🔊 Add nudge audio caching to reduce TTS calls #84
Description
Summary
Implement intelligent audio caching for nudges to reduce Text-to-Speech API calls, improve response times, and optimize resource usage.
Benefits
- Faster nudge delivery: Pre-generated audio eliminates TTS generation delay
- Reduced API costs: Fewer calls to TTS services (Google Cloud TTS, etc.)
- Offline capability: Cached audio works during internet disruptions
- Consistent quality: Same audio quality for repeated nudges
- Resource efficiency: Lower CPU and network usage
Caching Strategy
Cache Categories
- Static nudges: Common reminders that don't change ("Time for a break!")
- Template nudges: Parameterized content with variable substitution
- Personalized nudges: User-specific content with moderate reuse
- Dynamic nudges: Highly contextual, single-use content
Cache Management
- Intelligent pre-generation: Create audio for common nudges at startup
- Usage-based caching: Cache frequently used nudge patterns
- LRU eviction: Remove least recently used audio files
- Size limits: Configurable cache size with automatic cleanup
- Expiration: Time-based expiration for personalized content
Technical Implementation
Cache Storage
- Local filesystem cache with organized directory structure
- Audio format optimization (MP3, Opus, AAC comparison)
- Metadata storage for cache management (SQLite or JSON)
- Checksum verification for cache integrity
Cache Key Generation
- Content-based hashing for static nudges
- Template + parameter hashing for dynamic content
- Voice/personality parameter inclusion
- User-specific cache partitioning
TTS Integration
- Fallback to real-time TTS for cache misses
- Background cache warming for predicted nudges
- Multi-voice support with separate cache partitions
- Quality settings optimization for cache vs real-time
Smart Features
Predictive Caching
- Analyze user patterns to predict likely nudges
- Pre-generate audio for upcoming scheduled nudges
- Calendar integration for event-specific nudge preparation
- Task-based nudge prediction and preparation
Dynamic Content Handling
- Template-based audio generation with parameter substitution
- Voice modulation for slight variations without full regeneration
- Partial caching for common nudge components
Performance Optimization
- Asynchronous cache warming
- Parallel audio generation for batch operations
- Compressed audio storage with quality balance
- Memory caching for frequently accessed audio
Configuration Options
- Cache size limits (disk space and file count)
- Audio quality settings (bitrate, format)
- Cache warming strategies (startup, background, on-demand)
- Expiration policies per nudge type
- Voice and personality cache partitioning
Files to Implement/Modify
- Audio cache management module
- TTS integration layer
- Nudge generation and delivery system
- Configuration and settings management
- Cache monitoring and cleanup utilities
Acceptance Criteria
- Common nudges are served from cache without TTS calls
- Cache warming happens efficiently in background
- Cache size stays within configured limits
- Audio quality is maintained across cache and real-time generation
- Fallback to real-time TTS works seamlessly
- Performance improvement is measurable (response time, API usage)
- Cache management is automated and requires no manual intervention
- Configuration options allow customization for different setups
Metrics to Track
- Cache hit/miss ratios
- TTS API call reduction percentage
- Average nudge delivery time improvement
- Cache storage utilization
- Background processing impact on system performance
Related to
- Main nudge system issue 🔔 Implement Google Nest nudge system for ADHD support #74
- TTS integration and device discovery
- Performance optimization initiatives
Priority
Medium - Performance and cost optimization feature