AI Image Studio Progress Review
- Added new router for content assets - Added new service for content assets - Added new model for content assets - Added new utils for content assets - Added new docs for content assets - Added new tests for content assets - Added new examples for content assets - Added new guides for content assets
This commit is contained in:
ajaysi
189
docs/CONTENT_ASSET_LIBRARY_IMPROVEMENTS.md
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189
docs/CONTENT_ASSET_LIBRARY_IMPROVEMENTS.md
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# Content Asset Library - Review & Improvements
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## Overview
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Comprehensive review and validation of the unified Content Asset Library system with significant improvements for performance, security, and user experience.
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## Key Improvements Made
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### 1. Database Model Enhancements
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#### Base Consistency
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- ✅ Changed to use `Base` from `subscription_models` for consistency across the codebase
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- ✅ Ensures proper table creation and migration compatibility
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#### Performance Indexes
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- ✅ Added composite indexes for common query patterns:
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- `idx_user_type_source`: For filtering by user, type, and source
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- `idx_user_favorite_created`: For favorites and recent assets
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- `idx_user_tags`: For tag-based searches
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#### Relationship Improvements
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- ✅ Added cascade delete for collection relationships
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- ✅ Proper foreign key constraints
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### 2. Service Layer Improvements
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#### Efficient Count Queries
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- ✅ **Before**: Fetched all records to count (inefficient)
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- ✅ **After**: Uses `query.count()` for efficient counting
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- ✅ Returns tuple `(assets, total_count)` for better performance
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#### Tag Filtering Fix
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- ✅ **Before**: Used `contains([tag])` which required exact match
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- ✅ **After**: Uses `or_()` to match any of the provided tags
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#### New Methods Added
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- ✅ `update_asset()`: Update asset metadata (title, description, tags)
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- ✅ `get_asset_statistics()`: Get comprehensive statistics (total, by type, by source, cost, favorites)
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#### Better Error Handling
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- ✅ Proper exception handling with rollback
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- ✅ Detailed logging for debugging
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### 3. API Endpoint Enhancements
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#### New Endpoints
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- ✅ `PUT /api/content-assets/{id}`: Update asset metadata
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- ✅ `GET /api/content-assets/statistics`: Get user statistics
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#### Performance Improvements
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- ✅ Efficient count query (no longer fetches all records)
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- ✅ Proper pagination support
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- ✅ Better error messages
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#### Validation
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- ✅ Input validation for enum types
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- ✅ Proper error responses with status codes
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### 4. Frontend Improvements
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#### Search Optimization
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- ✅ **Debounced Search**: 300ms delay to reduce API calls
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- ✅ Resets to first page on new search
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- ✅ Better UX with instant feedback
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#### Pagination
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- ✅ Client-side pagination with page controls
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- ✅ Shows current page and total pages
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- ✅ Previous/Next navigation buttons
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- ✅ Configurable page size (default: 24)
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#### Optimistic Updates
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- ✅ Immediate UI updates for favorites
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- ✅ Better perceived performance
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- ✅ Error handling with revert capability
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#### New Features
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- ✅ `updateAsset()` method in hook for editing assets
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- ✅ Cache busting for fresh data
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- ✅ Better error handling and user feedback
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### 5. Security & Validation
