diff --git a/backend/alwrity_utils/router_manager.py b/backend/alwrity_utils/router_manager.py
index 454bb5f6..608ffc3c 100644
--- a/backend/alwrity_utils/router_manager.py
+++ b/backend/alwrity_utils/router_manager.py
@@ -170,6 +170,13 @@ class RouterManager:
except Exception as e:
logger.warning(f"AI Blog Writer router not mounted: {e}")
+ # Story Writer router
+ try:
+ from api.story_writer.router import router as story_writer_router
+ self.include_router_safely(story_writer_router, "story_writer")
+ except Exception as e:
+ logger.warning(f"Story Writer router not mounted: {e}")
+
# Wix Integration router
try:
from api.wix_routes import router as wix_router
diff --git a/backend/api/blog_writer/router.py b/backend/api/blog_writer/router.py
index 12c6a72e..2fe8998d 100644
--- a/backend/api/blog_writer/router.py
+++ b/backend/api/blog_writer/router.py
@@ -671,4 +671,122 @@ async def rewrite_status(task_id: str):
raise
except Exception as e:
logger.error(f"Failed to get rewrite status for {task_id}: {e}")
+ raise HTTPException(status_code=500, detail=str(e))
+
+
+@router.post("/titles/generate-seo")
+async def generate_seo_titles(
+ request: Dict[str, Any],
+ current_user: Dict[str, Any] = Depends(get_current_user)
+) -> Dict[str, Any]:
+ """Generate 5 SEO-optimized blog titles using research and outline data."""
+ try:
+ # Extract Clerk user ID (required)
+ if not current_user:
+ raise HTTPException(status_code=401, detail="Authentication required")
+
+ user_id = str(current_user.get('id', ''))
+ if not user_id:
+ raise HTTPException(status_code=401, detail="Invalid user ID in authentication token")
+
+ # Import here to avoid circular dependencies
+ from services.blog_writer.outline.seo_title_generator import SEOTitleGenerator
+ from models.blog_models import BlogResearchResponse, BlogOutlineSection
+
+ # Parse request data
+ research_data = request.get('research')
+ outline_data = request.get('outline', [])
+ primary_keywords = request.get('primary_keywords', [])
+ secondary_keywords = request.get('secondary_keywords', [])
+ content_angles = request.get('content_angles', [])
+ search_intent = request.get('search_intent', 'informational')
+ word_count = request.get('word_count', 1500)
+
+ if not research_data:
+ raise HTTPException(status_code=400, detail="Research data is required")
+
+ # Convert to models
+ research = BlogResearchResponse(**research_data)
+ outline = [BlogOutlineSection(**section) for section in outline_data]
+
+ # Generate titles
+ title_generator = SEOTitleGenerator()
+ titles = await title_generator.generate_seo_titles(
+ research=research,
+ outline=outline,
+ primary_keywords=primary_keywords,
+ secondary_keywords=secondary_keywords,
+ content_angles=content_angles,
+ search_intent=search_intent,
+ word_count=word_count,
+ user_id=user_id
+ )
+
+ return {
+ "success": True,
+ "titles": titles
+ }
+ except HTTPException:
+ raise
+ except Exception as e:
+ logger.error(f"Failed to generate SEO titles: {e}")
+ raise HTTPException(status_code=500, detail=str(e))
+
+
+@router.post("/introductions/generate")
+async def generate_introductions(
+ request: Dict[str, Any],
+ current_user: Dict[str, Any] = Depends(get_current_user)
+) -> Dict[str, Any]:
+ """Generate 3 varied blog introductions using research, outline, and content."""
+ try:
+ # Extract Clerk user ID (required)
+ if not current_user:
+ raise HTTPException(status_code=401, detail="Authentication required")
+
+ user_id = str(current_user.get('id', ''))
+ if not user_id:
+ raise HTTPException(status_code=401, detail="Invalid user ID in authentication token")
+
+ # Import here to avoid circular dependencies
+ from services.blog_writer.content.introduction_generator import IntroductionGenerator
+ from models.blog_models import BlogResearchResponse, BlogOutlineSection
+
+ # Parse request data
+ blog_title = request.get('blog_title', '')
+ research_data = request.get('research')
+ outline_data = request.get('outline', [])
+ sections_content = request.get('sections_content', {})
+ primary_keywords = request.get('primary_keywords', [])
+ search_intent = request.get('search_intent', 'informational')
+
+ if not research_data:
+ raise HTTPException(status_code=400, detail="Research data is required")
+ if not blog_title:
+ raise HTTPException(status_code=400, detail="Blog title is required")
+
+ # Convert to models
+ research = BlogResearchResponse(**research_data)
+ outline = [BlogOutlineSection(**section) for section in outline_data]
+
+ # Generate introductions
+ intro_generator = IntroductionGenerator()
+ introductions = await intro_generator.generate_introductions(
+ blog_title=blog_title,
+ research=research,
+ outline=outline,
+ sections_content=sections_content,
+ primary_keywords=primary_keywords,
+ search_intent=search_intent,
+ user_id=user_id
+ )
+
+ return {
+ "success": True,
+ "introductions": introductions
+ }
+ except HTTPException:
+ raise
+ except Exception as e:
+ logger.error(f"Failed to generate introductions: {e}")
raise HTTPException(status_code=500, detail=str(e))
\ No newline at end of file
diff --git a/backend/api/scheduler_dashboard.py b/backend/api/scheduler_dashboard.py
index 967778ce..e8ff9d5f 100644
--- a/backend/api/scheduler_dashboard.py
+++ b/backend/api/scheduler_dashboard.py
@@ -1151,6 +1151,118 @@ async def retry_website_analysis(
raise HTTPException(status_code=500, detail=f"Failed to retry website analysis: {str(e)}")
+@router.get("/tasks-needing-intervention/{user_id}")
+async def get_tasks_needing_intervention(
+ user_id: str,
+ db: Session = Depends(get_db),
+ current_user: Dict[str, Any] = Depends(get_current_user)
+):
+ """
+ Get all tasks that need human intervention.
+
+ Args:
+ user_id: User ID
+
+ Returns:
+ List of tasks needing intervention with failure pattern details
+ """
+ try:
+ # Verify user access
+ if str(current_user.get('id')) != user_id:
+ raise HTTPException(status_code=403, detail="Access denied")
+
+ from services.scheduler.core.failure_detection_service import FailureDetectionService
+ detection_service = FailureDetectionService(db)
+
+ tasks = detection_service.get_tasks_needing_intervention(user_id=user_id)
+
+ return {
+ "success": True,
+ "tasks": tasks,
+ "count": len(tasks)
+ }
+ except HTTPException:
+ raise
+ except Exception as e:
+ logger.error(f"Error getting tasks needing intervention: {e}", exc_info=True)
+ raise HTTPException(status_code=500, detail=f"Failed to get tasks needing intervention: {str(e)}")
+
+
+@router.post("/tasks/{task_type}/{task_id}/manual-trigger")
+async def manual_trigger_task(
+ task_type: str,
+ task_id: int,
+ db: Session = Depends(get_db),
+ current_user: Dict[str, Any] = Depends(get_current_user)
+):
+ """
+ Manually trigger a task that is in cool-off or needs intervention.
+ This bypasses the cool-off check and executes the task immediately.
+
+ Args:
+ task_type: Task type (oauth_token_monitoring, website_analysis, gsc_insights, bing_insights)
+ task_id: Task ID
+
+ Returns:
+ Success status and execution result
+ """
+ try:
+ from services.scheduler.core.task_execution_handler import execute_task_async
+ scheduler = get_scheduler()
+
+ # Load task based on type
+ task = None
+ if task_type == "oauth_token_monitoring":
+ task = db.query(OAuthTokenMonitoringTask).filter(
+ OAuthTokenMonitoringTask.id == task_id
+ ).first()
+ elif task_type == "website_analysis":
+ task = db.query(WebsiteAnalysisTask).filter(
+ WebsiteAnalysisTask.id == task_id
+ ).first()
+ elif task_type in ["gsc_insights", "bing_insights"]:
+ task = db.query(PlatformInsightsTask).filter(
+ PlatformInsightsTask.id == task_id
+ ).first()
+ else:
+ raise HTTPException(status_code=400, detail=f"Unknown task type: {task_type}")
+
+ if not task:
+ raise HTTPException(status_code=404, detail="Task not found")
+
+ # Verify user access
+ if str(current_user.get('id')) != task.user_id:
+ raise HTTPException(status_code=403, detail="Access denied")
+
+ # Clear cool-off status and reset failure count
+ task.status = "active"
+ task.consecutive_failures = 0
+ task.failure_pattern = None
+
+ # Execute task manually (bypasses cool-off check)
+ # Task types are registered as: oauth_token_monitoring, website_analysis, gsc_insights, bing_insights
+ await execute_task_async(scheduler, task_type, task, execution_source="manual")
+
+ db.commit()
+
+ logger.info(f"Manually triggered task {task_id} ({task_type}) for user {task.user_id}")
+
+ return {
+ "success": True,
+ "message": "Task triggered successfully",
+ "task": {
+ "id": task.id,
+ "status": task.status,
+ "last_check": task.last_check.isoformat() if task.last_check else None
+ }
+ }
+ except HTTPException:
+ raise
+ except Exception as e:
+ logger.error(f"Error manually triggering task {task_id}: {e}", exc_info=True)
+ raise HTTPException(status_code=500, detail=f"Failed to trigger task: {str(e)}")
+
+
@router.get("/platform-insights/logs/{user_id}")
async def get_platform_insights_logs(
user_id: str,
diff --git a/backend/api/story_writer/__init__.py b/backend/api/story_writer/__init__.py
new file mode 100644
index 00000000..dbd75aab
--- /dev/null
+++ b/backend/api/story_writer/__init__.py
@@ -0,0 +1,9 @@
+"""
+Story Writer API
+
+API endpoints for story generation functionality.
+"""
+
+from .router import router
+
+__all__ = ['router']
diff --git a/backend/api/story_writer/cache_manager.py b/backend/api/story_writer/cache_manager.py
new file mode 100644
index 00000000..c0db5fe1
--- /dev/null
+++ b/backend/api/story_writer/cache_manager.py
@@ -0,0 +1,70 @@
+"""
+Cache Management System for Story Writer API
+
+Handles story generation cache operations.
+"""
+
+from typing import Any, Dict, Optional
+from loguru import logger
+
+
+class CacheManager:
+ """Manages cache operations for story generation data."""
+
+ def __init__(self):
+ """Initialize the cache manager."""
+ self.cache: Dict[str, Dict[str, Any]] = {}
+ logger.info("[StoryWriter] CacheManager initialized")
+
+ def get_cache_key(self, request_data: Dict[str, Any]) -> str:
+ """Generate a cache key from request data."""
+ import hashlib
+ import json
+
+ # Create a normalized version of the request for caching
+ cache_data = {
+ "persona": request_data.get("persona", ""),
+ "story_setting": request_data.get("story_setting", ""),
+ "character_input": request_data.get("character_input", ""),
+ "plot_elements": request_data.get("plot_elements", ""),
+ "writing_style": request_data.get("writing_style", ""),
+ "story_tone": request_data.get("story_tone", ""),
+ "narrative_pov": request_data.get("narrative_pov", ""),
+ "audience_age_group": request_data.get("audience_age_group", ""),
+ "content_rating": request_data.get("content_rating", ""),
+ "ending_preference": request_data.get("ending_preference", ""),
+ }
+
+ cache_str = json.dumps(cache_data, sort_keys=True)
+ return hashlib.md5(cache_str.encode()).hexdigest()
+
+ def get_cached_result(self, cache_key: str) -> Optional[Dict[str, Any]]:
+ """Get a cached result if available."""
+ if cache_key in self.cache:
+ logger.debug(f"[StoryWriter] Cache hit for key: {cache_key}")
+ return self.cache[cache_key]
+ logger.debug(f"[StoryWriter] Cache miss for key: {cache_key}")
+ return None
+
+ def cache_result(self, cache_key: str, result: Dict[str, Any]):
+ """Cache a result."""
+ self.cache[cache_key] = result
+ logger.debug(f"[StoryWriter] Cached result for key: {cache_key}")
+
+ def clear_cache(self):
+ """Clear all cached results."""
+ count = len(self.cache)
+ self.cache.clear()
+ logger.info(f"[StoryWriter] Cleared {count} cached entries")
+ return {"status": "success", "message": f"Cleared {count} cached entries"}
+
+ def get_cache_stats(self) -> Dict[str, Any]:
+ """Get cache statistics."""
+ return {
+ "total_entries": len(self.cache),
+ "cache_keys": list(self.cache.keys())
+ }
+
+
+# Global cache manager instance
+cache_manager = CacheManager()
diff --git a/backend/api/story_writer/router.py b/backend/api/story_writer/router.py
new file mode 100644
index 00000000..cabcc9f4
--- /dev/null
+++ b/backend/api/story_writer/router.py
@@ -0,0 +1,1181 @@
+"""
+Story Writer API Router
+
+Main router for story generation operations including premise, outline,
+content generation, and full story creation.
+"""
+
+from fastapi import APIRouter, HTTPException, Depends, BackgroundTasks
+from typing import Any, Dict, Union, List
+from loguru import logger
+from middleware.auth_middleware import get_current_user
+
+from models.story_models import (
+ StoryGenerationRequest,
+ StorySetupGenerationRequest,
+ StorySetupGenerationResponse,
+ StorySetupOption,
+ StoryStartRequest,
+ StoryPremiseResponse,
+ StoryOutlineResponse,
+ StoryScene,
+ StoryContentResponse,
+ StoryFullGenerationResponse,
+ StoryContinueRequest,
+ StoryContinueResponse,
+ StoryImageGenerationRequest,
+ StoryImageGenerationResponse,
+ StoryImageResult,
+ StoryAudioGenerationRequest,
+ StoryAudioGenerationResponse,
+ StoryAudioResult,
+ StoryVideoGenerationRequest,
+ StoryVideoGenerationResponse,
+ StoryVideoResult,
+ TaskStatus,
+)
+from services.story_writer.story_service import StoryWriterService
+from .task_manager import task_manager
+from .cache_manager import cache_manager
+
+
+router = APIRouter(prefix="/api/story", tags=["Story Writer"])
+
+service = StoryWriterService()
+
+
+@router.get("/health")
+async def health() -> Dict[str, Any]:
+ """Health check endpoint."""
+ return {"status": "ok", "service": "story_writer"}
+
+
+# ---------------------------
+# Story Setup Generation Endpoints
+# ---------------------------
+
+@router.post("/generate-setup", response_model=StorySetupGenerationResponse)
+async def generate_story_setup(
+ request: StorySetupGenerationRequest,
+ current_user: Dict[str, Any] = Depends(get_current_user)
+) -> StorySetupGenerationResponse:
+ """Generate 3 story setup options from a user's story idea."""
+ try:
+ if not current_user:
+ raise HTTPException(status_code=401, detail="Authentication required")
+
+ user_id = str(current_user.get('id', ''))
+ if not user_id:
+ raise HTTPException(status_code=401, detail="Invalid user ID in authentication token")
+
+ if not request.story_idea or not request.story_idea.strip():
+ raise HTTPException(status_code=400, detail="Story idea is required")
+
+ logger.info(f"[StoryWriter] Generating story setup options for user {user_id}")
+
+ options = service.generate_story_setup_options(
+ story_idea=request.story_idea,
+ user_id=user_id
+ )
+
+ # Convert dict options to StorySetupOption models
+ setup_options = [StorySetupOption(**option) for option in options]
+
+ return StorySetupGenerationResponse(options=setup_options, success=True)
+
+ except HTTPException:
+ raise
+ except Exception as e:
+ logger.error(f"[StoryWriter] Failed to generate story setup options: {e}")
+ raise HTTPException(status_code=500, detail=str(e))
+
+
+# ---------------------------
+# Premise Generation Endpoints
+# ---------------------------
+
+@router.post("/generate-premise", response_model=StoryPremiseResponse)
+async def generate_premise(
+ request: StoryGenerationRequest,
+ current_user: Dict[str, Any] = Depends(get_current_user)
+) -> StoryPremiseResponse:
+ """Generate a story premise."""
+ try:
+ if not current_user:
+ raise HTTPException(status_code=401, detail="Authentication required")
+
+ user_id = str(current_user.get('id', ''))
+ if not user_id:
+ raise HTTPException(status_code=401, detail="Invalid user ID in authentication token")
+
+ logger.info(f"[StoryWriter] Generating premise for user {user_id}")
+
+ premise = service.generate_premise(
+ persona=request.persona,
+ story_setting=request.story_setting,
+ character_input=request.character_input,
+ plot_elements=request.plot_elements,
+ writing_style=request.writing_style,
+ story_tone=request.story_tone,
+ narrative_pov=request.narrative_pov,
+ audience_age_group=request.audience_age_group,
+ content_rating=request.content_rating,
+ ending_preference=request.ending_preference,
+ user_id=user_id
+ )
+
+ return StoryPremiseResponse(premise=premise, success=True)
+
+ except HTTPException:
+ raise
+ except Exception as e:
+ logger.error(f"[StoryWriter] Failed to generate premise: {e}")
+ raise HTTPException(status_code=500, detail=str(e))
+
+
+# ---------------------------
+# Outline Generation Endpoints
+# ---------------------------
+
+@router.post("/generate-outline", response_model=StoryOutlineResponse)
+async def generate_outline(
+ request: StoryStartRequest,
+ current_user: Dict[str, Any] = Depends(get_current_user),
+ use_structured: bool = True
+) -> StoryOutlineResponse:
+ """Generate a story outline from a premise."""
+ try:
+ if not current_user:
+ raise HTTPException(status_code=401, detail="Authentication required")
+
+ user_id = str(current_user.get('id', ''))
+ if not user_id:
+ raise HTTPException(status_code=401, detail="Invalid user ID in authentication token")
+
+ if not request.premise or not request.premise.strip():
+ raise HTTPException(status_code=400, detail="Premise is required")
+
+ logger.info(f"[StoryWriter] Generating outline for user {user_id} (structured={use_structured})")
+ logger.info(f"[StoryWriter] Outline generation parameters: audience_age_group={request.audience_age_group}, writing_style={request.writing_style}, story_tone={request.story_tone}")
+
+ outline = service.generate_outline(
+ premise=request.premise,
+ persona=request.persona,
+ story_setting=request.story_setting,
+ character_input=request.character_input,
+ plot_elements=request.plot_elements,
+ writing_style=request.writing_style,
+ story_tone=request.story_tone,
+ narrative_pov=request.narrative_pov,
+ audience_age_group=request.audience_age_group,
+ content_rating=request.content_rating,
+ ending_preference=request.ending_preference,
+ user_id=user_id,
+ use_structured_output=use_structured
+ )
+
+ # Check if outline is structured (list of scenes) or plain text
+ is_structured = isinstance(outline, list)
+
+ if is_structured:
+ # Convert dict scenes to StoryScene models
+ scenes = [StoryScene(**scene) if isinstance(scene, dict) else scene for scene in outline]
+ return StoryOutlineResponse(outline=scenes, success=True, is_structured=True)
+ else:
+ # Plain text outline
+ return StoryOutlineResponse(outline=str(outline), success=True, is_structured=False)
+
+ except HTTPException:
+ raise
+ except Exception as e:
+ logger.error(f"[StoryWriter] Failed to generate outline: {e}")
+ raise HTTPException(status_code=500, detail=str(e))
+
+
+# ---------------------------
+# Story Content Generation Endpoints
+# ---------------------------
+
+@router.post("/generate-start", response_model=StoryContentResponse)
+async def generate_story_start(
+ request: StoryStartRequest,
+ current_user: Dict[str, Any] = Depends(get_current_user)
+) -> StoryContentResponse:
+ """Generate the starting section of a story."""
