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…nd performance - Add modular architecture with organized folder structure - Implement custom hooks (useAutoencoder, useErrorHandler) - Add centralized configuration and utilities - Optimize performance with lazy loading, throttling, and memory management - Add comprehensive error handling with ErrorBoundary - Improve accessibility with ARIA attributes and semantic HTML - Optimize build configuration with code splitting and minification - Add ESLint configuration and code quality tools - Enhance CI/CD pipeline with quality gates - Improve SEO with meta tags and structured HTML
- Fix gap between spinner disappearing and app being ready - Spinner now shows until both loading is complete AND app is ready - Remove opacity transition dependency on isAppReady state - Ensure smooth loading experience without blank screen
- Add robust backend initialization with fallback options (webgl -> webgpu -> cpu) - Improve loading spinner synchronization with actual ML model readiness - Add comprehensive logging for debugging initialization issues - Wait for successful first letter generation before hiding spinner - Add favicon.svg to resolve 404 error - Update favicon reference in index.html - Add retry mechanism for failed model initialization - Enhance error handling with detailed TensorFlow.js backend information
… issue - Remove StrictMode to prevent double execution - Add resourcesLoaded flag to prevent duplicate resource loading - Simplify initialization logic for debugging - Add extensive logging to track initialization process
- Split app initialization and first letter generation into separate effects - App now shows immediately when resources are loaded - First letter generation happens asynchronously after app is ready - Prevents infinite loading spinner by decoupling UI readiness from letter generation - Add comprehensive logging for debugging - Remove dependency on letter generation success for app initialization
- Re-enable React.StrictMode for production - Remove excessive logging while keeping essential error logs - Optimize resource loading with Promise.all for parallel execution - Simplify console output for better user experience - Maintain robust error handling without verbose debugging - Ready for production deployment
- Remove duplicate favicon.ico, keep only favicon.svg - Reduce console logging to only essential error messages - Use useRef for resourcesLoaded to prevent double execution in StrictMode - Remove verbose initialization messages - Keep only warning for TensorFlow.js backend fallbacks - Cleaner console output for production use
- Change input type from 'number' to 'text' to allow decimal and negative input - Add local state management in ControlPanel for coordinate inputs - Implement onBlur and onKeyPress (Enter) validation - Allow users to type partial values like '-' or '1.' without immediate validation - Add placeholder text showing valid range for each coordinate - Add tooltips with precise min/max values - Simplify handleCoordInputChange in useAutoencoder hook - Ensure values are clamped within latent space bounds - Better UX for manual coordinate entry
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