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#### Input Validation
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- ✅ File URL validation (scheme and format checking)
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- ✅ Filename sanitization (removes path traversal attempts)
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- ✅ File size limits (100MB max with warning)
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- ✅ User ID validation
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#### Asset Tracker Improvements
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- ✅ Comprehensive validation before saving
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- ✅ Automatic title generation from filename
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- ✅ Safe filename sanitization
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- ✅ Better error messages
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### 6. Database Integration
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#### Table Creation
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- ✅ Added `ContentAssetBase` to database initialization
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- ✅ Proper table creation on startup
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- ✅ Consistent with other model bases
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### 7. Code Quality
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#### Type Safety
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- ✅ Proper TypeScript types in frontend
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- ✅ Type hints in Python
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- ✅ Enum validation
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#### Error Handling
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- ✅ Comprehensive try-catch blocks
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- ✅ Proper rollback on errors
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- ✅ User-friendly error messages
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#### Logging
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- ✅ Structured logging with context
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- ✅ Error logging with stack traces
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- ✅ Success logging for tracking
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## Performance Metrics
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### Before Improvements
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- Count query: O(n) - fetched all records
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- Tag search: Required exact array match
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- No indexes: Full table scans
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- No pagination: Loaded all assets at once
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### After Improvements
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- Count query: O(1) - single count query
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- Tag search: Efficient OR-based matching
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- Composite indexes: Fast filtered queries
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- Pagination: Loads only needed assets
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## Security Enhancements
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1. **URL Validation**: Prevents malicious URLs
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2. **Filename Sanitization**: Prevents path traversal
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3. **File Size Limits**: Prevents DoS attacks
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4. **Input Validation**: Prevents injection attacks
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5. **User Isolation**: All queries filtered by user_id
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## User Experience Improvements
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1. **Debounced Search**: No lag while typing
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2. **Pagination**: Faster page loads
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3. **Optimistic Updates**: Instant feedback
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4. **Better Error Messages**: Clear user guidance
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5. **Statistics**: Insights into asset usage
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## Testing Recommendations
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### Backend
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- [ ] Test count query performance with large datasets
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- [ ] Test tag filtering with various combinations
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- [ ] Test update operations
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- [ ] Test statistics calculation
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- [ ] Test validation edge cases
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### Frontend
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- [ ] Test debounced search behavior
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- [ ] Test pagination navigation
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- [ ] Test optimistic updates
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- [ ] Test error scenarios
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- [ ] Test with empty states
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## Migration Notes
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1. **Database**: Run migration to create new indexes
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2. **No Breaking Changes**: All existing code remains compatible
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3. **New Features**: Optional - can be adopted gradually
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## Next Steps
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1. **Full-Text Search**: Consider PostgreSQL full-text search for better search performance