+ try:
+ if not current_user:
+ raise HTTPException(status_code=401, detail="Authentication required")
+
+ user_id = str(current_user.get('id', ''))
+ if not user_id:
+ raise HTTPException(status_code=401, detail="Invalid user ID in authentication token")
+
+ if not request.premise or not request.premise.strip():
+ raise HTTPException(status_code=400, detail="Premise is required")
+ if not request.outline or (isinstance(request.outline, str) and not request.outline.strip()):
+ raise HTTPException(status_code=400, detail="Outline is required")
+
+ logger.info(f"[StoryWriter] Generating story start for user {user_id}")
+
+ # Handle outline - could be string or list (structured scenes)
+ outline_data = request.outline
+ # Convert StoryScene models to dicts if needed
+ if isinstance(outline_data, list) and len(outline_data) > 0:
+ if isinstance(outline_data[0], StoryScene):
+ outline_data = [scene.dict() for scene in outline_data]
+
+ story_length = getattr(request, 'story_length', 'Medium')
+ story_start = service.generate_story_start(
+ premise=request.premise,
+ outline=outline_data,
+ persona=request.persona,
+ story_setting=request.story_setting,
+ character_input=request.character_input,
+ plot_elements=request.plot_elements,
+ writing_style=request.writing_style,
+ story_tone=request.story_tone,
+ narrative_pov=request.narrative_pov,
+ audience_age_group=request.audience_age_group,
+ content_rating=request.content_rating,
+ ending_preference=request.ending_preference,
+ story_length=story_length,
+ user_id=user_id
+ )
+
+ # Check if this is a short story - if so, mark as complete immediately
+ story_length_lower = story_length.lower()
+ is_short_story = "short" in story_length_lower or "1000" in story_length_lower
+
+ # For short stories, check word count to verify completeness
+ is_complete = False
+ if is_short_story:
+ word_count = len(story_start.split()) if story_start else 0
+ # Short story should be ~1000 words (900-1100 acceptable range)
+ if word_count >= 900:
+ is_complete = True
+ logger.info(f"[StoryWriter] Short story generated with {word_count} words. Marking as complete.")
+ else:
+ logger.warning(f"[StoryWriter] Short story generated with only {word_count} words. May need continuation.")
+
+ # Format outline for response (convert list to string if needed)
+ outline_response = outline_data
+ if isinstance(outline_data, list):
+ # Format structured outline as readable text
+ outline_response = "\n".join([
+ f"Scene {scene.get('scene_number', i+1) if isinstance(scene, dict) else getattr(scene, 'scene_number', i+1)}: "
+ f"{scene.get('title', 'Untitled') if isinstance(scene, dict) else getattr(scene, 'title', 'Untitled')}\n"
+ f" {scene.get('description', '') if isinstance(scene, dict) else getattr(scene, 'description', '')}"
+ for i, scene in enumerate(outline_data)
+ ])
+
+ return StoryContentResponse(
+ story=story_start,
+ premise=request.premise,
+ outline=str(outline_response),
+ is_complete=is_complete, # True for short stories that are complete, False for medium/long
+ success=True
+ )
+
+ except HTTPException:
+ raise
+ except Exception as e:
+ logger.error(f"[StoryWriter] Failed to generate story start: {e}")
+ raise HTTPException(status_code=500, detail=str(e))
+
+
+@router.post("/continue", response_model=StoryContinueResponse)
+async def continue_story(
+ request: StoryContinueRequest,
+ current_user: Dict[str, Any] = Depends(get_current_user)
+) -> StoryContinueResponse:
+ """Continue writing a story."""
+ try:
+ if not current_user:
+ raise HTTPException(status_code=401, detail="Authentication required")
+
+ user_id = str(current_user.get('id', ''))
+ if not user_id:
+ raise HTTPException(status_code=401, detail="Invalid user ID in authentication token")
+
+ if not request.story_text or not request.story_text.strip():
+ raise HTTPException(status_code=400, detail="Story text is required")
+
+ logger.info(f"[StoryWriter] Continuing story for user {user_id}")
+
+ # Handle outline - could be string or list (structured scenes)
+ outline_data = request.outline
+ # Convert StoryScene models to dicts if needed
+ if isinstance(outline_data, list) and len(outline_data) > 0:
+ if isinstance(outline_data[0], StoryScene):
+ outline_data = [scene.dict() for scene in outline_data]
+
+ # Check word count before continuing
+ story_length = getattr(request, 'story_length', 'Medium')
+ story_length_lower = story_length.lower()
+ is_short_story = "short" in story_length_lower or "1000" in story_length_lower
+
+ # Block continuation for short stories - they should be complete in one call
+ if is_short_story:
+ logger.warning(f"[StoryWriter] Attempted to continue a short story. Short stories should be complete in one call.")
+ raise HTTPException(
+ status_code=400,
+ detail="Short stories are generated in a single call and should be complete. If the story is incomplete, please regenerate it from the beginning."
+ )
+
+ current_word_count = len(request.story_text.split()) if request.story_text else 0
+
+ # Determine target word count based on story length (with 5% buffer)
+ # Medium: <5000 words (target ~4500, buffer ~4725)
+ # Long: around 10000 words (target ~10000, buffer ~10500)
+ if "long" in story_length_lower or "10000" in story_length_lower:
+ target_total_words = 10000
+ buffer_target = int(10000 * 1.05) # 10500 words maximum
+ else:
+ # Medium story: <5000 words
+ target_total_words = 4500 # Target for medium stories
+ buffer_target = int(4500 * 1.05) # ~4725 words maximum
+
+ # If target is already reached or exceeded, return completion immediately
+ if current_word_count >= buffer_target:
+ logger.info(f"[StoryWriter] Word count ({current_word_count}) already at or past buffer target ({buffer_target}) for {story_length} story. Story is complete.")
+ return StoryContinueResponse(
+ continuation="IAMDONE",
+ is_complete=True,
+ success=True
+ )
+
+ # Also check if we're very close to target (within 50 words)
+ if current_word_count >= target_total_words and (current_word_count - target_total_words) < 50:
+ logger.info(f"[StoryWriter] Word count ({current_word_count}) is very close to target ({target_total_words}). Story is complete.")
+ return StoryContinueResponse(
+ continuation="IAMDONE",
+ is_complete=True,
+ success=True
+ )
+
+ continuation = service.continue_story(
+ premise=request.premise,
+ outline=outline_data,
+ story_text=request.story_text,
+ persona=request.persona,
+ story_setting=request.story_setting,
+ character_input=request.character_input,
+ plot_elements=request.plot_elements,
+ writing_style=request.writing_style,
+ story_tone=request.story_tone,
+ narrative_pov=request.narrative_pov,
+ audience_age_group=request.audience_age_group,
+ content_rating=request.content_rating,
+ ending_preference=request.ending_preference,
+ story_length=story_length,
+ user_id=user_id
+ )
+
+ # Check if continuation is IAMDONE or if word count now exceeds target
+ is_complete = 'IAMDONE' in continuation.upper()
+
+ # Also check word count after continuation
+ if not is_complete and continuation:
+ # Estimate new word count
+ new_story_text = request.story_text + '\n\n' + continuation
+ new_word_count = len(new_story_text.split())
+
+ # Calculate buffer target
+ buffer_target = int(target_total_words * 1.05)
+
+ # If new word count exceeds buffer target, mark as complete
+ if new_word_count >= buffer_target:
+ logger.info(f"[StoryWriter] Word count ({new_word_count}) now exceeds buffer target ({buffer_target}). Story is complete.")
+ # Append IAMDONE if not already present
+ if 'IAMDONE' not in continuation.upper():
+ continuation = continuation.rstrip() + '\n\nIAMDONE'
+ is_complete = True
+ # Also check if we're at or very close to target
+ elif new_word_count >= target_total_words and (new_word_count - target_total_words) < 100:
+ logger.info(f"[StoryWriter] Word count ({new_word_count}) is at or very close to target ({target_total_words}). Story is complete.")
+ if 'IAMDONE' not in continuation.upper():
+ continuation = continuation.rstrip() + '\n\nIAMDONE'
+ is_complete = True
+
+ return StoryContinueResponse(
+ continuation=continuation,
+ is_complete=is_complete,
+ success=True
+ )
+
+ except HTTPException:
+ raise
+ except Exception as e:
+ logger.error(f"[StoryWriter] Failed to continue story: {e}")
+ raise HTTPException(status_code=500, detail=str(e))
+
+
+# ---------------------------
+# Full Story Generation Endpoints (Async)
+# ---------------------------
+
+@router.post("/generate-full", response_model=Dict[str, Any])
+async def generate_full_story(
+ request: StoryGenerationRequest,
+ background_tasks: BackgroundTasks,
+ current_user: Dict[str, Any] = Depends(get_current_user),
+ max_iterations: int = 10
+) -> Dict[str, Any]:
+ """Generate a complete story asynchronously."""
+ try:
+ if not current_user:
+ raise HTTPException(status_code=401, detail="Authentication required")
+
+ user_id = str(current_user.get('id', ''))
+ if not user_id:
+ raise HTTPException(status_code=401, detail="Invalid user ID in authentication token")
+
+ # Check cache first
+ cache_key = cache_manager.get_cache_key(request.dict())
+ cached_result = cache_manager.get_cached_result(cache_key)
+ if cached_result:
+ logger.info(f"[StoryWriter] Returning cached result for user {user_id}")
+ task_id = task_manager.create_task("story_generation")
+ task_manager.update_task_status(
+ task_id,
+ "completed",
+ progress=100.0,
+ result=cached_result,
+ message="Returned cached result"
+ )
+ return {"task_id": task_id, "cached": True}
+
+ # Create task
+ task_id = task_manager.create_task("story_generation")
+
+ # Prepare request data
+ request_data = request.dict()
+ request_data["max_iterations"] = max_iterations
+
+ # Execute task in background
+ background_tasks.add_task(
+ task_manager.execute_story_generation_task,
+ task_id=task_id,
+ request_data=request_data,
+ user_id=user_id
+ )
+
+ logger.info(f"[StoryWriter] Created task {task_id} for full story generation (user {user_id})")
+
+ return {
+ "task_id": task_id,
+ "status": "pending",
+ "message": "Story generation started. Use /task/{task_id}/status to check progress."
+ }
+
+ except HTTPException:
+ raise
+ except Exception as e:
+ logger.error(f"[StoryWriter] Failed to start story generation: {e}")
+ raise HTTPException(status_code=500, detail=str(e))
+
+
+# ---------------------------
+# Task Management Endpoints
+# ---------------------------
+
+@router.get("/task/{task_id}/status", response_model=TaskStatus)
+async def get_task_status(
+ task_id: str,
+ current_user: Dict[str, Any] = Depends(get_current_user)
+) -> TaskStatus:
+ """Get the status of a story generation task."""
+ try:
+ if not current_user:
+ raise HTTPException(status_code=401, detail="Authentication required")
+
+ task_status = task_manager.get_task_status(task_id)
+
+ if not task_status:
+ raise HTTPException(status_code=404, detail=f"Task {task_id} not found")
+
+ return TaskStatus(**task_status)
+
+ except HTTPException:
+ raise
+ except Exception as e:
+ logger.error(f"[StoryWriter] Failed to get task status: {e}")
+ raise HTTPException(status_code=500, detail=str(e))
+
+
+@router.get("/task/{task_id}/result", response_model=StoryFullGenerationResponse)
+async def get_task_result(
+ task_id: str,
+ current_user: Dict[str, Any] = Depends(get_current_user)
+) -> StoryFullGenerationResponse:
+ """Get the result of a completed story generation task."""
+ try:
+ if not current_user:
+ raise HTTPException(status_code=401, detail="Authentication required")
+
+ task_status = task_manager.get_task_status(task_id)
+
+ if not task_status:
+ raise HTTPException(status_code=404, detail=f"Task {task_id} not found")
+
+ if task_status["status"] != "completed":
+ raise HTTPException(
+ status_code=400,
+ detail=f"Task {task_id} is not completed. Status: {task_status['status']}"
+ )
+
+ result = task_status.get("result")
+ if not result:
+ raise HTTPException(status_code=404, detail=f"No result found for task {task_id}")
+
+ return StoryFullGenerationResponse(**result, success=True, task_id=task_id)
+
+ except HTTPException:
+ raise
+ except Exception as e:
+ logger.error(f"[StoryWriter] Failed to get task result: {e}")
+ raise HTTPException(status_code=500, detail=str(e))
+
+
+# ---------------------------
+# Image Generation Endpoints
+# ---------------------------
+
+@router.post("/generate-images", response_model=StoryImageGenerationResponse)
+async def generate_scene_images(
+ request: StoryImageGenerationRequest,
+ current_user: Dict[str, Any] = Depends(get_current_user)
+) -> StoryImageGenerationResponse:
+ """Generate images for story scenes."""
+ try:
+ if not current_user:
+ raise HTTPException(status_code=401, detail="Authentication required")
+
+ user_id = str(current_user.get('id', ''))
+ if not user_id:
+ raise HTTPException(status_code=401, detail="Invalid user ID in authentication token")
+
+ if not request.scenes or len(request.scenes) == 0:
+ raise HTTPException(status_code=400, detail="At least one scene is required")
+
+ logger.info(f"[StoryWriter] Generating images for {len(request.scenes)} scenes for user {user_id}")
+
+ # Import image generation service
+ from services.story_writer.image_generation_service import StoryImageGenerationService
+
+ image_service = StoryImageGenerationService()
+
+ # Convert StoryScene models to dicts
+ scenes_data = [scene.dict() if isinstance(scene, StoryScene) else scene for scene in request.scenes]
+
+ # Generate images for all scenes
+ image_results = image_service.generate_scene_images(
+ scenes=scenes_data,
+ user_id=user_id,
+ provider=request.provider,
+ width=request.width or 1024,
+ height=request.height or 1024,
+ model=request.model
+ )
+
+ # Convert results to StoryImageResult models
+ image_models = [
+ StoryImageResult(
+ scene_number=result.get("scene_number", 0),
+ scene_title=result.get("scene_title", "Untitled"),
+ image_filename=result.get("image_filename", ""),
+ image_url=result.get("image_url", ""),
+ width=result.get("width", 1024),
+ height=result.get("height", 1024),
+ provider=result.get("provider", "unknown"),
+ model=result.get("model"),
+ seed=result.get("seed"),
+ error=result.get("error")
+ )
+ for result in image_results
+ ]
+
+ return StoryImageGenerationResponse(
+ images=image_models,
+ success=True
+ )
+
+ except HTTPException:
+ raise
+ except Exception as e:
+ logger.error(f"[StoryWriter] Failed to generate images: {e}")
+ raise HTTPException(status_code=500, detail=str(e))
+
+
+@router.get("/images/{image_filename}")
+async def serve_scene_image(
+ image_filename: str,
+ current_user: Dict[str, Any] = Depends(get_current_user)
+):
+ """Serve a generated story scene image."""
+ try:
+ if not current_user:
+ raise HTTPException(status_code=401, detail="Authentication required")
+
+ # Import image generation service to get output directory
+ from services.story_writer.image_generation_service import StoryImageGenerationService
+ from fastapi.responses import FileResponse
+
+ image_service = StoryImageGenerationService()
+ image_path = image_service.output_dir / image_filename
+
+ if not image_path.exists():
+ raise HTTPException(status_code=404, detail=f"Image not found: {image_filename}")
+
+ # Validate that the file is within the output directory (security check)
+ try:
+ image_path.resolve().relative_to(image_service.output_dir.resolve())
+ except ValueError:
+ raise HTTPException(status_code=403, detail="Access denied")
+
+ return FileResponse(
+ path=str(image_path),
+ media_type="image/png",
+ filename=image_filename
+ )
+
+ except HTTPException:
+ raise
+ except Exception as e:
+ logger.error(f"[StoryWriter] Failed to serve image: {e}")
+ raise HTTPException(status_code=500, detail=str(e))
+
+
+# ---------------------------
+# Audio Generation Endpoints
+# ---------------------------
+
+@router.post("/generate-audio", response_model=StoryAudioGenerationResponse)
+async def generate_scene_audio(
+ request: StoryAudioGenerationRequest,
+ current_user: Dict[str, Any] = Depends(get_current_user)
+) -> StoryAudioGenerationResponse:
+ """Generate audio narration for story scenes."""
+ try:
+ if not current_user:
+ raise HTTPException(status_code=401, detail="Authentication required")
+
+ user_id = str(current_user.get('id', ''))
+ if not user_id:
+ raise HTTPException(status_code=401, detail="Invalid user ID in authentication token")
+
+ if not request.scenes or len(request.scenes) == 0:
+ raise HTTPException(status_code=400, detail="At least one scene is required")
+
+ logger.info(f"[StoryWriter] Generating audio for {len(request.scenes)} scenes for user {user_id}")
+
+ # Import audio generation service
+ from services.story_writer.audio_generation_service import StoryAudioGenerationService
+
+ audio_service = StoryAudioGenerationService()
+
+ # Convert StoryScene models to dicts
+ scenes_data = [scene.dict() if isinstance(scene, StoryScene) else scene for scene in request.scenes]
+
+ # Generate audio for all scenes
+ audio_results = audio_service.generate_scene_audio_list(
+ scenes=scenes_data,
+ user_id=user_id,
+ provider=request.provider or "gtts",
+ lang=request.lang or "en",
+ slow=request.slow or False,
+ rate=request.rate or 150
+ )
+
+ # Convert results to StoryAudioResult models
+ # Ensure all required fields are strings, not None
+ audio_models = []
+ for result in audio_results:
+ # Handle None values by converting to empty strings for required fields
+ audio_url = result.get("audio_url") or ""
+ audio_filename = result.get("audio_filename") or ""
+
+ audio_models.append(
+ StoryAudioResult(
+ scene_number=result.get("scene_number", 0),
+ scene_title=result.get("scene_title", "Untitled"),
+ audio_filename=audio_filename,
+ audio_url=audio_url,
+ provider=result.get("provider", "unknown"),
+ file_size=result.get("file_size", 0),
+ error=result.get("error")
+ )
+ )
+
+ return StoryAudioGenerationResponse(
+ audio_files=audio_models,
+ success=True
+ )
+
+ except HTTPException:
+ raise
+ except Exception as e:
+ logger.error(f"[StoryWriter] Failed to generate audio: {e}")
+ raise HTTPException(status_code=500, detail=str(e))
+
+
+@router.get("/audio/{audio_filename}")
+async def serve_scene_audio(
+ audio_filename: str,
+ current_user: Dict[str, Any] = Depends(get_current_user)
+):
+ """Serve a generated story scene audio file."""
+ try:
+ if not current_user:
+ raise HTTPException(status_code=401, detail="Authentication required")
+
+ # Import audio generation service to get output directory
+ from services.story_writer.audio_generation_service import StoryAudioGenerationService
+ from fastapi.responses import FileResponse
+
+ audio_service = StoryAudioGenerationService()
+ audio_path = audio_service.output_dir / audio_filename
+
+ if not audio_path.exists():
+ raise HTTPException(status_code=404, detail=f"Audio not found: {audio_filename}")
+
+ # Validate that the file is within the output directory (security check)
+ try:
+ audio_path.resolve().relative_to(audio_service.output_dir.resolve())
+ except ValueError:
+ raise HTTPException(status_code=403, detail="Access denied")
+
+ return FileResponse(
+ path=str(audio_path),
+ media_type="audio/mpeg",
+ filename=audio_filename
+ )
+
+ except HTTPException:
+ raise
+ except Exception as e:
+ logger.error(f"[StoryWriter] Failed to serve audio: {e}")
+ raise HTTPException(status_code=500, detail=str(e))
+
+
+# ---------------------------
+# Video Generation Endpoints
+# ---------------------------
+
+@router.post("/generate-video", response_model=StoryVideoGenerationResponse)
+async def generate_story_video(
+ request: StoryVideoGenerationRequest,
+ current_user: Dict[str, Any] = Depends(get_current_user)
+) -> StoryVideoGenerationResponse:
+ """Generate a video from story scenes, images, and audio."""
