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Kunthawat Greethong
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# Content Asset Library Integration Guide
## Overview
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.
## Architecture
### Database Models
- `ContentAsset`: Main model for tracking all assets
- `AssetCollection`: Collections/albums for organizing assets
### Service Layer
- `ContentAssetService`: CRUD operations for assets
- `asset_tracker.py`: Helper utility for easy integration
### API Endpoints
- `GET /api/content-assets/`: List assets with filtering
- `POST /api/content-assets/{id}/favorite`: Toggle favorite
- `DELETE /api/content-assets/{id}`: Delete asset
- `POST /api/content-assets/{id}/usage`: Track usage
## Integration Steps
### 1. Story Writer Integration
When story writer generates images, videos, or audio, save them to the asset library:
```python
from utils.asset_tracker import save_asset_to_library
# After generating a story image
asset_id = save_asset_to_library(
db=db,
user_id=user_id,
asset_type="image",
source_module="story_writer",
filename=image_filename,
file_url=image_url,
file_path=str(image_path),
file_size=image_path.stat().st_size,
mime_type="image/png",
title=f"Scene {scene_number}: {scene_title}",
description=scene_description,
prompt=image_prompt,
tags=["story", "scene", scene_number],
metadata={
"scene_number": scene_number,
"story_id": story_id,
"provider": image_provider,
},
provider=image_provider,
model=image_model,
cost=image_cost,
generation_time=generation_time,
)
```
### 2. Image Studio Integration
When Image Studio generates or edits images:
```python
from utils.asset_tracker import save_asset_to_library
# After generating an image
asset_id = save_asset_to_library(
db=db,
user_id=user_id,
asset_type="image",
source_module="image_studio",
filename=result_filename,
file_url=result_url,
title=prompt[:100], # Use prompt as title
prompt=prompt,
tags=["image-generation", provider],
provider=provider,
model=model,
cost=cost,
)
```
### 3. Main Text Generation Integration
For text generation modules:
```python
from utils.asset_tracker import save_asset_to_library
# After generating text content
asset_id = save_asset_to_library(
db=db,
user_id=user_id,
asset_type="text",
source_module="main_text_generation",
filename=f"generated_{timestamp}.txt",
file_url=f"/api/text-assets/{filename}",
title=content_title,
description=content_summary,
prompt=generation_prompt,
tags=["text", "generation"],
provider=llm_provider,
model=llm_model,
cost=api_cost,
)
```
## Frontend Usage
The Asset Library component automatically fetches and displays all assets:
```tsx
import { useContentAssets } from '../../hooks/useContentAssets';
const { assets, loading, error, toggleFavorite, deleteAsset } = useContentAssets({
asset_type: 'image',
source_module: 'story_writer',
search: 'cloud kitchen',
favorites_only: false,
});
```
## Next Steps
1. **Story Writer**: Add asset tracking to image/video/audio generation endpoints
2. **Image Studio**: Add asset tracking to create/edit/upscale operations
3. **Text Generation**: Add asset tracking to main text generation endpoints
4. **Video Generation**: Add asset tracking when videos are generated
5. **Audio Generation**: Add asset tracking for TTS/audio generation
## Database Migration
Run migration to create the tables:
```bash
# The models are defined in backend/models/content_asset_models.py
# Use Alembic or your migration tool to create the tables
```
## Benefits
- **Unified View**: All generated content in one place
- **Search & Filter**: Find assets by type, source, tags, prompt
- **Cost Tracking**: See generation costs per asset
- **Usage Analytics**: Track downloads, shares, favorites
- **Organization**: Collections and favorites for better organization