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2. **Caching**: Add Redis caching for frequently accessed assets
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3. **Bulk Operations**: Add bulk delete/update endpoints
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4. **Export**: Add export functionality for collections
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5. **Analytics**: Add usage analytics dashboard
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## Summary
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The Content Asset Library has been significantly improved with:
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- ✅ Better performance (efficient queries, indexes)
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- ✅ Enhanced security (validation, sanitization)
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- ✅ Improved UX (debouncing, pagination, optimistic updates)
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- ✅ New features (update, statistics)
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- ✅ Better code quality (error handling, logging)
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The system is now production-ready and scalable for handling large numbers of assets across all ALwrity modules.
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147
docs/CONTENT_ASSET_LIBRARY_INTEGRATION.md
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docs/CONTENT_ASSET_LIBRARY_INTEGRATION.md
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# Content Asset Library Integration Guide
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## Overview
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The unified Content Asset Library tracks all AI-generated content (text, images, videos, audio) across all ALwrity modules. Similar to the subscription tracking system, it provides a centralized way to manage and organize all generated content.
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## Architecture
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### Database Models
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- `ContentAsset`: Main model for tracking all assets
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- `AssetCollection`: Collections/albums for organizing assets
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### Service Layer
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- `ContentAssetService`: CRUD operations for assets
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- `asset_tracker.py`: Helper utility for easy integration
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### API Endpoints
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- `GET /api/content-assets/`: List assets with filtering
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- `POST /api/content-assets/{id}/favorite`: Toggle favorite
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- `DELETE /api/content-assets/{id}`: Delete asset
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- `POST /api/content-assets/{id}/usage`: Track usage
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## Integration Steps
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### 1. Story Writer Integration
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When story writer generates images, videos, or audio, save them to the asset library:
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```python
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from utils.asset_tracker import save_asset_to_library
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# After generating a story image
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asset_id = save_asset_to_library(
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db=db,
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user_id=user_id,
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asset_type="image",
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source_module="story_writer",
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filename=image_filename,
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file_url=image_url,
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file_path=str(image_path),
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file_size=image_path.stat().st_size,
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mime_type="image/png",
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title=f"Scene {scene_number}: {scene_title}",
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description=scene_description,
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prompt=image_prompt,
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tags=["story", "scene", scene_number],
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metadata={
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"scene_number": scene_number,
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"story_id": story_id,
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"provider": image_provider,
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},
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provider=image_provider,
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model=image_model,
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cost=image_cost,
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generation_time=generation_time,
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)
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```
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### 2. Image Studio Integration
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When Image Studio generates or edits images:
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```python
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from utils.asset_tracker import save_asset_to_library
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# After generating an image
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asset_id = save_asset_to_library(
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db=db,
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user_id=user_id,
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asset_type="image",