+ try:
+ if not current_user:
+ raise HTTPException(status_code=401, detail="Authentication required")
+
+ user_id = str(current_user.get('id', ''))
+ if not user_id:
+ raise HTTPException(status_code=401, detail="Invalid user ID in authentication token")
+
+ if not request.scenes or len(request.scenes) == 0:
+ raise HTTPException(status_code=400, detail="At least one scene is required")
+
+ if len(request.scenes) != len(request.image_urls) or len(request.scenes) != len(request.audio_urls):
+ raise HTTPException(status_code=400, detail="Number of scenes, image URLs, and audio URLs must match")
+
+ logger.info(f"[StoryWriter] Generating video for {len(request.scenes)} scenes for user {user_id}")
+
+ # Import video generation service and image/audio services
+ from services.story_writer.video_generation_service import StoryVideoGenerationService
+ from services.story_writer.image_generation_service import StoryImageGenerationService
+ from services.story_writer.audio_generation_service import StoryAudioGenerationService
+ from pathlib import Path
+
+ video_service = StoryVideoGenerationService()
+ image_service = StoryImageGenerationService()
+ audio_service = StoryAudioGenerationService()
+
+ # Convert StoryScene models to dicts
+ scenes_data = [scene.dict() if isinstance(scene, StoryScene) else scene for scene in request.scenes]
+
+ # Extract image and audio filenames from URLs
+ image_paths = []
+ audio_paths = []
+ valid_scenes = []
+
+ for idx, (scene, image_url, audio_url) in enumerate(zip(scenes_data, request.image_urls, request.audio_urls)):
+ # Extract filename from URL (e.g., "/api/story/images/scene_1_image.png" -> "scene_1_image.png")
+ # Handle both full URLs and relative paths
+ image_filename = image_url.split('/')[-1] if '/' in image_url else image_url
+ audio_filename = audio_url.split('/')[-1] if '/' in audio_url else audio_url
+
+ # Remove query parameters if present
+ image_filename = image_filename.split('?')[0]
+ audio_filename = audio_filename.split('?')[0]
+
+ # Construct full paths
+ image_path = image_service.output_dir / image_filename
+ audio_path = audio_service.output_dir / audio_filename
+
+ if not image_path.exists():
+ logger.warning(f"[StoryWriter] Image not found: {image_path} (from URL: {image_url})")
+ continue
+ if not audio_path.exists():
+ logger.warning(f"[StoryWriter] Audio not found: {audio_path} (from URL: {audio_url})")
+ continue
+
+ image_paths.append(str(image_path))
+ audio_paths.append(str(audio_path))
+ valid_scenes.append(scene)
+
+ if len(image_paths) == 0 or len(audio_paths) == 0:
+ raise HTTPException(status_code=400, detail="No valid image or audio files were found")
+
+ if len(image_paths) != len(audio_paths):
+ raise HTTPException(status_code=400, detail="Number of valid images and audio files must match")
+
+ # Use only valid scenes that have both image and audio
+ scenes_data = valid_scenes
+
+ # Generate video
+ video_result = video_service.generate_story_video(
+ scenes=scenes_data,
+ image_paths=image_paths,
+ audio_paths=audio_paths,
+ user_id=user_id,
+ story_title=request.story_title or "Story",
+ fps=request.fps or 24,
+ transition_duration=request.transition_duration or 0.5
+ )
+
+ # Convert result to StoryVideoResult model
+ video_model = StoryVideoResult(
+ video_filename=video_result.get("video_filename", ""),
+ video_url=video_result.get("video_url", ""),
+ duration=video_result.get("duration", 0.0),
+ fps=video_result.get("fps", 24),
+ file_size=video_result.get("file_size", 0),
+ num_scenes=video_result.get("num_scenes", 0),
+ error=video_result.get("error")
+ )
+
+ return StoryVideoGenerationResponse(
+ video=video_model,
+ success=True
+ )
+
+ except HTTPException:
+ raise
+ except Exception as e:
+ logger.error(f"[StoryWriter] Failed to generate video: {e}")
+ raise HTTPException(status_code=500, detail=str(e))
+
+
+@router.post("/generate-complete-video", response_model=Dict[str, Any])
+async def generate_complete_story_video(
+ request: StoryGenerationRequest,
+ background_tasks: BackgroundTasks,
+ current_user: Dict[str, Any] = Depends(get_current_user)
+) -> Dict[str, Any]:
+ """Generate a complete story video (outline → images → audio → video) asynchronously."""
+ try:
+ if not current_user:
+ raise HTTPException(status_code=401, detail="Authentication required")
+
+ user_id = str(current_user.get('id', ''))
+ if not user_id:
+ raise HTTPException(status_code=401, detail="Invalid user ID in authentication token")
+
+ logger.info(f"[StoryWriter] Starting complete video generation for user {user_id}")
+
+ # Create task
+ task_id = task_manager.create_task("complete_video_generation")
+
+ # Start background task
+ background_tasks.add_task(
+ execute_complete_video_generation,
+ task_id=task_id,
+ request_data=request.dict(),
+ user_id=user_id
+ )
+
+ return {
+ "task_id": task_id,
+ "status": "pending",
+ "message": "Complete video generation started"
+ }
+
+ except HTTPException:
+ raise
+ except Exception as e:
+ logger.error(f"[StoryWriter] Failed to start complete video generation: {e}")
+ raise HTTPException(status_code=500, detail=str(e))
+
+
+def execute_complete_video_generation(
+ task_id: str,
+ request_data: Dict[str, Any],
+ user_id: str
+):
+ """
+ Execute complete video generation workflow synchronously.
+
+ This function runs in a background task and performs blocking operations.
+ It's not async because it calls synchronous methods from the services.
+ """
+ from services.story_writer.story_service import StoryWriterService
+ from services.story_writer.image_generation_service import StoryImageGenerationService
+ from services.story_writer.audio_generation_service import StoryAudioGenerationService
+ from services.story_writer.video_generation_service import StoryVideoGenerationService
+
+ service = StoryWriterService()
+ image_service = StoryImageGenerationService()
+ audio_service = StoryAudioGenerationService()
+ video_service = StoryVideoGenerationService()
+
+ try:
+ task_manager.update_task_status(task_id, "processing", progress=5.0, message="Starting complete video generation...")
+
+ # Step 1: Generate premise
+ task_manager.update_task_status(task_id, "processing", progress=10.0, message="Generating story premise...")
+ premise = service.generate_premise(
+ persona=request_data["persona"],
+ story_setting=request_data["story_setting"],
+ character_input=request_data["character_input"],
+ plot_elements=request_data["plot_elements"],
+ writing_style=request_data["writing_style"],
+ story_tone=request_data["story_tone"],
+ narrative_pov=request_data["narrative_pov"],
+ audience_age_group=request_data["audience_age_group"],
+ content_rating=request_data["content_rating"],
+ ending_preference=request_data["ending_preference"],
+ user_id=user_id
+ )
+
+ # Step 2: Generate structured outline
+ task_manager.update_task_status(task_id, "processing", progress=20.0, message="Generating structured outline with scenes...")
+ outline_scenes = service.generate_outline(
+ premise=premise,
+ persona=request_data["persona"],
+ story_setting=request_data["story_setting"],
+ character_input=request_data["character_input"],
+ plot_elements=request_data["plot_elements"],
+ writing_style=request_data["writing_style"],
+ story_tone=request_data["story_tone"],
+ narrative_pov=request_data["narrative_pov"],
+ audience_age_group=request_data["audience_age_group"],
+ content_rating=request_data["content_rating"],
+ ending_preference=request_data["ending_preference"],
+ user_id=user_id,
+ use_structured_output=True
+ )
+
+ if not isinstance(outline_scenes, list):
+ raise RuntimeError("Failed to generate structured outline")
+
+ # Step 3: Generate images for all scenes
+ # Progress range: 30-50% (20% total for image generation)
+ task_manager.update_task_status(task_id, "processing", progress=30.0, message="Generating images for scenes...")
+
+ def image_progress_callback(sub_progress: float, message: str):
+ """Map sub-progress (0-100) to overall progress (30-50%)."""
+ overall_progress = 30.0 + (sub_progress * 0.2)
+ task_manager.update_task_status(task_id, "processing", progress=overall_progress, message=message)
+
+ # Get image generation settings from request (with defaults)
+ image_provider = request_data.get("image_provider")
+ image_width = request_data.get("image_width", 1024)
+ image_height = request_data.get("image_height", 1024)
+ image_model = request_data.get("image_model")
+
+ image_results = image_service.generate_scene_images(
+ scenes=outline_scenes,
+ user_id=user_id,
+ provider=image_provider,
+ width=image_width,
+ height=image_height,
+ model=image_model,
+ progress_callback=image_progress_callback
+ )
+
+ # Step 4: Generate audio for all scenes
+ # Progress range: 50-70% (20% total for audio generation)
+ task_manager.update_task_status(task_id, "processing", progress=50.0, message="Generating audio narration for scenes...")
+
+ def audio_progress_callback(sub_progress: float, message: str):
+ """Map sub-progress (0-100) to overall progress (50-70%)."""
+ overall_progress = 50.0 + (sub_progress * 0.2)
+ task_manager.update_task_status(task_id, "processing", progress=overall_progress, message=message)
+
+ # Get audio generation settings from request (with defaults)
+ audio_provider = request_data.get("audio_provider", "gtts")
+ audio_lang = request_data.get("audio_lang", "en")
+ audio_slow = request_data.get("audio_slow", False)
+ audio_rate = request_data.get("audio_rate", 150)
+
+ audio_results = audio_service.generate_scene_audio_list(
+ scenes=outline_scenes,
+ user_id=user_id,
+ provider=audio_provider,
+ lang=audio_lang,
+ slow=audio_slow,
+ rate=audio_rate,
+ progress_callback=audio_progress_callback
+ )
+
+ # Step 5: Prepare image and audio paths
+ task_manager.update_task_status(task_id, "processing", progress=70.0, message="Preparing video assets...")
+ image_paths = []
+ audio_paths = []
+ valid_scenes = []
+
+ for scene in outline_scenes:
+ scene_number = scene.get("scene_number", 0)
+ image_result = next((img for img in image_results if img.get("scene_number") == scene_number), None)
+ audio_result = next((aud for aud in audio_results if aud.get("scene_number") == scene_number), None)
+
+ if image_result and audio_result and not image_result.get("error") and not audio_result.get("error"):
+ image_path = image_result.get("image_path")
+ audio_path = audio_result.get("audio_path")
+
+ if image_path and audio_path:
+ image_paths.append(image_path)
+ audio_paths.append(audio_path)
+ valid_scenes.append(scene)
+
+ if len(image_paths) == 0 or len(audio_paths) == 0:
+ raise RuntimeError(f"No valid images or audio files were generated. Images: {len(image_paths)}, Audio: {len(audio_paths)}")
+
+ if len(image_paths) != len(audio_paths):
+ raise RuntimeError(f"Mismatch between image and audio counts. Images: {len(image_paths)}, Audio: {len(audio_paths)}")
+
+ # Step 6: Generate video
+ # Progress range: 75-95% (20% total for video generation)
+ task_manager.update_task_status(task_id, "processing", progress=75.0, message="Composing video from scenes...")
+
+ def video_progress_callback(sub_progress: float, message: str):
+ """Map sub-progress (0-100) to overall progress (75-95%)."""
+ overall_progress = 75.0 + (sub_progress * 0.2)
+ task_manager.update_task_status(task_id, "processing", progress=overall_progress, message=message)
+
+ # Get video generation settings from request (with defaults)
+ video_fps = request_data.get("video_fps", 24)
+ video_transition_duration = request_data.get("video_transition_duration", 0.5)
+ story_title = request_data.get("story_setting", "Story")[:50]
+
+ video_result = video_service.generate_story_video(
+ scenes=valid_scenes,
+ image_paths=image_paths,
+ audio_paths=audio_paths,
+ user_id=user_id,
+ story_title=story_title,
+ fps=video_fps,
+ transition_duration=video_transition_duration,
+ progress_callback=video_progress_callback
+ )
+
+ # Prepare result
+ result = {
+ "premise": premise,
+ "outline_scenes": outline_scenes,
+ "images": image_results,
+ "audio_files": audio_results,
+ "video": video_result,
+ "success": True
+ }
+
+ task_manager.update_task_status(
+ task_id,
+ "completed",
+ progress=100.0,
+ message="Complete video generation finished!",
+ result=result
+ )
+
+ logger.info(f"[StoryWriter] Complete video generation task {task_id} completed successfully")
+
+ except Exception as e:
+ error_msg = str(e)
+ logger.error(f"[StoryWriter] Complete video generation task {task_id} failed: {error_msg}", exc_info=True)
+ task_manager.update_task_status(
+ task_id,
+ "failed",
+ error=error_msg,
+ message=f"Complete video generation failed: {error_msg}"
+ )
+
+
+@router.get("/videos/{video_filename}")
+async def serve_story_video(
+ video_filename: str,
+ current_user: Dict[str, Any] = Depends(get_current_user)
+):
+ """Serve a generated story video file."""
+ try:
+ if not current_user:
+ raise HTTPException(status_code=401, detail="Authentication required")
+
+ # Import video generation service to get output directory
+ from services.story_writer.video_generation_service import StoryVideoGenerationService
+ from fastapi.responses import FileResponse
+
+ video_service = StoryVideoGenerationService()
+ video_path = video_service.output_dir / video_filename
+
+ if not video_path.exists():
+ raise HTTPException(status_code=404, detail=f"Video not found: {video_filename}")
+
+ # Validate that the file is within the output directory (security check)
+ try:
+ video_path.resolve().relative_to(video_service.output_dir.resolve())
+ except ValueError:
+ raise HTTPException(status_code=403, detail="Access denied")
+
+ return FileResponse(
+ path=str(video_path),
+ media_type="video/mp4",
+ filename=video_filename
+ )
+
+ except HTTPException:
+ raise
+ except Exception as e:
+ logger.error(f"[StoryWriter] Failed to serve video: {e}")
+ raise HTTPException(status_code=500, detail=str(e))
+
+
+# ---------------------------
+# Cache Management Endpoints
+# ---------------------------
+
+@router.get("/cache/stats")
+async def get_cache_stats(
+ current_user: Dict[str, Any] = Depends(get_current_user)
+) -> Dict[str, Any]:
+ """Get cache statistics."""
+ try:
+ if not current_user:
+ raise HTTPException(status_code=401, detail="Authentication required")
+
+ stats = cache_manager.get_cache_stats()
+ return {"success": True, "stats": stats}
+
+ except Exception as e:
+ logger.error(f"[StoryWriter] Failed to get cache stats: {e}")
+ raise HTTPException(status_code=500, detail=str(e))
+
+
+@router.post("/cache/clear")
+async def clear_cache(
+ current_user: Dict[str, Any] = Depends(get_current_user)
+) -> Dict[str, Any]:
+ """Clear the story generation cache."""
+ try:
+ if not current_user:
+ raise HTTPException(status_code=401, detail="Authentication required")
+
+ result = cache_manager.clear_cache()
+ return {"success": True, **result}
+
+ except Exception as e:
+ logger.error(f"[StoryWriter] Failed to clear cache: {e}")
+ raise HTTPException(status_code=500, detail=str(e))
diff --git a/backend/api/story_writer/task_manager.py b/backend/api/story_writer/task_manager.py
new file mode 100644
index 00000000..58b876c0
--- /dev/null
+++ b/backend/api/story_writer/task_manager.py
@@ -0,0 +1,251 @@
+"""
+Task Management System for Story Writer API
+
+Handles background task execution, status tracking, and progress updates
+for story generation operations.
+"""
+
+import asyncio
+import uuid
+from datetime import datetime
+from typing import Any, Dict, Optional
+from loguru import logger
+
+
+class TaskManager:
+ """Manages background tasks for story generation."""
+
+ def __init__(self):
+ """Initialize the task manager."""
+ self.task_storage: Dict[str, Dict[str, Any]] = {}
+ logger.info("[StoryWriter] TaskManager initialized")
+
+ def cleanup_old_tasks(self):
+ """Remove tasks older than 1 hour to prevent memory leaks."""
+ current_time = datetime.now()
+ tasks_to_remove = []
+
+ for task_id, task_data in self.task_storage.items():
+ created_at = task_data.get("created_at")
+ if created_at and (current_time - created_at).total_seconds() > 3600: # 1 hour
+ tasks_to_remove.append(task_id)
+
+ for task_id in tasks_to_remove:
+ del self.task_storage[task_id]
+ logger.debug(f"[StoryWriter] Cleaned up old task: {task_id}")
+
+ def create_task(self, task_type: str = "story_generation") -> str:
+ """Create a new task and return its ID."""
+ task_id = str(uuid.uuid4())
+
+ self.task_storage[task_id] = {
+ "status": "pending",
+ "created_at": datetime.now(),
+ "result": None,
+ "error": None,
+ "progress_messages": [],
+ "task_type": task_type,
+ "progress": 0.0
+ }
+
+ logger.info(f"[StoryWriter] Created task: {task_id} (type: {task_type})")
+ return task_id
+
+ def get_task_status(self, task_id: str) -> Optional[Dict[str, Any]]:
+ """Get the status of a task."""
+ self.cleanup_old_tasks()
+
+ if task_id not in self.task_storage:
+ logger.warning(f"[StoryWriter] Task not found: {task_id}")
+ return None
+
+ task = self.task_storage[task_id]
+ response = {
+ "task_id": task_id,
+ "status": task["status"],
+ "progress": task.get("progress", 0.0),
+ "message": task.get("progress_messages", [])[-1] if task.get("progress_messages") else None,
+ "created_at": task["created_at"].isoformat() if task.get("created_at") else None,
+ "updated_at": task.get("updated_at", task.get("created_at")).isoformat() if task.get("updated_at") or task.get("created_at") else None,
+ }
+
+ if task["status"] == "completed" and task.get("result"):
+ response["result"] = task["result"]
+
+ if task["status"] == "failed" and task.get("error"):
+ response["error"] = task["error"]
+
+ return response
+
+ def update_task_status(
+ self,
+ task_id: str,
+ status: str,
+ progress: Optional[float] = None,
+ message: Optional[str] = None,
+ result: Optional[Dict[str, Any]] = None,
+ error: Optional[str] = None
+ ):
+ """Update the status of a task."""
+ if task_id not in self.task_storage:
+ logger.warning(f"[StoryWriter] Cannot update non-existent task: {task_id}")
+ return
+
+ task = self.task_storage[task_id]
+ task["status"] = status
+ task["updated_at"] = datetime.now()
+
+ if progress is not None:
+ task["progress"] = progress
+
+ if message:
+ if "progress_messages" not in task:
+ task["progress_messages"] = []
+ task["progress_messages"].append(message)
+ logger.info(f"[StoryWriter] Task {task_id}: {message} (progress: {progress}%)")
+
+ if result is not None:
+ task["result"] = result
+
+ if error is not None:
+ task["error"] = error
+ logger.error(f"[StoryWriter] Task {task_id} error: {error}")
+
+ async def execute_story_generation_task(
+ self,
+ task_id: str,
+ request_data: Dict[str, Any],
+ user_id: str
+ ):
+ """Execute story generation task asynchronously."""
+ from services.story_writer.story_service import StoryWriterService
+
+ service = StoryWriterService()
+
+ try:
+ self.update_task_status(task_id, "processing", progress=0.0, message="Starting story generation...")
+
+ # Step 1: Generate premise
+ self.update_task_status(task_id, "processing", progress=10.0, message="Generating story premise...")
+ premise = service.generate_premise(
+ persona=request_data["persona"],
+ story_setting=request_data["story_setting"],
+ character_input=request_data["character_input"],
+ plot_elements=request_data["plot_elements"],
+ writing_style=request_data["writing_style"],
+ story_tone=request_data["story_tone"],
+ narrative_pov=request_data["narrative_pov"],
+ audience_age_group=request_data["audience_age_group"],
+ content_rating=request_data["content_rating"],
+ ending_preference=request_data["ending_preference"],
+ user_id=user_id
+ )
+
+ # Step 2: Generate outline
+ self.update_task_status(task_id, "processing", progress=30.0, message="Generating story outline...")
