Story Writer Service

Story generation service using prompt chaining approach, migrated from ToBeMigrated/ai_writers/ai_story_writer/.

Structure

backend/
├── services/
│   └── story_writer/
│       ├── __init__.py
│       ├── story_service.py      # Core story generation logic
│       └── README.md
├── api/
│   └── story_writer/
│       ├── __init__.py
│       ├── router.py              # API endpoints
│       ├── task_manager.py        # Async task management
│       └── cache_manager.py       # Result caching
└── models/
    └── story_models.py             # Pydantic models

Features

Prompt Chaining: Generates stories through premise → outline → start → continuation
Multiple Personas: Supports 11 predefined author personas/genres
Configurable Parameters:
- Story setting, characters, plot elements
- Writing style, tone, narrative POV
- Audience age group, content rating, ending preference
Subscription Integration: Automatic usage tracking via main_text_generation
Provider Support: Works with both Gemini and HuggingFace
Async Task Management: Long-running story generation with polling
Caching: Result caching for identical requests

API Endpoints

Synchronous Endpoints

POST /api/story/generate-premise - Generate story premise
POST /api/story/generate-outline - Generate outline from premise
POST /api/story/generate-start - Generate story beginning
POST /api/story/continue - Continue story generation

Asynchronous Endpoints

POST /api/story/generate-full - Generate complete story (returns task_id)
GET /api/story/task/{task_id}/status - Get task status
GET /api/story/task/{task_id}/result - Get completed task result

Cache Management

GET /api/story/cache/stats - Get cache statistics
POST /api/story/cache/clear - Clear cache

Usage Example

from services.story_writer.story_service import StoryWriterService

service = StoryWriterService()

# Generate full story
result = service.generate_full_story(
    persona="Award-Winning Science Fiction Author",
    story_setting="A bustling futuristic city in 2150",
    character_input="John, a tall muscular man with a kind heart",
    plot_elements="The hero's journey, Good vs. evil",
    writing_style="Formal",
    story_tone="Suspenseful",
    narrative_pov="Third Person Limited",
    audience_age_group="Adults",
    content_rating="PG-13",
    ending_preference="Happy",
    user_id="clerk_user_id",
    max_iterations=10
)

print(result["premise"])
print(result["outline"])
print(result["story"])

Migration Notes

Updated imports from legacy ...gpt_providers.text_generation.main_text_generation to services.llm_providers.main_text_generation
Added user_id parameter to all LLM calls for subscription support
Removed Streamlit dependencies (UI moved to frontend)
Added proper error handling with HTTPException support
Added async task management for long-running operations
Added caching support for identical requests

Integration

The router is automatically registered via alwrity_utils/router_manager.py in the optional routers section.