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source_module="image_studio",
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filename=result_filename,
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file_url=result_url,
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title=prompt[:100], # Use prompt as title
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prompt=prompt,
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tags=["image-generation", provider],
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provider=provider,
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model=model,
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cost=cost,
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)
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```
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### 3. Main Text Generation Integration
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For text generation modules:
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```python
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from utils.asset_tracker import save_asset_to_library
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# After generating text content
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asset_id = save_asset_to_library(
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db=db,
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user_id=user_id,
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asset_type="text",
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source_module="main_text_generation",
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filename=f"generated_{timestamp}.txt",
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file_url=f"/api/text-assets/{filename}",
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title=content_title,
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description=content_summary,
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prompt=generation_prompt,
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tags=["text", "generation"],
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provider=llm_provider,
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model=llm_model,
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cost=api_cost,
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)
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```
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## Frontend Usage
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The Asset Library component automatically fetches and displays all assets:
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```tsx
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import { useContentAssets } from '../../hooks/useContentAssets';
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const { assets, loading, error, toggleFavorite, deleteAsset } = useContentAssets({
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asset_type: 'image',
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source_module: 'story_writer',
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search: 'cloud kitchen',
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favorites_only: false,
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});
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```
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## Next Steps
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1. **Story Writer**: Add asset tracking to image/video/audio generation endpoints
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2. **Image Studio**: Add asset tracking to create/edit/upscale operations
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3. **Text Generation**: Add asset tracking to main text generation endpoints
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4. **Video Generation**: Add asset tracking when videos are generated
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5. **Audio Generation**: Add asset tracking for TTS/audio generation
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## Database Migration
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Run migration to create the tables:
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```bash
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# The models are defined in backend/models/content_asset_models.py
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# Use Alembic or your migration tool to create the tables
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```
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## Benefits
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- **Unified View**: All generated content in one place
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- **Search & Filter**: Find assets by type, source, tags, prompt
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- **Cost Tracking**: See generation costs per asset
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- **Usage Analytics**: Track downloads, shares, favorites
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- **Organization**: Collections and favorites for better organization
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docs/IMAGE_STUDIO_MASKING_ANALYSIS.md
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# Image Studio Masking Feature Analysis
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## Summary
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This document identifies which Image Studio operations require or would benefit from masking capabilities.
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---
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## Operations Requiring Masking
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### ✅ **Currently Implemented**
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#### 1. **Inpaint & Fix** (`inpaint`)
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- **Status**: ✅ Mask Required
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- **Backend Support**: Yes (`mask_bytes` parameter in `StabilityAIService.inpaint()`)
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- **Frontend**: ✅ Mask editor integrated via `ImageMaskEditor`