+ outline = service.generate_outline(
+ premise=premise,
+ persona=request_data["persona"],
+ story_setting=request_data["story_setting"],
+ character_input=request_data["character_input"],
+ plot_elements=request_data["plot_elements"],
+ writing_style=request_data["writing_style"],
+ story_tone=request_data["story_tone"],
+ narrative_pov=request_data["narrative_pov"],
+ audience_age_group=request_data["audience_age_group"],
+ content_rating=request_data["content_rating"],
+ ending_preference=request_data["ending_preference"],
+ user_id=user_id
+ )
+
+ # Step 3: Generate story start
+ self.update_task_status(task_id, "processing", progress=50.0, message="Writing story beginning...")
+ story_start = service.generate_story_start(
+ premise=premise,
+ outline=outline,
+ persona=request_data["persona"],
+ story_setting=request_data["story_setting"],
+ character_input=request_data["character_input"],
+ plot_elements=request_data["plot_elements"],
+ writing_style=request_data["writing_style"],
+ story_tone=request_data["story_tone"],
+ narrative_pov=request_data["narrative_pov"],
+ audience_age_group=request_data["audience_age_group"],
+ content_rating=request_data["content_rating"],
+ ending_preference=request_data["ending_preference"],
+ user_id=user_id
+ )
+
+ # Step 4: Continue story
+ self.update_task_status(task_id, "processing", progress=70.0, message="Continuing story generation...")
+ story_text = story_start
+ max_iterations = request_data.get("max_iterations", 10)
+ iteration = 0
+
+ while 'IAMDONE' not in story_text and iteration < max_iterations:
+ iteration += 1
+ progress = 70.0 + (iteration / max_iterations) * 25.0
+ self.update_task_status(
+ task_id,
+ "processing",
+ progress=min(progress, 95.0),
+ message=f"Writing continuation {iteration}/{max_iterations}..."
+ )
+
+ continuation = service.continue_story(
+ premise=premise,
+ outline=outline,
+ story_text=story_text,
+ persona=request_data["persona"],
+ story_setting=request_data["story_setting"],
+ character_input=request_data["character_input"],
+ plot_elements=request_data["plot_elements"],
+ writing_style=request_data["writing_style"],
+ story_tone=request_data["story_tone"],
+ narrative_pov=request_data["narrative_pov"],
+ audience_age_group=request_data["audience_age_group"],
+ content_rating=request_data["content_rating"],
+ ending_preference=request_data["ending_preference"],
+ user_id=user_id
+ )
+
+ if continuation:
+ story_text += '\n\n' + continuation
+ else:
+ logger.warning(f"[StoryWriter] Empty continuation at iteration {iteration}")
+ break
+
+ # Clean up and finalize
+ final_story = story_text.replace('IAMDONE', '').strip()
+
+ result = {
+ "premise": premise,
+ "outline": outline,
+ "story": final_story,
+ "is_complete": 'IAMDONE' in story_text or iteration >= max_iterations,
+ "iterations": iteration
+ }
+
+ self.update_task_status(
+ task_id,
+ "completed",
+ progress=100.0,
+ message="Story generation completed!",
+ result=result
+ )
+
+ logger.info(f"[StoryWriter] Task {task_id} completed successfully")
+
+ except Exception as e:
+ error_msg = str(e)
+ logger.error(f"[StoryWriter] Task {task_id} failed: {error_msg}")
+ self.update_task_status(
+ task_id,
+ "failed",
+ error=error_msg,
+ message=f"Story generation failed: {error_msg}"
+ )
+
+
+# Global task manager instance
+task_manager = TaskManager()
diff --git a/backend/api/subscription_api.py b/backend/api/subscription_api.py
index 8da81210..cb02204f 100644
--- a/backend/api/subscription_api.py
+++ b/backend/api/subscription_api.py
@@ -5,6 +5,7 @@ Provides endpoints for subscription management and usage monitoring.
from fastapi import APIRouter, Depends, HTTPException, Query
from sqlalchemy.orm import Session
+from sqlalchemy import desc, func
from typing import Dict, Any, Optional, List
from datetime import datetime, timedelta
from loguru import logger
@@ -12,12 +13,14 @@ from functools import lru_cache
from services.database import get_db
from services.subscription import UsageTrackingService, PricingService
+from services.subscription.log_wrapping_service import LogWrappingService
from services.subscription.schema_utils import ensure_subscription_plan_columns
import sqlite3
from middleware.auth_middleware import get_current_user
from models.subscription_models import (
APIProvider, SubscriptionPlan, UserSubscription, UsageSummary,
- APIProviderPricing, UsageAlert, SubscriptionTier, BillingCycle, UsageStatus
+ APIProviderPricing, UsageAlert, SubscriptionTier, BillingCycle, UsageStatus,
+ APIUsageLog, SubscriptionRenewalHistory
)
router = APIRouter(prefix="/api/subscription", tags=["subscription"])
@@ -525,8 +528,67 @@ async def subscribe_to_plan(
).first()
now = datetime.utcnow()
-
+
+ # Track renewal history - capture BEFORE updating subscription
+ previous_period_start = None
+ previous_period_end = None
+ previous_plan_name = None
+ previous_plan_tier = None
+ renewal_type = "new"
+ renewal_count = 0
+
+ # Get usage snapshot BEFORE renewal (capture current state)
+ usage_before_snapshot = None
+ current_period = datetime.utcnow().strftime("%Y-%m")
+ usage_before = db.query(UsageSummary).filter(
+ UsageSummary.user_id == user_id,
+ UsageSummary.billing_period == current_period
+ ).first()
+
+ if usage_before:
+ usage_before_snapshot = {
+ "total_calls": usage_before.total_calls or 0,
+ "total_tokens": usage_before.total_tokens or 0,
+ "total_cost": float(usage_before.total_cost) if usage_before.total_cost else 0.0,
+ "gemini_calls": usage_before.gemini_calls or 0,
+ "mistral_calls": usage_before.mistral_calls or 0,
+ "usage_status": usage_before.usage_status.value if hasattr(usage_before.usage_status, 'value') else str(usage_before.usage_status)
+ }
+
if existing_subscription:
+ # This is a renewal/update - capture previous subscription state BEFORE updating
+ previous_period_start = existing_subscription.current_period_start
+ previous_period_end = existing_subscription.current_period_end
+ previous_plan = existing_subscription.plan
+ previous_plan_name = previous_plan.name if previous_plan else None
+ previous_plan_tier = previous_plan.tier.value if previous_plan else None
+
+ # Determine renewal type
+ if previous_plan and previous_plan.id == plan_id:
+ # Same plan - this is a renewal
+ renewal_type = "renewal"
+ elif previous_plan:
+ # Different plan - check if upgrade or downgrade
+ tier_order = {"free": 0, "basic": 1, "pro": 2, "enterprise": 3}
+ previous_tier_order = tier_order.get(previous_plan_tier or "free", 0)
+ new_tier_order = tier_order.get(plan.tier.value, 0)
+ if new_tier_order > previous_tier_order:
+ renewal_type = "upgrade"
+ elif new_tier_order < previous_tier_order:
+ renewal_type = "downgrade"
+ else:
+ renewal_type = "renewal" # Same tier, different plan name
+
+ # Get renewal count (how many times this user has renewed)
+ last_renewal = db.query(SubscriptionRenewalHistory).filter(
+ SubscriptionRenewalHistory.user_id == user_id
+ ).order_by(SubscriptionRenewalHistory.created_at.desc()).first()
+
+ if last_renewal:
+ renewal_count = last_renewal.renewal_count + 1
+ else:
+ renewal_count = 1 # First renewal
+
# Update existing subscription
existing_subscription.plan_id = plan_id
existing_subscription.billing_cycle = BillingCycle(billing_cycle)
@@ -552,7 +614,30 @@ async def subscribe_to_plan(
auto_renew=True
)
db.add(subscription)
-
+
+ db.commit()
+
+ # Create renewal history record AFTER subscription update (so we have the new period_end)
+ renewal_history = SubscriptionRenewalHistory(
+ user_id=user_id,
+ plan_id=plan_id,
+ plan_name=plan.name,
+ plan_tier=plan.tier.value,
+ previous_period_start=previous_period_start,
+ previous_period_end=previous_period_end,
+ new_period_start=now,
+ new_period_end=subscription.current_period_end,
+ billing_cycle=BillingCycle(billing_cycle),
+ renewal_type=renewal_type,
+ renewal_count=renewal_count,
+ previous_plan_name=previous_plan_name,
+ previous_plan_tier=previous_plan_tier,
+ usage_before_renewal=usage_before_snapshot, # Usage snapshot captured BEFORE renewal
+ payment_amount=plan.price_yearly if billing_cycle == 'yearly' else plan.price_monthly,
+ payment_status="paid", # Assume paid for now (can be updated if payment processing is added)
+ payment_date=now
+ )
+ db.add(renewal_history)
db.commit()
# Get current usage BEFORE reset for logging
@@ -883,4 +968,222 @@ async def get_dashboard_data(
except Exception as e:
logger.error(f"Error getting dashboard data: {e}")
- raise HTTPException(status_code=500, detail=str(e))
\ No newline at end of file
+ raise HTTPException(status_code=500, detail=str(e))
+
+@router.get("/renewal-history/{user_id}")
+async def get_renewal_history(
+ user_id: str,
+ limit: int = Query(50, ge=1, le=100, description="Number of records to return"),
+ offset: int = Query(0, ge=0, description="Pagination offset"),
+ current_user: Dict[str, Any] = Depends(get_current_user),
+ db: Session = Depends(get_db)
+) -> Dict[str, Any]:
+ """
+ Get subscription renewal history for a user.
+
+ Returns:
+ - List of renewal history records
+ - Total count for pagination
+ """
+ try:
+ # Verify user can only access their own data
+ if current_user.get('id') != user_id:
+ raise HTTPException(status_code=403, detail="Access denied")
+
+ # Get total count
+ total_count = db.query(SubscriptionRenewalHistory).filter(
+ SubscriptionRenewalHistory.user_id == user_id
+ ).count()
+
+ # Get paginated results, ordered by created_at descending (most recent first)
+ renewals = db.query(SubscriptionRenewalHistory).filter(
+ SubscriptionRenewalHistory.user_id == user_id
+ ).order_by(SubscriptionRenewalHistory.created_at.desc()).offset(offset).limit(limit).all()
+
+ # Format renewal history for response
+ renewal_history = []
+ for renewal in renewals:
+ renewal_history.append({
+ 'id': renewal.id,
+ 'plan_name': renewal.plan_name,
+ 'plan_tier': renewal.plan_tier,
+ 'previous_period_start': renewal.previous_period_start.isoformat() if renewal.previous_period_start else None,
+ 'previous_period_end': renewal.previous_period_end.isoformat() if renewal.previous_period_end else None,
+ 'new_period_start': renewal.new_period_start.isoformat() if renewal.new_period_start else None,
+ 'new_period_end': renewal.new_period_end.isoformat() if renewal.new_period_end else None,
+ 'billing_cycle': renewal.billing_cycle.value if renewal.billing_cycle else None,
+ 'renewal_type': renewal.renewal_type,
+ 'renewal_count': renewal.renewal_count,
+ 'previous_plan_name': renewal.previous_plan_name,
+ 'previous_plan_tier': renewal.previous_plan_tier,
+ 'usage_before_renewal': renewal.usage_before_renewal,
+ 'payment_amount': float(renewal.payment_amount) if renewal.payment_amount else 0.0,
+ 'payment_status': renewal.payment_status,
+ 'payment_date': renewal.payment_date.isoformat() if renewal.payment_date else None,
+ 'created_at': renewal.created_at.isoformat() if renewal.created_at else None
+ })
+
+ return {
+ "success": True,
+ "data": {
+ "renewals": renewal_history,
+ "total_count": total_count,
+ "limit": limit,
+ "offset": offset,
+ "has_more": (offset + limit) < total_count
+ }
+ }
+
+ except HTTPException:
+ raise
+ except Exception as e:
+ logger.error(f"Error getting renewal history: {e}", exc_info=True)
+ raise HTTPException(status_code=500, detail=str(e))
+
+@router.get("/usage-logs")
+async def get_usage_logs(
+ limit: int = Query(50, ge=1, le=5000, description="Number of logs to return"),
+ offset: int = Query(0, ge=0, description="Pagination offset"),
+ provider: Optional[str] = Query(None, description="Filter by provider"),
+ status_code: Optional[int] = Query(None, description="Filter by HTTP status code"),
+ billing_period: Optional[str] = Query(None, description="Filter by billing period (YYYY-MM)"),
+ current_user: Dict[str, Any] = Depends(get_current_user),
+ db: Session = Depends(get_db)
+) -> Dict[str, Any]:
+ """
+ Get API usage logs for the current user.
+
+ Query Params:
+ - limit: Number of logs to return (1-500, default: 50)
+ - offset: Pagination offset (default: 0)
+ - provider: Filter by provider (e.g., "gemini", "openai", "huggingface")
+ - status_code: Filter by HTTP status code (e.g., 200 for success, 400+ for errors)
+ - billing_period: Filter by billing period (YYYY-MM format)
+
+ Returns:
+ - List of usage logs with API call details
+ - Total count for pagination
+ """
+ try:
+ # Get user_id from current_user
+ user_id = str(current_user.get('id', '')) if current_user else None
+
+ if not user_id:
+ raise HTTPException(status_code=401, detail="User not authenticated")
+
+ # Build query
+ query = db.query(APIUsageLog).filter(
+ APIUsageLog.user_id == user_id
+ )
+
+ # Apply filters
+ if provider:
+ provider_lower = provider.lower()
+ # Handle special case: huggingface maps to MISTRAL enum in database
+ if provider_lower == "huggingface":
+ provider_enum = APIProvider.MISTRAL
+ else:
+ try:
+ provider_enum = APIProvider(provider_lower)
+ except ValueError:
+ # Invalid provider, return empty results
+ return {
+ "logs": [],
+ "total_count": 0,
+ "limit": limit,
+ "offset": offset,
+ "has_more": False
+ }
+ query = query.filter(APIUsageLog.provider == provider_enum)
+
+ if status_code is not None:
+ query = query.filter(APIUsageLog.status_code == status_code)
+
+ if billing_period:
+ query = query.filter(APIUsageLog.billing_period == billing_period)
+
+ # Check and wrap logs if necessary (before getting count)
+ wrapping_service = LogWrappingService(db)
+ wrap_result = wrapping_service.check_and_wrap_logs(user_id)
+ if wrap_result.get('wrapped'):
+ logger.info(f"[UsageLogs] Log wrapping completed for user {user_id}: {wrap_result.get('message')}")
+ # Rebuild query after wrapping (in case filters changed)
+ query = db.query(APIUsageLog).filter(
+ APIUsageLog.user_id == user_id
+ )
+ # Reapply filters
+ if provider:
+ provider_lower = provider.lower()
+ if provider_lower == "huggingface":
+ provider_enum = APIProvider.MISTRAL
+ else:
+ try:
+ provider_enum = APIProvider(provider_lower)
+ except ValueError:
+ return {
+ "logs": [],
+ "total_count": 0,
+ "limit": limit,
+ "offset": offset,
+ "has_more": False
+ }
+ query = query.filter(APIUsageLog.provider == provider_enum)
+ if status_code is not None:
+ query = query.filter(APIUsageLog.status_code == status_code)
+ if billing_period:
+ query = query.filter(APIUsageLog.billing_period == billing_period)
+
+ # Get total count
+ total_count = query.count()
+
+ # Get paginated results, ordered by timestamp descending (most recent first)
+ logs = query.order_by(desc(APIUsageLog.timestamp)).offset(offset).limit(limit).all()
+
+ # Format logs for response
+ formatted_logs = []
+ for log in logs:
+ # Determine status based on status_code
+ status = 'success' if 200 <= log.status_code < 300 else 'failed'
+
+ # Handle provider display name - ALL MISTRAL enum logs are actually HuggingFace
+ # (HuggingFace always maps to MISTRAL enum in the database)
+ provider_display = log.provider.value if log.provider else None
+ if provider_display == "mistral":
+ # All MISTRAL provider logs are HuggingFace calls
+ provider_display = "huggingface"
+
+ formatted_logs.append({
+ 'id': log.id,
+ 'timestamp': log.timestamp.isoformat() if log.timestamp else None,
+ 'provider': provider_display,
+ 'model_used': log.model_used,
+ 'endpoint': log.endpoint,
+ 'method': log.method,
+ 'tokens_input': log.tokens_input or 0,
+ 'tokens_output': log.tokens_output or 0,
+ 'tokens_total': log.tokens_total or 0,
+ 'cost_input': float(log.cost_input) if log.cost_input else 0.0,
+ 'cost_output': float(log.cost_output) if log.cost_output else 0.0,
+ 'cost_total': float(log.cost_total) if log.cost_total else 0.0,
+ 'response_time': float(log.response_time) if log.response_time else 0.0,
+ 'status_code': log.status_code,
+ 'status': status,
+ 'error_message': log.error_message,
+ 'billing_period': log.billing_period,
+ 'retry_count': log.retry_count or 0,
+ 'is_aggregated': log.endpoint == "[AGGREGATED]" # Flag to indicate aggregated log
+ })
+
+ return {
+ "logs": formatted_logs,
+ "total_count": total_count,
+ "limit": limit,
+ "offset": offset,
+ "has_more": (offset + limit) < total_count
+ }
+
+ except HTTPException:
+ raise
+ except Exception as e:
+ logger.error(f"Error getting usage logs: {e}", exc_info=True)
+ raise HTTPException(status_code=500, detail=f"Failed to get usage logs: {str(e)}")
\ No newline at end of file
diff --git a/backend/api/wix_routes.py b/backend/api/wix_routes.py
index fb43aac2..2ceda9cc 100644
--- a/backend/api/wix_routes.py
+++ b/backend/api/wix_routes.py
@@ -498,7 +498,15 @@ async def get_test_authorization_url(state: Optional[str] = None) -> Dict[str, s
if not wix_service.client_id:
logger.warning("TEST: Wix Client ID not configured, returning mock URL")
return {
- "url": "https://www.wix.com/oauth/access?client_id=YOUR_CLIENT_ID&redirect_uri=http://localhost:3000/wix/callback&response_type=code&scope=BLOG.CREATE-DRAFT,BLOG.PUBLISH,MEDIA.MANAGE&code_challenge=test&code_challenge_method=S256",
+ "url": (
+ "https://www.wix.com/oauth/access?client_id=YOUR_CLIENT_ID"
+ "&redirect_uri=http://localhost:3000/wix/callback"
+ "&response_type=code&scope="
+ "BLOG.CREATE-DRAFT,BLOG.PUBLISH-POST,BLOG.READ-CATEGORY,"
+ "BLOG.CREATE-CATEGORY,BLOG.READ-TAG,BLOG.CREATE-TAG,"
+ "MEDIA.SITE_MEDIA_FILES_IMPORT"
+ "&code_challenge=test&code_challenge_method=S256"
+ ),
"state": state or "test_state",
"message": "WIX_CLIENT_ID not configured. Please set it in your .env file to get a real authorization URL."
}
@@ -573,9 +581,19 @@ async def test_publish_real(payload: Dict[str, Any]) -> Dict[str, Any]:
- Derives member_id server-side (required by Wix for third-party apps)
"""
try:
- access_token = payload.get("access_token")
- if not access_token:
+ # Normalize access_token from payload (could be string, dict, or other format)
+ from services.integrations.wix.utils import normalize_token_string
+ raw_access_token = payload.get("access_token")
+ if not raw_access_token:
raise HTTPException(status_code=400, detail="Missing access_token")
+
+ # Normalize token to string (handles dict with accessToken.value, int, etc.)
