Big Christmas update
WE GOT METRICS and real time adjustments
V2.2
-
VTube Studio Integration Improvements
- Added robust error handling for VTube Studio connection failures
- Implemented graceful fallback when VTube Studio is not running
- Added connection state management and automatic reconnection
- Enhanced emotion-to-expression mapping system
- Improved performance with lazy initialization
- Added connection attempt limiting to prevent resource drain
-
Performance Optimizations
- Implemented lazy loading for resource-heavy integrations
- Added connection pooling for better resource management
- Enhanced error isolation to prevent cascading failures
- Improved logging system with better error categorization
- Added resource usage monitoring and cleanup
-
Stability Enhancements
- Added system-wide error boundary implementation
- Improved module initialization sequence
- Enhanced cross-module communication reliability
- Added automatic recovery mechanisms for common failure modes
- Implemented better state management across integrations
-
Added comprehensive logging system:
- Added
track_response_time
decorator for performance monitoring - Added
log_startup()
function for application initialization logging - Added file-based logging with automatic log directory creation
- Added structured logging with timestamp and log levels
- Added global debug, RAG, and temperature logging capabilities
- Added
-
Improved configuration system:
- Added dataclass-based configuration
- Added support for hot-reloading configuration
- Added JSON-based config persistence
- Separated RP Suppression and Newline Cut controls
- Added independent UI toggles for RP Suppression and Newline Cut
- Added environment variable support for default settings
- Improved stopping strings organization with categorical structure
- Added message length validation with debug logging
- Optimized RP Suppression threshold for better accuracy
V2.1
-
Performance Metrics Tracking
- Implemented a comprehensive performance metrics tracking system to monitor the application's efficiency and responsiveness.
- Added logging for key performance indicators, including response times and resource usage.
- Introduced a real-time performance metrics dashboard with:
- Response time tracking and analysis
- CPU and memory usage monitoring
- Automatic performance data logging
- Resource usage history tracking
- Enhanced the overall user experience by ensuring smoother interactions and quicker response times.
- Added function-level performance tracking using decorators
- Implemented automatic cleanup of old performance data
- Added system resource monitoring with alerts for high usage
-
Emotion Recognition Enhancements
- Improved accuracy by refining the model and incorporating new training data.
- Enhanced the emotional response system to better reflect detected emotions in interactions.
-
Dynamic Personality Adjustments
- Introduced algorithms for adjusting personality based on user feedback and interaction history.
- Improved adaptability of AI responses to better match user preferences and emotional states.