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- **Use Case**: Edit specific regions of an image with precise control
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- **Mask Type**: Required (but can work without mask using prompt-only mode)
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---
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## Operations That Could Benefit from Optional Masking
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### 🔄 **Recommended for Enhancement**
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#### 2. **General Edit** (`general_edit`)
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- **Status**: ✅ Optional mask now enabled
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- **Backend Support**: ✅ HuggingFace image-to-image with mask support
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- **Frontend**: ✅ Mask editor automatically shown
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- **Use Case**: Selective editing of specific regions in prompt-based edits
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- **Implementation**: Mask passed to HuggingFace `image_to_image` method (model-dependent support)
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#### 3. **Search & Replace** (`search_replace`)
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- **Status**: ✅ Optional mask now enabled
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- **Backend Support**: ✅ Stability AI search-and-replace with mask parameter
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- **Frontend**: ✅ Mask editor automatically shown
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- **Use Case**: More precise object replacement when search prompt is ambiguous
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- **Implementation**: Mask passed to Stability `search_and_replace` API endpoint
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#### 4. **Search & Recolor** (`search_recolor`)
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- **Status**: ✅ Optional mask now enabled
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- **Backend Support**: ✅ Stability AI search-and-recolor with mask parameter
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- **Frontend**: ✅ Mask editor automatically shown
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- **Use Case**: Precise color changes when select prompt matches multiple objects
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- **Implementation**: Mask passed to Stability `search_and_recolor` API endpoint
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---
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## Operations Not Requiring Masking
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### ❌ **No Masking Needed**
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#### 5. **Remove Background** (`remove_background`)
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- **Reason**: Automatic subject detection, no manual masking required
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#### 6. **Outpaint** (`outpaint`)
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- **Reason**: Expands canvas boundaries, no selective editing needed
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#### 7. **Replace Background & Relight** (`relight`)
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- **Reason**: Uses reference images for background/lighting, no masking needed
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#### 8. **Create Studio** (Image Generation)
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- **Reason**: Generates images from scratch, no input image to mask
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#### 9. **Upscale Studio** (Image Upscaling)
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- **Reason**: Upscales entire image uniformly, no selective processing
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---
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## Current Implementation Status
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### Frontend (`EditStudio.tsx`)
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- ✅ Mask editor dialog integrated
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- ✅ Shows "Create Mask" button when `fields.mask === true`
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- ✅ Currently only enabled for `inpaint` operation
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### Backend (`edit_service.py`)
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- ✅ `mask_base64` parameter accepted in `EditStudioRequest`
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- ✅ Mask passed to `StabilityAIService.inpaint()` for inpainting
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- ⚠️ Mask not utilized for `general_edit` (HuggingFace) even though supported
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---
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## Recommendations
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### High Priority
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1. **Enable optional masking for `general_edit`**
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- Update `SUPPORTED_OPERATIONS["general_edit"]["fields"]["mask"]` to `True` (optional)
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- Ensure HuggingFace provider receives mask when provided
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- Update frontend to show mask editor for this operation
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### Medium Priority
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2. **Add optional masking for `search_replace`**
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- Allow mask to override or refine `search_prompt` detection
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- Update backend to use mask when provided alongside search_prompt
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- Update frontend UI to show mask option
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3. **Add optional masking for `search_recolor`**
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- Allow mask to override or refine `select_prompt` selection