+ access_token = normalize_token_string(raw_access_token)
+ if not access_token:
+ # Fallback: try to convert to string directly
+ access_token = str(raw_access_token).strip()
+ if not access_token or access_token == "None":
+ raise HTTPException(status_code=400, detail="Invalid access_token format")
# Derive current member id from token (try local decode first, then API fallback)
member_id = wix_service.extract_member_id_from_access_token(access_token)
diff --git a/backend/app.py b/backend/app.py
index d028e1ae..b14fd7fc 100644
--- a/backend/app.py
+++ b/backend/app.py
@@ -16,7 +16,15 @@ from services.subscription import monitoring_middleware
from alwrity_utils import HealthChecker, RateLimiter, FrontendServing, RouterManager, OnboardingManager
# Load environment variables
-load_dotenv()
+# Try multiple locations for .env file
+from pathlib import Path
+backend_dir = Path(__file__).parent
+project_root = backend_dir.parent
+
+# Load from backend/.env first (higher priority), then root .env
+load_dotenv(backend_dir / '.env') # backend/.env
+load_dotenv(project_root / '.env') # root .env (fallback)
+load_dotenv() # CWD .env (fallback)
# Set up clean logging for end users
from logging_config import setup_clean_logging
@@ -318,6 +326,13 @@ async def startup_event():
from services.scheduler import get_scheduler
await get_scheduler().start()
+ # Check Wix API key configuration
+ wix_api_key = os.getenv('WIX_API_KEY')
+ if wix_api_key:
+ logger.warning(f"✅ WIX_API_KEY loaded ({len(wix_api_key)} chars, starts with '{wix_api_key[:10]}...')")
+ else:
+ logger.warning("⚠️ WIX_API_KEY not found in environment - Wix publishing may fail")
+
logger.info("ALwrity backend started successfully")
except Exception as e:
logger.error(f"Error during startup: {e}")
diff --git a/backend/models/oauth_token_monitoring_models.py b/backend/models/oauth_token_monitoring_models.py
index 259e6d00..842e4af4 100644
--- a/backend/models/oauth_token_monitoring_models.py
+++ b/backend/models/oauth_token_monitoring_models.py
@@ -26,7 +26,7 @@ class OAuthTokenMonitoringTask(Base):
platform = Column(String(50), nullable=False) # 'gsc', 'bing', 'wordpress', 'wix'
# Task Status
- status = Column(String(50), default='active') # 'active', 'failed', 'paused'
+ status = Column(String(50), default='active') # 'active', 'failed', 'paused', 'needs_intervention'
# Execution Tracking
last_check = Column(DateTime, nullable=True)
@@ -34,6 +34,10 @@ class OAuthTokenMonitoringTask(Base):
last_failure = Column(DateTime, nullable=True)
failure_reason = Column(Text, nullable=True)
+ # Failure Pattern Tracking
+ consecutive_failures = Column(Integer, default=0) # Count of consecutive failures
+ failure_pattern = Column(JSON, nullable=True) # JSON storing failure analysis
+
# Scheduling
next_check = Column(DateTime, nullable=True, index=True) # Next scheduled check time
diff --git a/backend/models/platform_insights_monitoring_models.py b/backend/models/platform_insights_monitoring_models.py
index 1f29e77a..c2ee77da 100644
--- a/backend/models/platform_insights_monitoring_models.py
+++ b/backend/models/platform_insights_monitoring_models.py
@@ -27,7 +27,7 @@ class PlatformInsightsTask(Base):
site_url = Column(String(500), nullable=True) # Optional: specific site URL
# Task Status
- status = Column(String(50), default='active') # 'active', 'failed', 'paused'
+ status = Column(String(50), default='active') # 'active', 'failed', 'paused', 'needs_intervention'
# Execution Tracking
last_check = Column(DateTime, nullable=True)
@@ -35,6 +35,10 @@ class PlatformInsightsTask(Base):
last_failure = Column(DateTime, nullable=True)
failure_reason = Column(Text, nullable=True)
+ # Failure Pattern Tracking
+ consecutive_failures = Column(Integer, default=0) # Count of consecutive failures
+ failure_pattern = Column(JSON, nullable=True) # JSON storing failure analysis
+
# Scheduling
next_check = Column(DateTime, nullable=True, index=True) # Next scheduled check time
diff --git a/backend/models/story_models.py b/backend/models/story_models.py
new file mode 100644
index 00000000..d1d78459
--- /dev/null
+++ b/backend/models/story_models.py
@@ -0,0 +1,262 @@
+"""
+Story Writer Models
+
+Pydantic models for story generation API requests and responses.
+"""
+
+from pydantic import BaseModel, Field
+from typing import List, Optional, Dict, Any, Union
+
+
+class StoryGenerationRequest(BaseModel):
+ """Request model for story generation."""
+ persona: str = Field(..., description="The persona statement for the author")
+ story_setting: str = Field(..., description="The setting of the story")
+ character_input: str = Field(..., description="The characters in the story")
+ plot_elements: str = Field(..., description="The plot elements of the story")
+ writing_style: str = Field(..., description="The writing style (e.g., Formal, Casual, Poetic, Humorous)")
+ story_tone: str = Field(..., description="The tone of the story (e.g., Dark, Uplifting, Suspenseful, Whimsical)")
+ narrative_pov: str = Field(..., description="The narrative point of view (e.g., First Person, Third Person Limited, Third Person Omniscient)")
+ audience_age_group: str = Field(..., description="The target audience age group (e.g., Children, Young Adults, Adults)")
+ content_rating: str = Field(..., description="The content rating (e.g., G, PG, PG-13, R)")
+ ending_preference: str = Field(..., description="The preferred ending (e.g., Happy, Tragic, Cliffhanger, Twist)")
+ story_length: str = Field(default="Medium", description="Target story length (Short: >1000 words, Medium: >5000 words, Long: >10000 words)")
+ enable_explainer: bool = Field(default=True, description="Enable explainer features")
+ enable_illustration: bool = Field(default=True, description="Enable illustration features")
+ enable_video_narration: bool = Field(default=True, description="Enable story video and narration features")
+
+ # Image generation settings
+ image_provider: Optional[str] = Field(default=None, description="Image generation provider (gemini, huggingface, stability)")
+ image_width: int = Field(default=1024, description="Image width in pixels")
+ image_height: int = Field(default=1024, description="Image height in pixels")
+ image_model: Optional[str] = Field(default=None, description="Image generation model")
+
+ # Video generation settings
+ video_fps: int = Field(default=24, description="Frames per second for video")
+ video_transition_duration: float = Field(default=0.5, description="Duration of transitions between scenes in seconds")
+
+ # Audio generation settings
+ audio_provider: Optional[str] = Field(default="gtts", description="TTS provider (gtts, pyttsx3)")
+ audio_lang: str = Field(default="en", description="Language code for TTS")
+ audio_slow: bool = Field(default=False, description="Whether to speak slowly (gTTS only)")
+ audio_rate: int = Field(default=150, description="Speech rate (pyttsx3 only)")
+
+
+class StorySetupGenerationRequest(BaseModel):
+ """Request model for AI story setup generation."""
+ story_idea: str = Field(..., description="Basic story idea or information from the user")
+
+
+class StorySetupOption(BaseModel):
+ """A single story setup option."""
+ persona: str = Field(..., description="The persona statement for the author")
+ story_setting: str = Field(..., description="The setting of the story")
+ character_input: str = Field(..., description="The characters in the story")
+ plot_elements: str = Field(..., description="The plot elements of the story")
+ writing_style: str = Field(..., description="The writing style")
+ story_tone: str = Field(..., description="The tone of the story")
+ narrative_pov: str = Field(..., description="The narrative point of view")
+ audience_age_group: str = Field(..., description="The target audience age group")
+ content_rating: str = Field(..., description="The content rating")
+ ending_preference: str = Field(..., description="The preferred ending")
+ story_length: str = Field(default="Medium", description="Target story length (Short: >1000 words, Medium: >5000 words, Long: >10000 words)")
+ premise: str = Field(..., description="The story premise (1-2 sentences)")
+ reasoning: str = Field(..., description="Brief reasoning for this setup option")
+
+ # Image generation settings
+ image_provider: Optional[str] = Field(default=None, description="Image generation provider (gemini, huggingface, stability)")
+ image_width: int = Field(default=1024, description="Image width in pixels")
+ image_height: int = Field(default=1024, description="Image height in pixels")
+ image_model: Optional[str] = Field(default=None, description="Image generation model")
+
+ # Video generation settings
+ video_fps: int = Field(default=24, description="Frames per second for video")
+ video_transition_duration: float = Field(default=0.5, description="Duration of transitions between scenes in seconds")
+
+ # Audio generation settings
+ audio_provider: Optional[str] = Field(default="gtts", description="TTS provider (gtts, pyttsx3)")
+ audio_lang: str = Field(default="en", description="Language code for TTS")
+ audio_slow: bool = Field(default=False, description="Whether to speak slowly (gTTS only)")
+ audio_rate: int = Field(default=150, description="Speech rate (pyttsx3 only)")
+
+
+class StorySetupGenerationResponse(BaseModel):
+ """Response model for story setup generation."""
+ options: List[StorySetupOption] = Field(..., description="Three story setup options")
+ success: bool = Field(default=True, description="Whether the generation was successful")
+
+
+class StoryScene(BaseModel):
+ """Model for a story scene."""
+ scene_number: int = Field(..., description="Scene number")
+ title: str = Field(..., description="Scene title")
+ description: str = Field(..., description="Scene description")
+ image_prompt: str = Field(..., description="Image prompt for scene visualization")
+ audio_narration: str = Field(..., description="Audio narration text for the scene")
+ character_descriptions: List[str] = Field(default_factory=list, description="Character descriptions in the scene")
+ key_events: List[str] = Field(default_factory=list, description="Key events in the scene")
+
+
+class StoryStartRequest(StoryGenerationRequest):
+ """Request model for story start generation."""
+ premise: str = Field(..., description="The story premise")
+ outline: Union[str, List[StoryScene], List[Dict[str, Any]]] = Field(..., description="The story outline (text or structured scenes)")
+
+
+class StoryPremiseResponse(BaseModel):
+ """Response model for premise generation."""
+ premise: str = Field(..., description="Generated story premise")
+ success: bool = Field(default=True, description="Whether the generation was successful")
+ task_id: Optional[str] = Field(None, description="Task ID for async operations")
+
+
+class StoryOutlineResponse(BaseModel):
+ """Response model for outline generation."""
+ outline: Union[str, List[StoryScene]] = Field(..., description="Generated story outline (text or structured scenes)")
+ success: bool = Field(default=True, description="Whether the generation was successful")
+ task_id: Optional[str] = Field(None, description="Task ID for async operations")
+ is_structured: bool = Field(default=False, description="Whether the outline is structured (scenes) or plain text")
+
+
+class StoryContentResponse(BaseModel):
+ """Response model for story content generation."""
+ story: str = Field(..., description="Generated story content")
+ premise: Optional[str] = Field(None, description="Story premise")
+ outline: Optional[str] = Field(None, description="Story outline")
+ is_complete: bool = Field(default=False, description="Whether the story is complete")
+ iterations: int = Field(default=0, description="Number of continuation iterations")
+ success: bool = Field(default=True, description="Whether the generation was successful")
+ task_id: Optional[str] = Field(None, description="Task ID for async operations")
+
+
+class StoryFullGenerationResponse(BaseModel):
+ """Response model for full story generation."""
+ premise: str = Field(..., description="Generated story premise")
+ outline: str = Field(..., description="Generated story outline")
+ story: str = Field(..., description="Generated complete story")
+ is_complete: bool = Field(default=False, description="Whether the story is complete")
+ iterations: int = Field(default=0, description="Number of continuation iterations")
+ success: bool = Field(default=True, description="Whether the generation was successful")
+ task_id: Optional[str] = Field(None, description="Task ID for async operations")
+
+
+class StoryContinueRequest(BaseModel):
+ """Request model for continuing story generation."""
+ premise: str = Field(..., description="The story premise")
+ outline: Union[str, List[StoryScene], List[Dict[str, Any]]] = Field(..., description="The story outline (text or structured scenes)")
+ story_text: str = Field(..., description="Current story text to continue from")
+ persona: str = Field(..., description="The persona statement for the author")
+ story_setting: str = Field(..., description="The setting of the story")
+ character_input: str = Field(..., description="The characters in the story")
+ plot_elements: str = Field(..., description="The plot elements of the story")
+ writing_style: str = Field(..., description="The writing style")
+ story_tone: str = Field(..., description="The tone of the story")
+ narrative_pov: str = Field(..., description="The narrative point of view")
+ audience_age_group: str = Field(..., description="The target audience age group")
+ content_rating: str = Field(..., description="The content rating")
+ ending_preference: str = Field(..., description="The preferred ending")
+ story_length: str = Field(default="Medium", description="Target story length (Short: >1000 words, Medium: >5000 words, Long: >10000 words)")
+
+
+class StoryContinueResponse(BaseModel):
+ """Response model for story continuation."""
+ continuation: str = Field(..., description="Generated story continuation")
+ is_complete: bool = Field(default=False, description="Whether the story is complete (contains IAMDONE)")
+ success: bool = Field(default=True, description="Whether the generation was successful")
+
+
+class TaskStatus(BaseModel):
+ """Task status model."""
+ task_id: str = Field(..., description="Task ID")
+ status: str = Field(..., description="Task status (pending, processing, completed, failed)")
+ progress: Optional[float] = Field(None, description="Progress percentage (0-100)")
+ message: Optional[str] = Field(None, description="Progress message")
+ result: Optional[Dict[str, Any]] = Field(None, description="Task result when completed")
+ error: Optional[str] = Field(None, description="Error message if failed")
+ created_at: Optional[str] = Field(None, description="Task creation timestamp")
+ updated_at: Optional[str] = Field(None, description="Task last update timestamp")
+
+
+class StoryImageGenerationRequest(BaseModel):
+ """Request model for image generation."""
+ scenes: List[StoryScene] = Field(..., description="List of scenes to generate images for")
+ provider: Optional[str] = Field(None, description="Image generation provider (gemini, huggingface, stability)")
+ width: Optional[int] = Field(default=1024, description="Image width")
+ height: Optional[int] = Field(default=1024, description="Image height")
+ model: Optional[str] = Field(None, description="Image generation model")
+
+
+class StoryImageResult(BaseModel):
+ """Model for a generated image result."""
+ scene_number: int = Field(..., description="Scene number")
+ scene_title: str = Field(..., description="Scene title")
+ image_filename: str = Field(..., description="Image filename")
+ image_url: str = Field(..., description="Image URL")
+ width: int = Field(..., description="Image width")
+ height: int = Field(..., description="Image height")
+ provider: str = Field(..., description="Image generation provider")
+ model: Optional[str] = Field(None, description="Image generation model")
+ seed: Optional[int] = Field(None, description="Image generation seed")
+ error: Optional[str] = Field(None, description="Error message if generation failed")
+
+
+class StoryImageGenerationResponse(BaseModel):
+ """Response model for image generation."""
+ images: List[StoryImageResult] = Field(..., description="List of generated images")
+ success: bool = Field(default=True, description="Whether the generation was successful")
+ task_id: Optional[str] = Field(None, description="Task ID for async operations")
+
+
+class StoryAudioGenerationRequest(BaseModel):
+ """Request model for audio generation."""
+ scenes: List[StoryScene] = Field(..., description="List of scenes to generate audio for")
+ provider: Optional[str] = Field(default="gtts", description="TTS provider (gtts, pyttsx3)")
+ lang: Optional[str] = Field(default="en", description="Language code for TTS")
+ slow: Optional[bool] = Field(default=False, description="Whether to speak slowly (gTTS only)")
+ rate: Optional[int] = Field(default=150, description="Speech rate (pyttsx3 only)")
+
+
+class StoryAudioResult(BaseModel):
+ """Model for a generated audio result."""
+ scene_number: int = Field(..., description="Scene number")
+ scene_title: str = Field(..., description="Scene title")
+ audio_filename: str = Field(..., description="Audio filename")
+ audio_url: str = Field(..., description="Audio URL")
+ provider: str = Field(..., description="TTS provider")
+ file_size: int = Field(..., description="Audio file size in bytes")
+ error: Optional[str] = Field(None, description="Error message if generation failed")
+
+
+class StoryAudioGenerationResponse(BaseModel):
+ """Response model for audio generation."""
+ audio_files: List[StoryAudioResult] = Field(..., description="List of generated audio files")
+ success: bool = Field(default=True, description="Whether the generation was successful")
+ task_id: Optional[str] = Field(None, description="Task ID for async operations")
+
+
+class StoryVideoGenerationRequest(BaseModel):
+ """Request model for video generation."""
+ scenes: List[StoryScene] = Field(..., description="List of scenes to generate video for")
+ image_urls: List[str] = Field(..., description="List of image URLs for each scene")
+ audio_urls: List[str] = Field(..., description="List of audio URLs for each scene")
+ story_title: Optional[str] = Field(default="Story", description="Title of the story")
+ fps: Optional[int] = Field(default=24, description="Frames per second for video")
+ transition_duration: Optional[float] = Field(default=0.5, description="Duration of transitions between scenes")
+
+
+class StoryVideoResult(BaseModel):
+ """Model for a generated video result."""
+ video_filename: str = Field(..., description="Video filename")
+ video_url: str = Field(..., description="Video URL")
+ duration: float = Field(..., description="Video duration in seconds")
+ fps: int = Field(..., description="Frames per second")
+ file_size: int = Field(..., description="Video file size in bytes")
+ num_scenes: int = Field(..., description="Number of scenes in the video")
+ error: Optional[str] = Field(None, description="Error message if generation failed")
+
+
+class StoryVideoGenerationResponse(BaseModel):
+ """Response model for video generation."""
+ video: StoryVideoResult = Field(..., description="Generated video")
+ success: bool = Field(default=True, description="Whether the generation was successful")
+ task_id: Optional[str] = Field(None, description="Task ID for async operations")
diff --git a/backend/models/subscription_models.py b/backend/models/subscription_models.py
index a6c73945..0b1e12b9 100644
--- a/backend/models/subscription_models.py
+++ b/backend/models/subscription_models.py
@@ -323,4 +323,54 @@ class BillingHistory(Base):
# Metadata
created_at = Column(DateTime, default=datetime.utcnow)
- updated_at = Column(DateTime, default=datetime.utcnow, onupdate=datetime.utcnow)
\ No newline at end of file
+ updated_at = Column(DateTime, default=datetime.utcnow, onupdate=datetime.utcnow)
+
+class SubscriptionRenewalHistory(Base):
+ """Historical record of subscription renewals and expiration events."""
+
+ __tablename__ = "subscription_renewal_history"
+
+ id = Column(Integer, primary_key=True)
+ user_id = Column(String(100), nullable=False)
+
+ # Subscription Details
+ plan_id = Column(Integer, ForeignKey('subscription_plans.id'), nullable=False)
+ plan_name = Column(String(50), nullable=False)
+ plan_tier = Column(String(20), nullable=False) # e.g., "free", "basic", "pro", "enterprise"
+
+ # Period Information
+ previous_period_start = Column(DateTime, nullable=True) # Start of the previous period (if renewal)
+ previous_period_end = Column(DateTime, nullable=True) # End of the previous period (when it expired)
+ new_period_start = Column(DateTime, nullable=False) # Start of the new period (when renewed)
+ new_period_end = Column(DateTime, nullable=False) # End of the new period
+
+ # Billing Cycle
+ billing_cycle = Column(Enum(BillingCycle), nullable=False) # "monthly" or "yearly"
+
+ # Renewal Information
+ renewal_type = Column(String(20), nullable=False) # "new", "renewal", "upgrade", "downgrade"
+ renewal_count = Column(Integer, default=0) # Sequential renewal number (1st renewal, 2nd renewal, etc.)
