow editing assignments
- Implemented Generate Audiobook and Skip Review buttons
- Styled for readability and mobile responsiveness with Tailwind CSS
- Text segments displayed as read-only (only speaker assignment is editable)
- Follows existing component patterns from VoiceAssignmentSection
- Validates Requirements 15.3, 15.4, 15.5, 15.6, 15.8
- 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
- Step-by-step testing instructions
- Multiple test scenarios with expected results
- Troubleshooting section
- Tips for best results
- Comparison of before/after AI features
- Tests complete workflow from unmarked text to segmented audio
- Demonstrates AI role detection on narrative text
- Shows AI text segmentation with intelligent speaker assignment
- Validates dialogue detection and speaker distribution
- Provides quality analysis of segmentation results
- Added comprehensive documentation for AI speaker detection
- Documented AI text segmentation capabilities
- Added Ollama setup instructions
- Explained benefits of AI-powered vs pattern-based detection
- Updated API endpoint documentation with AI feature details
- Added segment_text() method to OllamaService for AI-based text splitting
- OllamaService now annotates each text segment with the appropriate speaker
- Updated TTSService to use AI segmentation when available
- Falls back to pattern-based segmentation when Ollama unavailable
- AI intelligently assigns dialogue to speakers and narrative to Narrator
- Added comprehensive test suite for AI segmentation
- Verified AI correctly splits unmarked dialogue between multiple speakers
This makes the tool much more powerful - users can now input plain narrative
text without explicit role markers and the AI will intelligently assign voices
to different characters and the narrator.
- Changed model from 'llama3:8b' to 'llama3:latest' to match available models
- Verified Ollama integration is working correctly
- AI detection now successfully identifies speakers in unmarked text
- Sample up to 4 chunks of 5000 characters from different text positions
- Distribute samples evenly across beginning, middle, and end of text
- Deduplicate speakers across all samples for comprehensive detection
- Log individual sample results for debugging
- Handle short texts efficiently (single sample)
- Updated tests to verify multi-sample behavior
This ensures speakers introduced anywhere in long texts are detected,
not just those appearing in the first 2000 characters.
- Added Requirement 14 for intelligent speaker detection using Ollama/llama3:8B
- Updated design document with OllamaService component and integration details
- Added 4 new correctness properties for Ollama functionality
- Added tasks 15-17 for implementing Ollama integration
- Updated technology stack to include httpx and Ollama
- Added error handling guidelines for Ollama integration
- Configured fallback to pattern-based detection when Ollama unavailable
This enhancement allows users to paste raw dialogue text without manual role markers.
The system will use AI to intelligently detect speakers, making the tool more user-friendly.
- Updated main README with detailed setup, Kokoro model configuration, and troubleshooting
- Enhanced backend README with API documentation, Docker setup, and testing instructions
- Improved frontend README with component details, deployment guide, and development tips
- Added workflow testing steps and common error solutions
- Documented all supported languages, voices, and configuration options
Implements task 14 from text-to-audiobook spec
Requirements: 13.1, 13.2, 13.3, 13.4, 13.5
- Applied Tailwind CSS responsive classes across all components
- Implemented mobile-first design approach with breakpoints (sm, md, lg)
- Added touch-friendly interactions with min-h-[44px] touch targets
- Enhanced App.tsx with responsive padding, headings, and alerts
- Updated TextInputSection with responsive textarea and full-width mobile button
- Improved VoiceAssignmentSection with flexible layouts and mobile-optimized controls
- Enhanced AudioPlayerSection with responsive sizing and touch support
- Added custom CSS for range slider with larger thumb for mobile
- Improved select dropdowns with visible arrows and proper padding
- Added touch-manipulation class to prevent double-tap zoom
- Added active states for better mobile feedback
- Updated index.html with proper title and meta description
- Created RESPONSIVE_IMPROVEMENTS.md documentation
Requirements: 12.1, 12.2, 12.3, 12.4
- Add complete state management for text, phases, roles, voice assignments
- Implement phase transitions: input → assignment → generated
- Wire up text input to role detection API
- Wire up voice assignment to audio generation API
- Add loading states for async operations (role detection and generation)
- Implement comprehensive error handling and display
- Add warning messages for long text (>5000 chars) in assignment and generation phases
- Ensure text persists across all workflow phases
- Validates Requirements: 1.5, 6.1, 8.1, 8.2, 8.3, 8.4
- Created VoiceAssignmentSection component with role-to-voice mapping
- Added language selector with American English, British English, French, Japanese
- Added speed slider (0.5x - 1.5x range)
- Implemented Generate Audiobook button with proper disabled state
- Integrated component into App.tsx with state management
- Added role detection API call on text submission
- Validates all roles have assigned voices before enabling generation
Requirements: 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 4.1, 4.2, 4.3, 4.4, 5.1, 5.2, 5.3
- Create TextInputSection component with large multiline textarea
- Add 'Next: Assign voices' button
- Implement text validation (non-empty)
- Show validation message for empty text
- Disable button when text is empty
- Update App.tsx to integrate TextInputSection
- Requirements: 1.1, 1.2, 1.3, 1.4
- Create TypeScript interfaces (Role, RoleWithVoice, RolesResponse, GenerateRequest)
- Implement detectRoles() function for role detection
- Implement generateAudiobook() function for audio generation
- Implement checkHealth() function for backend health checks
- Add comprehensive error handling for network failures
- Use VITE_API_BASE_URL environment variable for configuration
- Add ApiError class for structured error handling
Requirements: 9.6, 9.7
- Vite project with React and TypeScript initialized
- TypeScript configured with strict mode enabled
- Tailwind CSS set up for styling
- Component and API directory structure created
- Environment variables configured (.env with VITE_API_BASE_URL)
- Build and dev server verified working
Requirements: 9.6, 12.3
- Create Dockerfile with Python 3.10 base image
- Install system dependencies (espeak-ng) for Kokoro TTS
- Install Python dependencies from requirements.txt
- Copy backend code and expose port 8000
- Configure Uvicorn server startup
- Add docker-compose.yml for easy orchestration
- Include health checks and environment variables
- Add .dockerignore to optimize build context
Implements task 6 - Requirements 11.1-11.6
- 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 TTSService class with pipeline caching per language
- Implemented text segmentation to identify role markers (colon and bracket patterns)
- Implemented segment synthesis with voice assignment
- Implemented audio concatenation at 24 kHz sample rate
- Added fallback to default voice (af_bella) for unmapped roles
- Supports language codes: a, b, f, j
- Handles long text by chunking on sentence boundaries
- Added comprehensive unit tests (13 tests, all passing)
Requirements: 10.1, 10.3, 10.4, 6.2, 6.3, 6.4, 6.5, 6.6
- 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