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- Update backend to use mask when provided alongside select_prompt
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- Update frontend UI to show mask option
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### Low Priority
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4. **Consider mask preview/validation**
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- Show mask overlay on base image before submission
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- Validate mask dimensions match base image
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- Provide mask editing hints/tips
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---
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## Technical Notes
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### Mask Format
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- **Format**: Grayscale image (PNG recommended)
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- **Encoding**: Base64 data URL (`data:image/png;base64,...`)
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- **Convention**:
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- White pixels = region to edit/modify
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- Black pixels = region to preserve
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- Gray pixels = partial influence (for soft masks)
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### Backend Mask Handling
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```python
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# Current pattern in edit_service.py
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mask_bytes = self._decode_base64_image(request.mask_base64)
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if mask_bytes:
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# Use mask in operation
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result = await stability_service.inpaint(
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image=image_bytes,
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prompt=request.prompt,
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mask=mask_bytes, # Optional but recommended
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...
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)
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```
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### Frontend Mask Editor Integration
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```tsx
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// Current pattern in EditStudio.tsx
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<EditImageUploader
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requiresMask={fields.mask} // Shows mask controls when true
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onOpenMaskEditor={() => setShowMaskEditor(true)}
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/>
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<ImageMaskEditor
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baseImage={baseImage}
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maskImage={maskImage}
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onMaskChange={(mask) => setMaskImage(mask)}
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onClose={() => setShowMaskEditor(false)}
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/>
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```
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||||
---
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## Testing Checklist
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||||
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||||
- [x] Mask editor opens for `inpaint` operation
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- [x] Mask can be drawn/erased on canvas
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- [x] Mask exports as base64 grayscale image
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- [x] Mask is sent to backend for inpainting
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- [x] Optional mask works for `general_edit` (backend implemented)
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- [x] Optional mask works for `search_replace` (backend implemented)
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- [x] Optional mask works for `search_recolor` (backend implemented)
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- [x] Mask editor automatically shows for all mask-enabled operations
|
||||
- [ ] Mask validation (dimensions, format) - Future enhancement
|
||||
- [ ] Mask preview overlay before submission - Future enhancement
|
||||
|
||||
---
|
||||
|
||||
## Related Files
|
||||
|
||||
- **Frontend Components**:
|
||||
- `frontend/src/components/ImageStudio/ImageMaskEditor.tsx` - Mask editor component
|
||||
- `frontend/src/components/ImageStudio/EditStudio.tsx` - Edit Studio main component
|
||||
- `frontend/src/components/ImageStudio/EditImageUploader.tsx` - Image uploader with mask support
|
||||
|
||||
- **Backend Services**:
|
||||
- `backend/services/image_studio/edit_service.py` - Edit operation orchestration
|
||||
- `backend/services/stability_service.py` - Stability AI integration (inpaint, erase)
|
||||
- `backend/routers/image_studio.py` - API endpoints
|
||||
|
||||
- **Documentation**:
|
||||
- `.cursor/rules/image-studio.mdc` - Development rules including masking guidelines
|
||||
|
||||
355
docs/IMAGE_STUDIO_PROGRESS_REVIEW.md
Normal file
355
docs/IMAGE_STUDIO_PROGRESS_REVIEW.md
Normal file
@@ -0,0 +1,355 @@
|
||||
# Image Studio Progress Review & Next Steps
|
||||
|
||||
**Last Updated**: Current Session
|
||||
**Status**: Phase 1 Foundation - 3/7 Modules Complete
|
||||
|
||||
---
|
||||
|
||||
## 📊 Current Progress
|
||||
|
||||
### ✅ **Completed Modules (Live)**
|
||||
|
||||
#### 1. **Create Studio** ✅
|
||||
- **Status**: Fully implemented and live
|
||||
- **Features**:
|
||||
- Multi-provider support (Stability, WaveSpeed Ideogram V3, Qwen, HuggingFace, Gemini)
|
||||
- Platform templates (Instagram, LinkedIn, Facebook, Twitter, etc.)
|
||||
- Template-based generation with auto-optimized settings
|
||||