+
+ # Previous Subscription Snapshot (before renewal)
+ previous_plan_name = Column(String(50), nullable=True)
+ previous_plan_tier = Column(String(20), nullable=True)
+
+ # Usage Summary Before Renewal (snapshot)
+ usage_before_renewal = Column(JSON, nullable=True) # Snapshot of usage before renewal
+
+ # Payment Information
+ payment_amount = Column(Float, default=0.0)
+ payment_status = Column(String(20), default="pending") # "pending", "paid", "failed"
+ payment_date = Column(DateTime, nullable=True)
+ stripe_invoice_id = Column(String(100), nullable=True)
+
+ # Metadata
+ created_at = Column(DateTime, default=datetime.utcnow)
+
+ # Relationships
+ plan = relationship("SubscriptionPlan")
+
+ # Indexes for performance
+ __table_args__ = (
+ {'mysql_engine': 'InnoDB'},
+ )
\ No newline at end of file
diff --git a/backend/models/website_analysis_monitoring_models.py b/backend/models/website_analysis_monitoring_models.py
index d20a92ba..c71c1619 100644
--- a/backend/models/website_analysis_monitoring_models.py
+++ b/backend/models/website_analysis_monitoring_models.py
@@ -28,7 +28,7 @@ class WebsiteAnalysisTask(Base):
competitor_id = Column(String(255), nullable=True) # For competitor tasks (domain or identifier)
# Task Status
- status = Column(String(50), default='active') # 'active', 'failed', 'paused'
+ status = Column(String(50), default='active') # 'active', 'failed', 'paused', 'needs_intervention'
# Execution Tracking
last_check = Column(DateTime, nullable=True)
@@ -36,6 +36,10 @@ class WebsiteAnalysisTask(Base):
last_failure = Column(DateTime, nullable=True)
failure_reason = Column(Text, nullable=True)
+ # Failure Pattern Tracking
+ consecutive_failures = Column(Integer, default=0) # Count of consecutive failures
+ failure_pattern = Column(JSON, nullable=True) # JSON storing failure analysis
+
# Scheduling
next_check = Column(DateTime, nullable=True, index=True) # Next scheduled check time
frequency_days = Column(Integer, default=10) # Recurring frequency in days
diff --git a/backend/requirements.txt b/backend/requirements.txt
index 76557032..5734dd24 100644
--- a/backend/requirements.txt
+++ b/backend/requirements.txt
@@ -56,6 +56,15 @@ Pillow>=10.0.0
huggingface_hub>=0.24.0
scikit-learn>=1.3.0
+# Text-to-Speech (TTS) dependencies
+gtts>=2.4.0
+pyttsx3>=2.90
+
+# Video composition dependencies
+moviepy>=1.0.3
+imageio>=2.31.0
+imageio-ffmpeg>=0.4.9
+
# Testing dependencies
pytest>=7.4.0
pytest-asyncio>=0.21.0
diff --git a/backend/scripts/check_wix_config.py b/backend/scripts/check_wix_config.py
new file mode 100644
index 00000000..e700f472
--- /dev/null
+++ b/backend/scripts/check_wix_config.py
@@ -0,0 +1,143 @@
+"""
+Quick diagnostic script to check Wix configuration.
+
+Run this to verify your WIX_API_KEY is properly loaded.
+
+Usage:
+ python backend/scripts/check_wix_config.py
+"""
+
+import os
+import sys
+from pathlib import Path
+
+# Add parent directory to path
+sys.path.insert(0, str(Path(__file__).parent.parent))
+
+def check_wix_config():
+ """Check if Wix configuration is properly set up."""
+
+ print("\n" + "="*60)
+ print("🔍 WIX CONFIGURATION DIAGNOSTIC")
+ print("="*60 + "\n")
+
+ # 1. Check if .env file exists
+ env_locations = [
+ Path.cwd() / ".env",
+ Path.cwd() / "backend" / ".env",
+ Path.cwd() / ".env.local",
+ ]
+
+ print("📁 Checking for .env files:")
+ env_file_found = False
+ for env_path in env_locations:
+ exists = env_path.exists()
+ status = "✅ FOUND" if exists else "❌ NOT FOUND"
+ print(f" {status}: {env_path}")
+ if exists:
+ env_file_found = True
+
+ if not env_file_found:
+ print("\n⚠️ WARNING: No .env file found!")
+ print(" Create a .env file in your project root.")
+
+ print("\n" + "-"*60 + "\n")
+
+ # 2. Try loading .env file
+ try:
+ from dotenv import load_dotenv
+ load_dotenv()
+ print("✅ dotenv loaded successfully")
+ except ImportError:
+ print("❌ python-dotenv not installed")
+ print(" Install: pip install python-dotenv")
+ except Exception as e:
+ print(f"⚠️ Error loading .env: {e}")
+
+ print("\n" + "-"*60 + "\n")
+
+ # 3. Check WIX_API_KEY environment variable
+ print("🔑 Checking WIX_API_KEY environment variable:")
+ api_key = os.getenv('WIX_API_KEY')
+
+ if not api_key:
+ print(" ❌ NOT FOUND")
+ print("\n⚠️ CRITICAL: WIX_API_KEY is not set!")
+ print("\nTo fix:")
+ print(" 1. Add this line to your .env file:")
+ print(" WIX_API_KEY=your_api_key_from_wix_dashboard")
+ print(" 2. Restart your backend server")
+ print(" 3. Run this script again to verify")
+ return False
+
+ print(" ✅ FOUND")
+ print(f" Length: {len(api_key)} characters")
+ print(f" Preview: {api_key[:30]}...")
+
+ # 4. Validate API key format
+ print("\n" + "-"*60 + "\n")
+ print("🔍 Validating API key format:")
+
+ if api_key.startswith("JWS."):
+ print(" ✅ Starts with 'JWS.' (correct format)")
+ else:
+ print(f" ⚠️ Doesn't start with 'JWS.' (got: {api_key[:10]}...)")
+ print(" This might not be a valid Wix API key")
+
+ if len(api_key) > 200:
+ print(f" ✅ Length looks correct ({len(api_key)} chars)")
+ else:
+ print(f" ⚠️ API key seems too short ({len(api_key)} chars)")
+ print(" Wix API keys are typically 500+ characters")
+
+ dot_count = api_key.count('.')
+ print(f" 📊 Contains {dot_count} dots (JWT tokens have 2+ dots)")
+
+ # 5. Test import of Wix services
+ print("\n" + "-"*60 + "\n")
+ print("📦 Testing Wix service imports:")
+
+ try:
+ from services.integrations.wix.auth_utils import get_wix_api_key
+ test_key = get_wix_api_key()
+
+ if test_key:
+ print(" ✅ auth_utils.get_wix_api_key() works")
+ print(f" ✅ Returned key length: {len(test_key)}")
+ print(f" ✅ Keys match: {test_key == api_key}")
+ else:
+ print(" ❌ auth_utils.get_wix_api_key() returned None")
+ print(" Even though os.getenv('WIX_API_KEY') found it!")
+ print(" This indicates an environment loading issue.")
+ except Exception as e:
+ print(f" ❌ Error importing: {e}")
+
+ # 6. Final summary
+ print("\n" + "="*60)
+ print("📋 SUMMARY")
+ print("="*60 + "\n")
+
+ if api_key and len(api_key) > 200 and api_key.startswith("JWS."):
+ print("✅ Configuration looks GOOD!")
+ print("\nNext steps:")
+ print(" 1. Restart your backend server")
+ print(" 2. Try publishing a blog post")
+ print(" 3. Check logs for 'Using API key' messages")
+ print(" 4. Verify no 403 Forbidden errors")
+ else:
+ print("❌ Configuration has ISSUES!")
+ print("\nPlease review the warnings above and:")
+ print(" 1. Ensure WIX_API_KEY is set in your .env file")
+ print(" 2. Verify the API key is correct (from Wix Dashboard)")
+ print(" 3. Restart your backend server")
+ print(" 4. Run this script again")
+
+ print("\n" + "="*60 + "\n")
+
+ return bool(api_key)
+
+
+if __name__ == "__main__":
+ success = check_wix_config()
+ sys.exit(0 if success else 1)
+
diff --git a/backend/scripts/run_failure_tracking_migration.py b/backend/scripts/run_failure_tracking_migration.py
new file mode 100644
index 00000000..3f871072
--- /dev/null
+++ b/backend/scripts/run_failure_tracking_migration.py
@@ -0,0 +1,85 @@
+"""
+Script to run the failure tracking migration.
+Adds consecutive_failures and failure_pattern columns to task tables.
+"""
+
+import sqlite3
+import os
+import sys
+
+# Add parent directory to path to import migration
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+def run_migration():
+ """Run the failure tracking migration."""
+ # Get database path
+ db_path = os.getenv('DATABASE_URL', 'sqlite:///alwrity.db')
+
+ # Extract path from SQLite URL if needed
+ if db_path.startswith('sqlite:///'):
+ db_path = db_path.replace('sqlite:///', '')
+
+ if not os.path.exists(db_path):
+ print(f"Database not found at {db_path}")
+ return False
+
+ print(f"Running migration on database: {db_path}")
+
+ try:
+ conn = sqlite3.connect(db_path)
+ cursor = conn.cursor()
+
+ # Read migration SQL
+ migration_file = os.path.join(
+ os.path.dirname(os.path.dirname(os.path.abspath(__file__))),
+ 'database',
+ 'migrations',
+ 'add_failure_tracking_to_tasks.sql'
+ )
+
+ if not os.path.exists(migration_file):
+ print(f"Migration file not found: {migration_file}")
+ return False
+
+ with open(migration_file, 'r') as f:
+ migration_sql = f.read()
+
+ # Execute migration (SQLite doesn't support multiple statements in execute, so split)
+ statements = [s.strip() for s in migration_sql.split(';') if s.strip()]
+
+ for statement in statements:
+ try:
+ cursor.execute(statement)
+ print(f"✓ Executed: {statement[:50]}...")
+ except sqlite3.OperationalError as e:
+ # Column might already exist - that's okay
+ if 'duplicate column name' in str(e).lower() or 'already exists' in str(e).lower():
+ print(f"⚠ Column already exists (skipping): {statement[:50]}...")
+ else:
+ raise
+
+ conn.commit()
+ print("\n✅ Migration completed successfully!")
+
+ # Verify columns were added
+ cursor.execute("PRAGMA table_info(oauth_token_monitoring_tasks)")
+ columns = [row[1] for row in cursor.fetchall()]
+
+ if 'consecutive_failures' in columns and 'failure_pattern' in columns:
+ print("✓ Verified: consecutive_failures and failure_pattern columns exist")
+ else:
+ print("⚠ Warning: Could not verify columns were added")
+
+ conn.close()
+ return True
+
+ except Exception as e:
+ print(f"❌ Error running migration: {e}")
+ import traceback
+ traceback.print_exc()
+ return False
+
+if __name__ == "__main__":
+ success = run_migration()
+ sys.exit(0 if success else 1)
+
diff --git a/backend/services/blog_writer/content/introduction_generator.py b/backend/services/blog_writer/content/introduction_generator.py
new file mode 100644
index 00000000..14451d27
--- /dev/null
+++ b/backend/services/blog_writer/content/introduction_generator.py
@@ -0,0 +1,186 @@
+"""
+Introduction Generator - Generates varied blog introductions based on content and research.
+
+Generates 3 different introduction options for the user to choose from.
+"""
+
+from typing import Dict, Any, List
+from loguru import logger
+
+from models.blog_models import BlogResearchResponse, BlogOutlineSection
+
+
+class IntroductionGenerator:
+ """Generates blog introductions using research and content data."""
+
+ def __init__(self):
+ """Initialize the introduction generator."""
+ pass
+
+ def build_introduction_prompt(
+ self,
+ blog_title: str,
+ research: BlogResearchResponse,
+ outline: List[BlogOutlineSection],
+ sections_content: Dict[str, str],
+ primary_keywords: List[str],
+ search_intent: str
+ ) -> str:
+ """Build a prompt for generating blog introductions."""
+
+ # Extract key research insights
+ keyword_analysis = research.keyword_analysis or {}
+ content_angles = research.suggested_angles or []
+
+ # Get a summary of the first few sections for context
+ section_summaries = []
+ for i, section in enumerate(outline[:3], 1):
+ section_id = section.id
+ content = sections_content.get(section_id, '')
+ if content:
+ # Take first 200 chars as summary
+ summary = content[:200] + '...' if len(content) > 200 else content
+ section_summaries.append(f"{i}. {section.heading}: {summary}")
+
+ sections_text = '\n'.join(section_summaries) if section_summaries else "Content sections are being generated."
+
+ primary_kw_text = ', '.join(primary_keywords) if primary_keywords else "the topic"
+ content_angle_text = ', '.join(content_angles[:3]) if content_angles else "General insights"
+
+ return f"""Generate exactly 3 varied blog introductions for the following blog post.
+
+BLOG TITLE: {blog_title}
+
+PRIMARY KEYWORDS: {primary_kw_text}
+SEARCH INTENT: {search_intent}
+CONTENT ANGLES: {content_angle_text}
+
+BLOG CONTENT SUMMARY:
+{sections_text}
+
+REQUIREMENTS FOR EACH INTRODUCTION:
+- 80-120 words in length
+- Hook the reader immediately with a compelling opening
+- Clearly state the value proposition and what readers will learn
+- Include the primary keyword naturally within the first 2 sentences
+- Each introduction should have a different angle/approach:
+ 1. First: Problem-focused (highlight the challenge readers face)
+ 2. Second: Benefit-focused (emphasize the value and outcomes)
+ 3. Third: Story/statistic-focused (use a compelling fact or narrative hook)
+- Maintain a professional yet engaging tone
+- Avoid generic phrases - be specific and benefit-driven
+
+Return ONLY a JSON array of exactly 3 introductions:
+[
+ "First introduction (80-120 words, problem-focused)",
+ "Second introduction (80-120 words, benefit-focused)",
+ "Third introduction (80-120 words, story/statistic-focused)"
+]"""
+
+ def get_introduction_schema(self) -> Dict[str, Any]:
+ """Get the JSON schema for introduction generation."""
+ return {
+ "type": "array",
+ "items": {
+ "type": "string",
+ "minLength": 80,
+ "maxLength": 150
+ },
+ "minItems": 3,
+ "maxItems": 3
+ }
+
+ async def generate_introductions(
+ self,
+ blog_title: str,
+ research: BlogResearchResponse,
+ outline: List[BlogOutlineSection],
+ sections_content: Dict[str, str],
+ primary_keywords: List[str],
+ search_intent: str,
+ user_id: str
+ ) -> List[str]:
+ """Generate 3 varied blog introductions.
+
+ Args:
+ blog_title: The blog post title
+ research: Research data with keywords and insights
+ outline: Blog outline sections
+ sections_content: Dictionary mapping section IDs to their content
+ primary_keywords: Primary keywords for the blog
+ search_intent: Search intent (informational, commercial, etc.)
+ user_id: User ID for API calls
+
+ Returns:
+ List of 3 introduction options
+ """
+ from services.llm_providers.main_text_generation import llm_text_gen
+
+ if not user_id:
+ raise ValueError("user_id is required for introduction generation")
+
+ # Build prompt
+ prompt = self.build_introduction_prompt(
+ blog_title=blog_title,
+ research=research,
+ outline=outline,
+ sections_content=sections_content,
+ primary_keywords=primary_keywords,
+ search_intent=search_intent
+ )
+
+ # Get schema
+ schema = self.get_introduction_schema()
+
+ logger.info(f"Generating blog introductions for user {user_id}")
+
+ try:
+ # Generate introductions using structured JSON response
+ result = llm_text_gen(
+ prompt=prompt,
+ json_struct=schema,
+ system_prompt="You are an expert content writer specializing in creating compelling blog introductions that hook readers and clearly communicate value.",
+ user_id=user_id
+ )
+
+ # Handle response - could be array directly or wrapped in dict
+ if isinstance(result, list):
+ introductions = result
+ elif isinstance(result, dict):
+ # Try common keys
+ introductions = result.get('introductions', result.get('options', result.get('intros', [])))
+ if not introductions and isinstance(result.get('response'), list):
+ introductions = result['response']
+ else:
+ logger.warning(f"Unexpected introduction generation result type: {type(result)}")
+ introductions = []
+
+ # Validate and clean introductions
+ cleaned_introductions = []
+ for intro in introductions:
+ if isinstance(intro, str) and len(intro.strip()) >= 50: # Minimum reasonable length
+ cleaned = intro.strip()
+ # Ensure it's within reasonable bounds
+ if len(cleaned) <= 200: # Allow slight overflow for quality
+ cleaned_introductions.append(cleaned)
+
+ # Ensure we have exactly 3 introductions
+ if len(cleaned_introductions) < 3:
+ logger.warning(f"Generated only {len(cleaned_introductions)} introductions, expected 3")
+ # Pad with placeholder if needed
+ while len(cleaned_introductions) < 3:
+ cleaned_introductions.append(f"{blog_title} - A comprehensive guide covering essential insights and practical strategies.")
+
+ # Return exactly 3 introductions
+ return cleaned_introductions[:3]
+
+ except Exception as e:
+ logger.error(f"Failed to generate introductions: {e}")
+ # Fallback: generate simple introductions
+ fallback_introductions = [
+ f"In this comprehensive guide, we'll explore {primary_keywords[0] if primary_keywords else 'essential insights'} and provide actionable strategies.",
+ f"Discover everything you need to know about {primary_keywords[0] if primary_keywords else 'this topic'} and how it can transform your approach.",
+ f"Whether you're new to {primary_keywords[0] if primary_keywords else 'this topic'} or looking to deepen your understanding, this guide has you covered."
+ ]
+ return fallback_introductions
+
diff --git a/backend/services/blog_writer/outline/prompt_builder.py b/backend/services/blog_writer/outline/prompt_builder.py
index b18b9972..1c52169b 100644
--- a/backend/services/blog_writer/outline/prompt_builder.py
+++ b/backend/services/blog_writer/outline/prompt_builder.py
@@ -5,7 +5,6 @@ Constructs comprehensive prompts with research data, keywords, and strategic req
"""
from typing import Dict, Any, List
-from loguru import logger
class PromptBuilder:
@@ -23,7 +22,18 @@ class PromptBuilder:
# Use the filtered research data (already cleaned by ResearchDataFilter)
research = request.research
- return f"""Create a comprehensive blog outline for: {', '.join(primary_keywords)}
+ primary_kw_text = ', '.join(primary_keywords) if primary_keywords else (request.topic or ', '.join(getattr(request.research, 'original_keywords', []) or ['the target topic']))
+ secondary_kw_text = ', '.join(secondary_keywords) if secondary_keywords else "None provided"
+ long_tail_text = ', '.join(research.keyword_analysis.get('long_tail', [])) if research and research.keyword_analysis else "None discovered"
+ semantic_text = ', '.join(research.keyword_analysis.get('semantic_keywords', [])) if research and research.keyword_analysis else "None discovered"
+ trending_text = ', '.join(research.keyword_analysis.get('trending_terms', [])) if research and research.keyword_analysis else "None discovered"
+ content_gap_text = ', '.join(research.keyword_analysis.get('content_gaps', [])) if research and research.keyword_analysis else "None identified"
+ content_angle_text = ', '.join(content_angles) if content_angles else "No explicit angles provided; infer compelling angles from research insights."
