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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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