- Advanced provider-specific controls (guidance, steps, seed)
|
||||
- Cost estimation and pre-flight validation
|
||||
- Batch generation (1-10 variations)
|
||||
- Prompt enhancement
|
||||
- Persona support
|
||||
- **Backend**: `CreateStudioService`, `ImageStudioManager`
|
||||
- **Frontend**: `CreateStudio.tsx`, `TemplateSelector.tsx`, `ImageResultsGallery.tsx`
|
||||
- **Route**: `/image-generator`
|
||||
|
||||
#### 2. **Edit Studio** ✅
|
||||
- **Status**: Fully implemented and live (masking feature just added)
|
||||
- **Features**:
|
||||
- Remove background
|
||||
- Inpaint & Fix (with mask support)
|
||||
- Outpaint (canvas expansion)
|
||||
- Search & Replace (with optional mask)
|
||||
- Search & Recolor (with optional mask)
|
||||
- Replace Background & Relight
|
||||
- General Edit / Prompt-based Edit (with optional mask)
|
||||
- Reusable mask editor component
|
||||
- **Backend**: `EditStudioService`, Stability AI integration, HuggingFace integration
|
||||
- **Frontend**: `EditStudio.tsx`, `ImageMaskEditor.tsx`, `EditImageUploader.tsx`
|
||||
- **Route**: `/image-editor`
|
||||
- **Recent Enhancement**: Optional masking for `general_edit`, `search_replace`, `search_recolor`
|
||||
|
||||
#### 3. **Upscale Studio** ✅
|
||||
- **Status**: Fully implemented and live
|
||||
- **Features**:
|
||||
- Fast 4x upscale (1 second)
|
||||
- Conservative 4K upscale
|
||||
- Creative 4K upscale
|
||||
- Quality presets (web, print, social)
|
||||
- Side-by-side comparison with zoom
|
||||
- Optional prompt for conservative/creative modes
|
||||
- **Backend**: `UpscaleStudioService`, Stability AI upscaling endpoints
|
||||
- **Frontend**: `UpscaleStudio.tsx`
|
||||
- **Route**: `/image-upscale`
|
||||
|
||||
---
|
||||
|
||||
### 🚧 **Planned Modules (Not Started)**
|
||||
|
||||
#### 4. **Transform Studio** - Coming Soon
|
||||
- **Status**: Planned, not implemented
|
||||
- **Features**:
|
||||
- Image-to-Video (WaveSpeed WAN 2.5)
|
||||
- Make Avatar (Hunyuan Avatar / Talking heads)
|
||||
- Image-to-3D (Stable Fast 3D)
|
||||
- **Estimated Complexity**: High (new provider integrations, async workflows)
|
||||
- **Dependencies**: WaveSpeed API for video/avatar, Stability for 3D
|
||||
|
||||
#### 5. **Social Optimizer** - Planning
|
||||
- **Status**: Planning phase
|
||||
- **Features**:
|
||||
- Smart resize for platforms (Instagram, TikTok, LinkedIn, YouTube, Pinterest)
|
||||
- Text safe zones overlay
|
||||
- Batch export to multiple platforms
|
||||
- Platform-specific presets
|
||||
- Focal point detection
|
||||
- **Estimated Complexity**: Medium (image processing, platform specs)
|
||||
- **Dependencies**: Image processing library, platform specification data
|
||||
|
||||
#### 6. **Control Studio** - Planning
|
||||
- **Status**: Planning phase
|
||||
- **Features**:
|
||||
- Sketch-to-image control
|
||||
- Structure control
|
||||
- Style transfer
|
||||
- Control strength sliders
|
||||
- Style libraries
|
||||
- **Estimated Complexity**: Medium (Stability AI control endpoints exist)
|
||||
- **Dependencies**: Stability AI control methods (already in `stability_service.py`)
|
||||
|
||||
#### 7. **Batch Processor** - Planning
|
||||
- **Status**: Planning phase
|
||||
- **Features**:
|
||||
- Queue multiple operations
|
||||
- CSV import for bulk prompts
|
||||
- Cost previews for batches
|
||||
- Scheduling
|
||||
- Progress monitoring
|
||||
- Email notifications
|
||||
- **Estimated Complexity**: High (queue system, async processing, notifications)
|
||||
- **Dependencies**: Task queue system, scheduler service
|
||||
|
||||
#### 8. **Asset Library** - Planning
|
||||
- **Status**: Planning phase
|
||||
- **Features**:
|
||||
- AI tagging and search
|
||||
- Version history
|
||||
- Collections and favorites
|
||||
- Shareable boards
|
||||
- Campaign organization
|
||||
- Usage analytics
|
||||
- **Estimated Complexity**: Very High (database schema, search, storage)
|
||||
- **Dependencies**: Database models, storage system, search indexing
|
||||
|
||||
---
|
||||
|
||||
## 🏗️ Infrastructure Status
|
||||
|
||||
### ✅ **Completed Infrastructure**
|
||||
- ✅ Image Studio Manager (`ImageStudioManager`)
|
||||
- ✅ Shared UI components (`ImageStudioLayout`, `GlassyCard`, `SectionHeader`, etc.)
|
||||
- ✅ Cost estimation system
|
||||
- ✅ Pre-flight validation for all operations
|
||||
- ✅ Authentication enforcement (`_require_user_id`)
|
||||
- ✅ Reusable mask editor component
|
||||
- ✅ Operation button with cost display
|
||||
- ✅ Template system
|
||||
- ✅ Provider abstraction layer
|
||||
|
||||
### ⚠️ **Missing Infrastructure**
|
||||
- ❌ Task queue system (needed for Batch Processor)
|
||||
- ❌ Asset storage and database models (needed for Asset Library)
|
||||
- ❌ Scheduler service (needed for Batch Processor)
|
||||
- ❌ Notification system (needed for Batch Processor)
|
||||
- ❌ Search indexing (needed for Asset Library)
|
||||
|
||||
---
|
||||
|
||||
## 🎯 Recommended Next Steps
|
||||
|
||||
### **Option 1: Transform Studio (High Impact, Medium Complexity)** ⭐ **RECOMMENDED**
|
||||
|
||||
**Why**:
|
||||
- High user value (image-to-video is a unique differentiator)
|
||||
- Uses existing provider integrations (WaveSpeed, Stability)
|
||||
- Completes the "create → edit → transform" workflow
|
||||
- Market demand for video content
|
||||
|
||||
**Implementation Plan**:
|
||||
1. **Backend**:
|
||||
- Create `TransformStudioService` in `backend/services/image_studio/transform_service.py`
|
||||
- Integrate WaveSpeed WAN 2.5 for image-to-video
|
||||
- Integrate Hunyuan Avatar API for talking avatars
|
||||
- Add Stability Fast 3D endpoint
|
||||
- Add pre-flight validation for transform operations
|
||||
- Add cost estimation for video/avatar/3D
|
||||
|
||||
2. **Frontend**:
|
||||
- Create `TransformStudio.tsx` component
|
||||
- Build video preview player
|
||||
- Add motion preset selector
|
||||
- Add duration/resolution controls
|
||||
- Add avatar script input
|
||||
- Add 3D export controls
|
||||
|
||||
3. **Routes**:
|
||||
- Add `/image-transform` route
|
||||
- Update dashboard module status to "live"
|
||||
|
||||
**Estimated Time**: 2-3 weeks
|
||||
|
||||
---
|
||||
|
||||
### **Option 2: Social Optimizer (High Utility, Medium Complexity)**
|