+ competitor_text = ', '.join(research.competitor_analysis.get('top_competitors', [])) if research and research.competitor_analysis else "Not available"
+ opportunity_text = ', '.join(research.competitor_analysis.get('opportunities', [])) if research and research.competitor_analysis else "Not available"
+ advantages_text = ', '.join(research.competitor_analysis.get('competitive_advantages', [])) if research and research.competitor_analysis else "Not available"
+
+ return f"""Create a comprehensive blog outline for: {primary_kw_text}
CONTEXT:
Search Intent: {search_intent}
@@ -32,19 +42,19 @@ Industry: {getattr(request.persona, 'industry', 'General') if request.persona el
Audience: {getattr(request.persona, 'target_audience', 'General') if request.persona else 'General'}
KEYWORDS:
-Primary: {', '.join(primary_keywords)}
-Secondary: {', '.join(secondary_keywords)}
-Long-tail: {', '.join(research.keyword_analysis.get('long_tail', []))}
-Semantic: {', '.join(research.keyword_analysis.get('semantic_keywords', []))}
-Trending: {', '.join(research.keyword_analysis.get('trending_terms', []))}
-Content Gaps: {', '.join(research.keyword_analysis.get('content_gaps', []))}
+Primary: {primary_kw_text}
+Secondary: {secondary_kw_text}
+Long-tail: {long_tail_text}
+Semantic: {semantic_text}
+Trending: {trending_text}
+Content Gaps: {content_gap_text}
-CONTENT ANGLES: {', '.join(content_angles)}
+CONTENT ANGLES / STORYLINES: {content_angle_text}
COMPETITIVE INTELLIGENCE:
-Top Competitors: {', '.join(research.competitor_analysis.get('top_competitors', []))}
-Market Opportunities: {', '.join(research.competitor_analysis.get('opportunities', []))}
-Competitive Advantages: {', '.join(research.competitor_analysis.get('competitive_advantages', []))}
+Top Competitors: {competitor_text}
+Market Opportunities: {opportunity_text}
+Competitive Advantages: {advantages_text}
RESEARCH SOURCES: {len(sources)} authoritative sources available
@@ -52,6 +62,7 @@ RESEARCH SOURCES: {len(sources)} authoritative sources available
STRATEGIC REQUIREMENTS:
- Create SEO-optimized headings with natural keyword integration
+- Surface the strongest research-backed angles within the outline
- Build logical narrative flow from problem to solution
- Include data-driven insights from research sources
- Address content gaps and market opportunities
@@ -59,23 +70,34 @@ STRATEGIC REQUIREMENTS:
- Ensure engaging, actionable content throughout
Return JSON format:
-{{
- "outline": [
- {{
- "heading": "Section heading with primary keyword",
- "subheadings": ["Subheading 1", "Subheading 2", "Subheading 3"],
- "key_points": ["Key point 1", "Key point 2", "Key point 3"],
+{
+ "title_options": [
+ "Title option 1",
+ "Title option 2",
+ "Title option 3"
+ ],
+ "outline": [
+ {
+ "heading": "Section heading with primary keyword",
+ "subheadings": ["Subheading 1", "Subheading 2", "Subheading 3"],
+ "key_points": ["Key point 1", "Key point 2", "Key point 3"],
"target_words": 300,
- "keywords": ["primary keyword", "secondary keyword"]
- }}
- ]
-}}"""
+ "keywords": ["primary keyword", "secondary keyword"]
+ }
+ ]
+}"""
def get_outline_schema(self) -> Dict[str, Any]:
"""Get the structured JSON schema for outline generation."""
return {
"type": "object",
"properties": {
+ "title_options": {
+ "type": "array",
+ "items": {
+ "type": "string"
+ }
+ },
"outline": {
"type": "array",
"items": {
@@ -100,6 +122,6 @@ Return JSON format:
}
}
},
- "required": ["outline"],
- "propertyOrdering": ["outline"]
+ "required": ["title_options", "outline"],
+ "propertyOrdering": ["title_options", "outline"]
}
diff --git a/backend/services/blog_writer/outline/seo_title_generator.py b/backend/services/blog_writer/outline/seo_title_generator.py
new file mode 100644
index 00000000..ef777a9c
--- /dev/null
+++ b/backend/services/blog_writer/outline/seo_title_generator.py
@@ -0,0 +1,198 @@
+"""
+SEO Title Generator - Specialized service for generating SEO-optimized blog titles.
+
+Generates 5 premium SEO-optimized titles using research data and outline context.
+"""
+
+from typing import Dict, Any, List
+from loguru import logger
+
+from models.blog_models import BlogResearchResponse, BlogOutlineSection
+
+
+class SEOTitleGenerator:
+ """Generates SEO-optimized blog titles using research and outline data."""
+
+ def __init__(self):
+ """Initialize the SEO title generator."""
+ pass
+
+ def build_title_prompt(
+ self,
+ research: BlogResearchResponse,
+ outline: List[BlogOutlineSection],
+ primary_keywords: List[str],
+ secondary_keywords: List[str],
+ content_angles: List[str],
+ search_intent: str,
+ word_count: int = 1500
+ ) -> str:
+ """Build a specialized prompt for SEO title generation."""
+
+ # Extract key research insights
+ keyword_analysis = research.keyword_analysis or {}
+ competitor_analysis = research.competitor_analysis or {}
+
+ primary_kw_text = ', '.join(primary_keywords) if primary_keywords else "the target topic"
+ secondary_kw_text = ', '.join(secondary_keywords) if secondary_keywords else "None provided"
+ long_tail_text = ', '.join(keyword_analysis.get('long_tail', [])) if keyword_analysis else "None discovered"
+ semantic_text = ', '.join(keyword_analysis.get('semantic_keywords', [])) if keyword_analysis else "None discovered"
+ trending_text = ', '.join(keyword_analysis.get('trending_terms', [])) if keyword_analysis else "None discovered"
+ content_gap_text = ', '.join(keyword_analysis.get('content_gaps', [])) if keyword_analysis else "None identified"
+ content_angle_text = ', '.join(content_angles) if content_angles else "No explicit angles provided"
+
+ # Extract outline structure summary
+ outline_summary = []
+ for i, section in enumerate(outline[:5], 1): # Limit to first 5 sections for context
+ outline_summary.append(f"{i}. {section.heading}")
+ if section.subheadings:
+ outline_summary.append(f" Subtopics: {', '.join(section.subheadings[:3])}")
+
+ outline_text = '\n'.join(outline_summary) if outline_summary else "No outline available"
+
+ return f"""Generate exactly 5 SEO-optimized blog titles for: {primary_kw_text}
+
+RESEARCH CONTEXT:
+Primary Keywords: {primary_kw_text}
+Secondary Keywords: {secondary_kw_text}
+Long-tail Keywords: {long_tail_text}
+Semantic Keywords: {semantic_text}
+Trending Terms: {trending_text}
+Content Gaps: {content_gap_text}
+Search Intent: {search_intent}
+Content Angles: {content_angle_text}
+
+OUTLINE STRUCTURE:
+{outline_text}
+
+COMPETITIVE INTELLIGENCE:
+Top Competitors: {', '.join(competitor_analysis.get('top_competitors', [])) if competitor_analysis else 'Not available'}
+Market Opportunities: {', '.join(competitor_analysis.get('opportunities', [])) if competitor_analysis else 'Not available'}
+
+SEO REQUIREMENTS:
+- Each title must be 50-65 characters (optimal for search engine display)
+- Include the primary keyword within the first 55 characters
+- Highlight a unique value proposition from the research angles
+- Use power words that drive clicks (e.g., "Ultimate", "Complete", "Essential", "Proven")
+- Avoid generic phrasing - be specific and benefit-focused
+- Target the search intent: {search_intent}
+- Ensure titles are compelling and click-worthy
+
+Return ONLY a JSON array of exactly 5 titles:
+[
+ "Title 1 (50-65 chars)",
+ "Title 2 (50-65 chars)",
+ "Title 3 (50-65 chars)",
+ "Title 4 (50-65 chars)",
+ "Title 5 (50-65 chars)"
+]"""
+
+ def get_title_schema(self) -> Dict[str, Any]:
+ """Get the JSON schema for title generation."""
+ return {
+ "type": "array",
+ "items": {
+ "type": "string",
+ "minLength": 50,
+ "maxLength": 65
+ },
+ "minItems": 5,
+ "maxItems": 5
+ }
+
+ async def generate_seo_titles(
+ self,
+ research: BlogResearchResponse,
+ outline: List[BlogOutlineSection],
+ primary_keywords: List[str],
+ secondary_keywords: List[str],
+ content_angles: List[str],
+ search_intent: str,
+ word_count: int,
+ user_id: str
+ ) -> List[str]:
+ """Generate SEO-optimized titles using research and outline data.
+
+ Args:
+ research: Research data with keywords and insights
+ outline: Blog outline sections
+ primary_keywords: Primary keywords for the blog
+ secondary_keywords: Secondary keywords
+ content_angles: Content angles from research
+ search_intent: Search intent (informational, commercial, etc.)
+ word_count: Target word count
+ user_id: User ID for API calls
+
+ Returns:
+ List of 5 SEO-optimized titles
+ """
+ from services.llm_providers.main_text_generation import llm_text_gen
+
+ if not user_id:
+ raise ValueError("user_id is required for title generation")
+
+ # Build specialized prompt
+ prompt = self.build_title_prompt(
+ research=research,
+ outline=outline,
+ primary_keywords=primary_keywords,
+ secondary_keywords=secondary_keywords,
+ content_angles=content_angles,
+ search_intent=search_intent,
+ word_count=word_count
+ )
+
+ # Get schema
+ schema = self.get_title_schema()
+
+ logger.info(f"Generating SEO-optimized titles for user {user_id}")
+
+ try:
+ # Generate titles using structured JSON response
+ result = llm_text_gen(
+ prompt=prompt,
+ json_struct=schema,
+ system_prompt="You are an expert SEO content strategist specializing in creating compelling, search-optimized blog titles.",
+ user_id=user_id
+ )
+
+ # Handle response - could be array directly or wrapped in dict
+ if isinstance(result, list):
+ titles = result
+ elif isinstance(result, dict):
+ # Try common keys
+ titles = result.get('titles', result.get('title_options', result.get('options', [])))
+ if not titles and isinstance(result.get('response'), list):
+ titles = result['response']
+ else:
+ logger.warning(f"Unexpected title generation result type: {type(result)}")
+ titles = []
+
+ # Validate and clean titles
+ cleaned_titles = []
+ for title in titles:
+ if isinstance(title, str) and len(title.strip()) >= 30: # Minimum reasonable length
+ cleaned = title.strip()
+ # Ensure it's within reasonable bounds (allow slight overflow for quality)
+ if len(cleaned) <= 70: # Allow slight overflow for quality
+ cleaned_titles.append(cleaned)
+
+ # Ensure we have exactly 5 titles
+ if len(cleaned_titles) < 5:
+ logger.warning(f"Generated only {len(cleaned_titles)} titles, expected 5")
+ # Pad with placeholder if needed (shouldn't happen with proper schema)
+ while len(cleaned_titles) < 5:
+ cleaned_titles.append(f"{primary_keywords[0] if primary_keywords else 'Blog'} - Comprehensive Guide")
+
+ # Return exactly 5 titles
+ return cleaned_titles[:5]
+
+ except Exception as e:
+ logger.error(f"Failed to generate SEO titles: {e}")
+ # Fallback: generate simple titles from keywords
+ fallback_titles = []
+ primary = primary_keywords[0] if primary_keywords else "Blog Post"
+ for i in range(5):
+ fallback_titles.append(f"{primary}: Complete Guide {i+1}")
+ return fallback_titles
+
diff --git a/backend/services/blog_writer/research/research_service.py b/backend/services/blog_writer/research/research_service.py
index 42ccd373..f8d8f505 100644
--- a/backend/services/blog_writer/research/research_service.py
+++ b/backend/services/blog_writer/research/research_service.py
@@ -74,7 +74,9 @@ class ResearchService:
if cached_result:
logger.info(f"Returning cached research result for keywords: {request.keywords}")
blog_writer_logger.log_operation_end("research", 0, success=True, cache_hit=True)
- return BlogResearchResponse(**cached_result)
+ # Normalize cached data to fix None values in confidence_scores
+ normalized_result = self._normalize_cached_research_data(cached_result)
+ return BlogResearchResponse(**normalized_result)
# User ID validation (validation logic is now in Google Grounding provider)
if not user_id:
@@ -421,7 +423,9 @@ class ResearchService:
if cached_result:
await task_manager.update_progress(task_id, "✅ Found cached research results! Returning instantly...")
logger.info(f"Returning cached research result for keywords: {request.keywords}")
- return BlogResearchResponse(**cached_result)
+ # Normalize cached data to fix None values in confidence_scores
+ normalized_result = self._normalize_cached_research_data(cached_result)
+ return BlogResearchResponse(**normalized_result)
# User ID validation
if not user_id:
@@ -759,6 +763,49 @@ class ResearchService:
return sources
+ def _normalize_cached_research_data(self, cached_data: Dict[str, Any]) -> Dict[str, Any]:
+ """
+ Normalize cached research data to fix None values in confidence_scores.
+ Ensures all GroundingSupport objects have confidence_scores as a list.
+ """
+ if not isinstance(cached_data, dict):
+ return cached_data
+
+ normalized = cached_data.copy()
+
+ # Normalize grounding_metadata if present
+ if "grounding_metadata" in normalized and normalized["grounding_metadata"]:
+ grounding_metadata = normalized["grounding_metadata"].copy() if isinstance(normalized["grounding_metadata"], dict) else {}
+
+ # Normalize grounding_supports
+ if "grounding_supports" in grounding_metadata and isinstance(grounding_metadata["grounding_supports"], list):
+ normalized_supports = []
+ for support in grounding_metadata["grounding_supports"]:
+ if isinstance(support, dict):
+ normalized_support = support.copy()
+ # Fix confidence_scores: ensure it's a list, not None
+ if normalized_support.get("confidence_scores") is None:
+ normalized_support["confidence_scores"] = []
+ elif not isinstance(normalized_support.get("confidence_scores"), list):
+ # If it's not a list, try to convert or default to empty list
+ normalized_support["confidence_scores"] = []
+ # Fix grounding_chunk_indices: ensure it's a list, not None
+ if normalized_support.get("grounding_chunk_indices") is None:
+ normalized_support["grounding_chunk_indices"] = []
+ elif not isinstance(normalized_support.get("grounding_chunk_indices"), list):
+ normalized_support["grounding_chunk_indices"] = []
+ # Ensure segment_text is a string
+ if normalized_support.get("segment_text") is None:
+ normalized_support["segment_text"] = ""
+ normalized_supports.append(normalized_support)
+ else:
+ normalized_supports.append(support)
+ grounding_metadata["grounding_supports"] = normalized_supports
+
+ normalized["grounding_metadata"] = grounding_metadata
+
+ return normalized
+
def _extract_grounding_metadata(self, gemini_result: Dict[str, Any]) -> GroundingMetadata:
"""Extract detailed grounding metadata from Gemini result."""
grounding_chunks = []
diff --git a/backend/services/integrations/wix/auth.py b/backend/services/integrations/wix/auth.py
index 17c0c2d9..6cc63fe2 100644
--- a/backend/services/integrations/wix/auth.py
+++ b/backend/services/integrations/wix/auth.py
@@ -25,7 +25,11 @@ class WixAuthService:
'client_id': self.client_id,
'redirect_uri': self.redirect_uri,
'response_type': 'code',
- 'scope': 'BLOG.CREATE-DRAFT,BLOG.PUBLISH,MEDIA.MANAGE',
+ 'scope': (
+ 'BLOG.CREATE-DRAFT,BLOG.PUBLISH-POST,BLOG.READ-CATEGORY,'
+ 'BLOG.CREATE-CATEGORY,BLOG.READ-TAG,BLOG.CREATE-TAG,'
+ 'MEDIA.SITE_MEDIA_FILES_IMPORT'
+ ),
'code_challenge': code_challenge,
'code_challenge_method': 'S256'
}
diff --git a/backend/services/integrations/wix/auth_utils.py b/backend/services/integrations/wix/auth_utils.py
new file mode 100644
index 00000000..3ed48dda
--- /dev/null
+++ b/backend/services/integrations/wix/auth_utils.py
@@ -0,0 +1,132 @@
+"""
+Authentication utilities for Wix API requests.
+
+Supports both OAuth Bearer tokens and API keys for Wix Headless apps.
+"""
+
+import os
+from typing import Dict, Optional
+from loguru import logger
+
+
+def get_wix_headers(
+ access_token: str,
+ client_id: Optional[str] = None,
+ extra: Optional[Dict[str, str]] = None
+) -> Dict[str, str]:
+ """
+ Build headers for Wix API requests with automatic token type detection.
+
+ Supports:
+ - OAuth Bearer tokens (JWT format: xxx.yyy.zzz)
+ - Wix API keys (for Headless apps)
+
+ Args:
+ access_token: OAuth token OR API key
+ client_id: Optional Wix client ID
+ extra: Additional headers to include
+
+ Returns:
+ Headers dict with proper Authorization format
+ """
+ headers: Dict[str, str] = {
+ 'Content-Type': 'application/json',
+ }
+
+ if access_token:
+ # Ensure access_token is a string (defensive check)
+ if not isinstance(access_token, str):
+ from services.integrations.wix.utils import normalize_token_string
+ normalized = normalize_token_string(access_token)
+ if normalized:
+ access_token = normalized
+ else:
+ access_token = str(access_token)
+
+ token = access_token.strip()
+ if token:
+ # Detect token type
+ # API keys are typically longer and don't have JWT structure (xxx.yyy.zzz)
+ # JWT tokens have exactly 2 dots separating 3 parts
+ # Wix OAuth tokens can have format "OauthNG.JWS.xxx.yyy.zzz"
+
+ # CRITICAL: Wix OAuth tokens can have format "OauthNG.JWS.xxx.yyy.zzz"
+ # These should use "Bearer" prefix even though they have more than 2 dots
+ if token.startswith('OauthNG.JWS.'):
+ # Wix OAuth token - use Bearer prefix
+ headers['Authorization'] = f'Bearer {token}'
+ logger.debug(f"Using Wix OAuth token with Bearer prefix (OauthNG.JWS. format detected)")
+ else:
+ # Count dots - JWT has exactly 2 dots
+ dot_count = token.count('.')
+
+ if dot_count == 2 and len(token) < 500:
+ # Likely OAuth JWT token - use Bearer prefix
+ headers['Authorization'] = f'Bearer {token}'
+ logger.debug(f"Using OAuth Bearer token (JWT format detected)")
+ else:
+ # Likely API key - use directly without Bearer prefix
+ headers['Authorization'] = token
+ logger.debug(f"Using API key for authorization (non-JWT format detected)")
+
+ if client_id:
+ headers['wix-client-id'] = client_id
+
+ if extra:
+ headers.update(extra)
+
+ return headers
+
+
+def get_wix_api_key() -> Optional[str]:
+ """
+ Get Wix API key from environment.
+
+ For Wix Headless apps, API keys provide admin-level access.
+
+ Returns:
+ API key if set, None otherwise
+ """
+ api_key = os.getenv('WIX_API_KEY')
+ if api_key:
+ logger.warning(f"✅ Wix API key found in environment ({len(api_key)} chars)")
+ else:
+ logger.warning("❌ No Wix API key in environment")
+ return api_key
+
+
+def should_use_api_key(access_token: Optional[str] = None) -> bool:
+ """
+ Determine if we should use API key instead of OAuth token.