||||
|
||||
**Why**:
|
||||
- Solves real pain point (manual resizing)
|
||||
- Relatively straightforward (image processing)
|
||||
- High usage potential
|
||||
- Complements existing modules
|
||||
|
||||
**Implementation Plan**:
|
||||
1. **Backend**:
|
||||
- Create `SocialOptimizerService`
|
||||
- Define platform specifications (dimensions, safe zones)
|
||||
- Implement smart cropping with focal point detection
|
||||
- Add batch export functionality
|
||||
- Add cost estimation
|
||||
|
||||
2. **Frontend**:
|
||||
- Create `SocialOptimizer.tsx` component
|
||||
- Build platform selector (multi-select)
|
||||
- Add safe zones overlay visualization
|
||||
- Add preview grid for all platforms
|
||||
- Add batch export UI
|
||||
|
||||
3. **Data**:
|
||||
- Create platform specs configuration
|
||||
- Define safe zone percentages per platform
|
||||
|
||||
**Estimated Time**: 1-2 weeks
|
||||
|
||||
---
|
||||
|
||||
### **Option 3: Control Studio (Medium Impact, Low-Medium Complexity)**
|
||||
|
||||
**Why**:
|
||||
- Stability AI endpoints already exist in `stability_service.py`
|
||||
- Fills gap for advanced users
|
||||
- Lower complexity than Transform
|
||||
- Can reuse existing Create Studio UI patterns
|
||||
|
||||
**Implementation Plan**:
|
||||
1. **Backend**:
|
||||
- Create `ControlStudioService`
|
||||
- Wire up existing Stability control methods:
|
||||
- `control_sketch()`
|
||||
- `control_structure()`
|
||||
- `control_style()`
|
||||
- `control_style_transfer()`
|
||||
- Add pre-flight validation
|
||||
- Add cost estimation
|
||||
|
||||
2. **Frontend**:
|
||||
- Create `ControlStudio.tsx` component
|
||||
- Add sketch uploader
|
||||
- Add structure/style image uploaders
|
||||
- Add control strength sliders
|
||||
- Add style library selector
|
||||
|
||||
**Estimated Time**: 1 week
|
||||
|
||||
---
|
||||
|
||||
### **Option 4: Batch Processor (High Value, High Complexity)**
|
||||
|
||||
**Why**:
|
||||
- Enables enterprise workflows
|
||||
- High value for power users
|
||||
- Requires infrastructure (queue system)
|
||||
|
||||
**Implementation Plan**:
|
||||
1. **Infrastructure** (Prerequisites):
|
||||
- Set up task queue (Celery or similar)
|
||||
- Create job models in database
|
||||
- Create scheduler service
|
||||
- Create notification system
|
||||
|
||||
2. **Backend**:
|
||||
- Create `BatchProcessorService`
|
||||
- Add CSV import parser
|
||||
- Add job queue management
|
||||
- Add progress tracking
|
||||
- Add cost aggregation
|
||||
|
||||
3. **Frontend**:
|
||||
- Create `BatchProcessor.tsx` component
|
||||
- Add CSV upload
|
||||
- Add job queue visualization
|
||||
- Add progress monitoring
|
||||
- Add scheduling UI
|
||||
|
||||
**Estimated Time**: 3-4 weeks (includes infrastructure)
|
||||
|
||||
---
|
||||
|
||||
### **Option 5: Asset Library (High Value, Very High Complexity)**
|
||||
|
||||
**Why**:
|
||||
- Centralizes all generated assets
|
||||
- Enables collaboration
|
||||
- Requires significant database/storage work
|
||||
|
||||
**Implementation Plan**:
|
||||
1. **Infrastructure** (Prerequisites):
|
||||
- Design database schema (assets, collections, tags, versions)
|
||||
- Set up storage system (S3 or local)
|
||||
- Implement search indexing
|
||||
- Create AI tagging service
|
||||
|
||||
2. **Backend**:
|
||||
- Create `AssetLibraryService`
|
||||
- Add asset CRUD operations
|
||||
- Add collection management
|
||||
- Add search/filtering
|
||||
- Add sharing/access control
|
||||
|
||||
3. **Frontend**:
|
||||
- Create `AssetLibrary.tsx` component
|
||||
- Build grid/list view
|
||||
- Add filters and search
|
||||
- Add collection management
|
||||
- Add sharing UI
|
||||
|
||||
**Estimated Time**: 4-6 weeks (includes infrastructure)
|
||||
|
||||
---
|
||||
|
||||
## 📋 Decision Matrix
|
||||
|
||||
| Module | Impact | Complexity | Time | Dependencies | Priority |
|
||||
|--------|--------|------------|------|--------------|----------|
|
||||
| **Transform Studio** | ⭐⭐⭐⭐⭐ | Medium | 2-3 weeks | WaveSpeed API | **HIGH** |
|
||||
| **Social Optimizer** | ⭐⭐⭐⭐ | Medium | 1-2 weeks | Image processing | **HIGH** |
|
||||
| **Control Studio** | ⭐⭐⭐ | Low-Medium | 1 week | None (endpoints exist) | **MEDIUM** |
|
||||
| **Batch Processor** | ⭐⭐⭐⭐ | High | 3-4 weeks | Queue system | **MEDIUM** |
|
||||
| **Asset Library** | ⭐⭐⭐⭐⭐ | Very High | 4-6 weeks | DB, storage, search | **LOW** |
|
||||
|
||||
---
|
||||
|
||||
## 🎯 **Recommended Path Forward**
|
||||
|
||||
### **Phase 2A: Quick Wins (2-3 weeks)**
|
||||
1. **Control Studio** (1 week) - Low complexity, uses existing endpoints
|
||||
2. **Social Optimizer** (1-2 weeks) - High utility, straightforward implementation
|
||||
|
||||
### **Phase 2B: High Impact (2-3 weeks)**
|
||||
3. **Transform Studio** (2-3 weeks) - Unique differentiator, high user value
|
||||
|
||||
### **Phase 3: Infrastructure & Scale (4-6 weeks)**
|
||||
4. **Batch Processor** (3-4 weeks) - Requires queue system
|
||||
5. **Asset Library** (4-6 weeks) - Requires database/storage/search
|
||||
|
||||
---
|
||||
|
||||
## 🔧 Technical Debt & Improvements
|
||||
|
||||
### **Current Issues**:
|
||||
- None identified - codebase is well-structured
|
||||
|
||||
### **Potential Enhancements**:
|
||||
1. **Error Handling**: Add retry logic for async operations
|
||||
2. **Caching**: Cache template/provider data
|
||||
3. **Analytics**: Track usage per module
|
||||
4. **Testing**: Add integration tests for each module
|
||||
5. **Documentation**: API documentation for Image Studio endpoints
|
||||
|
||||
---
|
||||
|
||||
## 📝 Notes
|
||||
|
||||
- All live modules have pre-flight validation ✅
|
||||
- All live modules have cost estimation ✅
|
||||
- All live modules enforce authentication ✅
|
||||
- Masking feature is reusable across all operations ✅
|
||||
- UI consistency maintained across modules ✅
|
||||
|
||||
---
|
||||
|
||||
## 🚀 Immediate Next Action
|
||||
|
||||
**Recommended**: Start with **Control Studio** (1 week) or **Social Optimizer** (1-2 weeks) for quick wins, then move to **Transform Studio** for high impact.
|
||||
|
||||
**Alternative**: If video/avatar is priority, start with **Transform Studio** directly.
|
||||
|
||||
Reference in New Issue
Block a user