+
+ Use API key if:
+ - No OAuth token provided
+ - OAuth token is getting 403 errors
+ - API key is available in environment
+
+ Args:
+ access_token: Optional OAuth token
+
+ Returns:
+ True if should use API key, False otherwise
+ """
+ # If no access token, check for API key
+ if not access_token or not access_token.strip():
+ return get_wix_api_key() is not None
+
+ # If access token looks like API key already, use it
+ # Ensure access_token is a string (defensive check)
+ if not isinstance(access_token, str):
+ from services.integrations.wix.utils import normalize_token_string
+ normalized = normalize_token_string(access_token)
+ if normalized:
+ access_token = normalized
+ else:
+ access_token = str(access_token)
+
+ token = access_token.strip()
+ if token.count('.') != 2 or len(token) > 500:
+ return True
+
+ return False
+
diff --git a/backend/services/integrations/wix/blog.py b/backend/services/integrations/wix/blog.py
index 6476e05a..edd41183 100644
--- a/backend/services/integrations/wix/blog.py
+++ b/backend/services/integrations/wix/blog.py
@@ -10,9 +10,39 @@ class WixBlogService:
def headers(self, access_token: str, extra: Optional[Dict[str, str]] = None) -> Dict[str, str]:
h: Dict[str, str] = {
- 'Authorization': f'Bearer {access_token}',
'Content-Type': 'application/json',
}
+
+ # Support both OAuth tokens and API keys
+ # API keys don't use 'Bearer' prefix
+ # Ensure access_token is a string (defensive check)
+ if access_token:
+ # Normalize token to string if needed
+ if not isinstance(access_token, str):
+ from .utils import normalize_token_string
+ normalized = normalize_token_string(access_token)
+ if normalized:
+ access_token = normalized
+ else:
+ access_token = str(access_token)
+
+ token = access_token.strip()
+ if token:
+ # CRITICAL: Wix OAuth tokens can have format "OauthNG.JWS.xxx.yyy.zzz"
+ # These should use "Bearer" prefix even though they have more than 2 dots
+ if token.startswith('OauthNG.JWS.'):
+ # Wix OAuth token - use Bearer prefix
+ h['Authorization'] = f'Bearer {token}'
+ logger.debug("Using Wix OAuth token with Bearer prefix (OauthNG.JWS. format detected)")
+ elif '.' not in token or len(token) > 500:
+ # Likely an API key - use directly without Bearer prefix
+ h['Authorization'] = token
+ logger.debug("Using API key for authorization")
+ else:
+ # Standard JWT OAuth token (xxx.yyy.zzz format) - use Bearer prefix
+ h['Authorization'] = f'Bearer {token}'
+ logger.debug("Using OAuth Bearer token for authorization")
+
if self.client_id:
h['wix-client-id'] = self.client_id
if extra:
@@ -20,41 +50,38 @@ class WixBlogService:
return h
def create_draft_post(self, access_token: str, payload: Dict[str, Any], extra_headers: Optional[Dict[str, str]] = None) -> Dict[str, Any]:
- # Log the exact payload being sent for debugging
+ """Create draft post with consolidated logging"""
+ from .logger import wix_logger
import json
- logger.warning(f"📤 Sending to Wix Blog API:")
- logger.warning(f" Endpoint: {self.base_url}/blog/v3/draft-posts")
- logger.warning(f" Payload top-level keys: {list(payload.keys())}")
+
+ # Build payload summary for logging
+ payload_summary = {}
if 'draftPost' in payload:
dp = payload['draftPost']
- logger.warning(f" draftPost keys: {list(dp.keys())}")
- if 'richContent' in dp:
- rc = dp['richContent']
- logger.warning(f" richContent keys: {list(rc.keys()) if isinstance(rc, dict) else 'N/A'}")
- if isinstance(rc, dict) and 'nodes' in rc:
- nodes = rc['nodes']
- logger.warning(f" richContent.nodes count: {len(nodes) if isinstance(nodes, list) else 'N/A'}")
- # Inspect first LIST_ITEM node if any
- for i, node in enumerate(nodes[:10]):
- if isinstance(node, dict) and node.get('type') == 'LIST_ITEM':
- logger.warning(f" Found LIST_ITEM at index {i}:")
- logger.warning(f" Keys: {list(node.keys())}")
- logger.warning(f" Has listItemData: {'listItemData' in node}")
- if 'listItemData' in node:
- logger.warning(f" listItemData type: {type(node['listItemData'])}, value: {node['listItemData']}")
- if 'nodes' in node:
- nested = node['nodes']
- logger.warning(f" Nested nodes count: {len(nested) if isinstance(nested, list) else 'N/A'}")
- for j, n_node in enumerate(nested[:3]):
- if isinstance(n_node, dict):
- logger.warning(f" Nested node {j}: type={n_node.get('type')}, keys={list(n_node.keys())}")
- if n_node.get('type') == 'PARAGRAPH' and 'paragraphData' in n_node:
- logger.warning(f" paragraphData type: {type(n_node['paragraphData'])}, value: {n_node['paragraphData']}")
- break # Only inspect first LIST_ITEM
+ payload_summary['draftPost'] = {
+ 'title': dp.get('title'),
+ 'richContent': {'nodes': len(dp.get('richContent', {}).get('nodes', []))} if 'richContent' in dp else None,
+ 'seoData': 'seoData' in dp
+ }
- logger.warning(f" Full Payload JSON (first 8000 chars):\n{json.dumps(payload, indent=2, ensure_ascii=False)[:8000]}...")
+ request_headers = self.headers(access_token, extra_headers)
+ response = requests.post(f"{self.base_url}/blog/v3/draft-posts", headers=request_headers, json=payload)
+
+ # Consolidated error logging
+ error_body = None
+ if response.status_code >= 400:
+ try:
+ error_body = response.json()
+ except:
+ error_body = {'message': response.text[:200]}
+
+ wix_logger.log_api_call("POST", "/blog/v3/draft-posts", response.status_code, payload_summary, error_body)
+
+ if response.status_code >= 400:
+ # Only show detailed error info for debugging
+ if response.status_code == 500:
+ logger.debug(f" Full error: {json.dumps(error_body, indent=2) if isinstance(error_body, dict) else error_body}")
- response = requests.post(f"{self.base_url}/blog/v3/draft-posts", headers=self.headers(access_token, extra_headers), json=payload)
response.raise_for_status()
return response.json()
diff --git a/backend/services/integrations/wix/blog_publisher.py b/backend/services/integrations/wix/blog_publisher.py
index 7da9f7e8..6eaecb59 100644
--- a/backend/services/integrations/wix/blog_publisher.py
+++ b/backend/services/integrations/wix/blog_publisher.py
@@ -14,6 +14,8 @@ from services.integrations.wix.blog import WixBlogService
from services.integrations.wix.content import convert_content_to_ricos
from services.integrations.wix.ricos_converter import convert_via_wix_api
from services.integrations.wix.seo import build_seo_data
+from services.integrations.wix.logger import wix_logger
+from services.integrations.wix.utils import normalize_token_string
def validate_ricos_content(ricos_content: Dict[str, Any]) -> Dict[str, Any]:
@@ -220,10 +222,96 @@ def create_blog_post(
if not member_id:
raise ValueError("memberId is required for third-party apps creating blog posts")
- headers = {
- 'Authorization': f'Bearer {access_token}',
- 'Content-Type': 'application/json'
- }
+ # Ensure access_token is a string (handle cases where it might be int, dict, or other type)
+ # Use normalize_token_string to handle various token formats (dict with accessToken.value, etc.)
+ normalized_token = normalize_token_string(access_token)
+ if not normalized_token:
+ raise ValueError("access_token is required and must be a valid string or token object")
+ access_token = normalized_token.strip()
+ if not access_token:
+ raise ValueError("access_token cannot be empty")
+
+ # BACK TO BASICS MODE: Try simplest possible structure FIRST
+ # Since posting worked before Ricos/SEO, let's test with absolute minimum
+ BACK_TO_BASICS_MODE = True # Set to True to test with simplest structure
+
+ wix_logger.reset()
+ wix_logger.log_operation_start("Blog Post Creation", title=title[:50] if title else None, member_id=member_id[:20] if member_id else None)
+
+ if BACK_TO_BASICS_MODE:
+ logger.info("🔧 Wix: BACK TO BASICS MODE - Testing minimal structure")
+
+ # Import auth utilities for proper token handling
+ from .auth_utils import get_wix_headers
+
+ # Create absolute minimal Ricos structure
+ minimal_ricos = {
+ 'nodes': [{
+ 'id': str(uuid.uuid4()),
+ 'type': 'PARAGRAPH',
+ 'nodes': [{
+ 'id': str(uuid.uuid4()),
+ 'type': 'TEXT',
+ 'nodes': [],
+ 'textData': {
+ 'text': (content[:500] if content else "This is a post from ALwrity.").strip(),
+ 'decorations': []
+ }
+ }],
+ 'paragraphData': {}
+ }]
+ }
+
+ # Extract wix-site-id from token if possible
+ extra_headers = {}
+ try:
+ token_str = str(access_token)
+ if token_str and token_str.startswith('OauthNG.JWS.'):
+ import jwt
+ import json
+ jwt_part = token_str[12:]
+ payload = jwt.decode(jwt_part, options={"verify_signature": False, "verify_aud": False})
+ data_payload = payload.get('data', {})
+ if isinstance(data_payload, str):
+ try:
+ data_payload = json.loads(data_payload)
+ except:
+ pass
+ instance_data = data_payload.get('instance', {})
+ meta_site_id = instance_data.get('metaSiteId')
+ if isinstance(meta_site_id, str) and meta_site_id:
+ extra_headers['wix-site-id'] = meta_site_id
+ except Exception:
+ pass
+
+ # Build minimal payload
+ minimal_blog_data = {
+ 'draftPost': {
+ 'title': str(title).strip() if title else "Untitled",
+ 'memberId': str(member_id).strip(),
+ 'richContent': minimal_ricos
+ },
+ 'publish': False,
+ 'fieldsets': ['URL']
+ }
+
+ try:
+ from .blog import WixBlogService
+ blog_service_test = WixBlogService('https://www.wixapis.com', None)
+ result = blog_service_test.create_draft_post(access_token, minimal_blog_data, extra_headers if extra_headers else None)
+ logger.success("✅✅✅ Wix: BACK TO BASICS SUCCEEDED! Issue is with Ricos/SEO structure")
+ wix_logger.log_operation_result("Back to Basics Test", True, result)
+ return result
+ except Exception as e:
+ logger.error(f"❌ Wix: BACK TO BASICS FAILED - {str(e)[:100]}")
+ logger.error(" ⚠️ Issue is NOT with Ricos/SEO - likely permissions/token")
+ wix_logger.add_error(f"Back to Basics: {str(e)[:100]}")
+
+ # Import auth utilities for proper token handling
+ from .auth_utils import get_wix_headers
+
+ # Headers for blog post creation (use user's OAuth token)
+ headers = get_wix_headers(access_token)
# Build valid Ricos rich content
# Ensure content is not empty
@@ -231,20 +319,87 @@ def create_blog_post(
content = "This is a post from ALwrity."
logger.warning("⚠️ Content was empty, using default text")
- # Try Wix API first (more reliable), fall back to custom parser
- ricos_content = None
+ # Quick token/permission check (only log if issues found)
+ has_blog_scope = None
+ meta_site_id = None
try:
- logger.warning("🔄 Attempting to convert markdown to Ricos via Wix API...")
- ricos_content = convert_via_wix_api(content, access_token, base_url)
- logger.warning(f"✅ Wix API conversion successful. Ricos document has {len(ricos_content.get('nodes', []))} nodes")
- except Exception as e:
- logger.warning(f"⚠️ Wix Ricos API conversion failed: {e}. Falling back to custom parser...")
- # Fall back to custom parser
- ricos_content = convert_content_to_ricos(content, None)
- logger.warning(f"✅ Custom parser conversion complete. Ricos document has {len(ricos_content.get('nodes', []))} nodes")
+ from .utils import decode_wix_token
+ import json
+ token_data = decode_wix_token(access_token)
+ if 'scope' in token_data:
+ scopes = token_data.get('scope')
+ if isinstance(scopes, str):
+ scope_list = scopes.split(',') if ',' in scopes else [scopes]
+ has_blog_scope = any('BLOG' in s.upper() for s in scope_list)
+ if not has_blog_scope:
+ logger.error("❌ Wix: Token missing BLOG scopes - verify OAuth app permissions")
+ if 'data' in token_data:
+ data = token_data.get('data')
+ if isinstance(data, str):
+ try:
+ data = json.loads(data)
+ except:
+ pass
+ if isinstance(data, dict) and 'instance' in data:
+ instance = data.get('instance', {})
+ meta_site_id = instance.get('metaSiteId')
+ except Exception:
+ pass
- # Validate Ricos content
- ricos_content = validate_ricos_content(ricos_content)
+ # Quick permission test (only log failures)
+ try:
+ test_headers = get_wix_headers(access_token)
+ import requests
+ test_response = requests.get(f"{base_url}/blog/v3/categories", headers=test_headers, timeout=5)
+ if test_response.status_code == 403:
+ logger.error("❌ Wix: Permission denied - OAuth app missing BLOG.CREATE-DRAFT")
+ elif test_response.status_code == 401:
+ logger.error("❌ Wix: Unauthorized - token may be expired")
+ except Exception:
+ pass
+
+ # Safely get token length (access_token is already validated as string above)
+ token_length = len(access_token) if access_token else 0
+ wix_logger.log_token_info(token_length, has_blog_scope, meta_site_id)
+
+ # Convert markdown to Ricos
+ ricos_content = convert_content_to_ricos(content, None)
+ nodes_count = len(ricos_content.get('nodes', []))
+ wix_logger.log_ricos_conversion(nodes_count)
+
+ # Validate Ricos content structure
+ # Per Wix Blog API documentation: richContent should ONLY contain 'nodes'
+ # The example in docs shows: { nodes: [...] } - no type, id, metadata, or documentStyle
+ if not isinstance(ricos_content, dict):
+ logger.error(f"❌ richContent is not a dict: {type(ricos_content)}")
+ raise ValueError("richContent must be a dictionary object")
+
+ if 'nodes' not in ricos_content or not isinstance(ricos_content['nodes'], list):
+ logger.error(f"❌ richContent.nodes is missing or not a list: {ricos_content.get('nodes', 'MISSING')}")
+ raise ValueError("richContent must contain a 'nodes' array")
+
+ # Remove type and id fields (not expected by Blog API)
+ # NOTE: metadata is optional - Wix UPDATE endpoint example shows it, but CREATE example doesn't
+ # We'll keep it minimal (nodes only) for CREATE to match the recipe example
+ fields_to_remove = ['type', 'id']
+ for field in fields_to_remove:
+ if field in ricos_content:
+ logger.debug(f"Removing '{field}' field from richContent (Blog API doesn't expect this)")
+ del ricos_content[field]
+
+ # Remove metadata and documentStyle - Blog API CREATE endpoint example shows only 'nodes'
+ # (UPDATE endpoint shows metadata, but we're using CREATE)
+ if 'metadata' in ricos_content:
+ logger.debug("Removing 'metadata' from richContent (CREATE endpoint expects only 'nodes')")
+ del ricos_content['metadata']
+ if 'documentStyle' in ricos_content:
+ logger.debug("Removing 'documentStyle' from richContent (CREATE endpoint expects only 'nodes')")
+ del ricos_content['documentStyle']
+
+ # Ensure we only have 'nodes' in richContent for CREATE endpoint
+ ricos_content = {'nodes': ricos_content['nodes']}
+
+ logger.debug(f"✅ richContent structure validated: {len(ricos_content['nodes'])} nodes, keys: {list(ricos_content.keys())}")
# Minimal payload per Wix docs: title, memberId, and richContent
# CRITICAL: Only include fields that have valid values (no None, no empty strings for required fields)
@@ -252,7 +407,7 @@ def create_blog_post(
'draftPost': {
'title': str(title).strip() if title else "Untitled",
'memberId': str(member_id).strip(), # Required for third-party apps (validated above)
- 'richContent': ricos_content, # Must be a valid Ricos document object
+ 'richContent': ricos_content, # Must be a valid Ricos object with ONLY 'nodes'
},
'publish': bool(publish),
'fieldsets': ['URL'] # Simplified fieldsets
@@ -340,76 +495,34 @@ def create_blog_post(
logger.warning("All tag IDs were invalid, not including tagIds in payload")
# Build SEO data from metadata if provided
+ # NOTE: seoData is optional - if it causes issues, we can create post without it
seo_data = None
if seo_metadata:
- logger.warning(f"📊 Building SEO data from metadata. Keys: {list(seo_metadata.keys())}")
- seo_data = build_seo_data(seo_metadata, title)
- if seo_data:
- # Log detailed SEO structure
- logger.warning(f"📋 SEO data built: {len(seo_data.get('tags', []))} tags, {len(seo_data.get('settings', {}).get('keywords', []))} keywords")
-
- # Log each SEO tag for debugging (key ones only to avoid too much output)
- if seo_data.get('tags'):
- for idx, tag in enumerate(seo_data['tags'][:3]): # First 3 tags only
- tag_type = tag.get('type')
- if tag_type == 'title':
- logger.warning(f" SEO tag {idx+1}: type={tag_type}, children={str(tag.get('children', ''))[:50]}...")
- else:
- props = tag.get('props', {})
- content_preview = str(props.get('content', props.get('href', props.get('name', ''))))[:50]
- logger.warning(f" SEO tag {idx+1}: type={tag_type}, props={list(props.keys())}, content={content_preview}...")
- if len(seo_data['tags']) > 3:
- logger.warning(f" ... and {len(seo_data['tags']) - 3} more SEO tags")
-
- blog_data['draftPost']['seoData'] = seo_data
- logger.warning(f"✅ Added seoData to blog post with {len(seo_data.get('tags', []))} tags")
- else:
- logger.warning("⚠️ SEO data was empty after building - check build_seo_data function")
+ try:
+ seo_data = build_seo_data(seo_metadata, title)
+ if seo_data:
+ tags_count = len(seo_data.get('tags', []))
+ keywords_count = len(seo_data.get('settings', {}).get('keywords', []))
+ wix_logger.log_seo_data(tags_count, keywords_count)
+ blog_data['draftPost']['seoData'] = seo_data
+ except Exception as e:
+ logger.warning(f"⚠️ Wix: SEO data build failed - {str(e)[:50]}")
+ wix_logger.add_warning(f"SEO build: {str(e)[:50]}")
- # Add SEO slug if provided (separate field from seoData)
+ # Add SEO slug if provided
if seo_metadata.get('url_slug'):
blog_data['draftPost']['seoSlug'] = str(seo_metadata.get('url_slug')).strip()
- logger.warning(f"✅ Added SEO slug: {blog_data['draftPost']['seoSlug']}")
else:
logger.warning("⚠️ No SEO metadata provided to create_blog_post")
- # Log the payload structure for debugging (without sensitive data)
- logger.warning(f"📝 Creating blog post with title: '{title}'")
- logger.warning(f"📋 Draft post fields: {list(blog_data['draftPost'].keys())}")
-
- # Detailed SEO logging
- if 'seoData' in blog_data['draftPost']:
- seo_data_debug = blog_data['draftPost']['seoData']
- logger.warning(f"📊 SEO data in payload: {len(seo_data_debug.get('tags', []))} tags, {len(seo_data_debug.get('settings', {}).get('keywords', []))} keywords")
-
- # Log sample SEO tags (first 2 only to avoid too much output)
- if seo_data_debug.get('tags'):
- logger.warning("📋 SEO Tags sample:")
- for i, tag in enumerate(seo_data_debug['tags'][:2]): # First 2 tags
- logger.warning(f" Tag {i+1}: type={tag.get('type')}, custom={tag.get('custom')}, disabled={tag.get('disabled')}")
- if len(seo_data_debug['tags']) > 2:
- logger.warning(f" ... and {len(seo_data_debug['tags']) - 2} more tags")
-
- if seo_data_debug.get('settings', {}).get('keywords'):
- keywords_list = [k.get('term') for k in seo_data_debug['settings']['keywords'][:3]]
- logger.warning(f"🔑 Keywords: {keywords_list}")
-
- # Log FULL seoData structure for debugging
- import json
- try:
- seo_json = json.dumps(seo_data_debug, indent=2, ensure_ascii=False)
- logger.warning(f"📄 FULL seoData JSON:\n{seo_json[:2000]}...") # First 2000 chars
- except Exception as e:
- logger.error(f"Failed to serialize seoData: {e}")
- else:
- logger.warning("⚠️ No seoData in draft post payload!")
-
try:
- # Add wix-site-id header if we can extract it from token
+ # Extract wix-site-id from token if possible
extra_headers = {}
try:
token_str = str(access_token)
if token_str and token_str.startswith('OauthNG.JWS.'):
+ import jwt
+ import json
jwt_part = token_str[12:]
payload = jwt.decode(jwt_part, options={"verify_signature": False, "verify_aud": False})
data_payload = payload.get('data', {})
@@ -423,12 +536,8 @@ def create_blog_post(
if isinstance(meta_site_id, str) and meta_site_id:
extra_headers['wix-site-id'] = meta_site_id
headers['wix-site-id'] = meta_site_id
- except Exception as e:
- logger.debug(f"Could not extract site ID from token: {e}")
-
- # Make the API call
- logger.warning(f"🚀 Calling Wix API: POST /blog/v3/draft-posts")
- logger.warning(f"📦 Payload: title='{blog_data['draftPost'].get('title')}', has_seoData={'seoData' in blog_data['draftPost']}, has_richContent={'richContent' in blog_data['draftPost']}")
+ except Exception:
+ pass
# Validate payload structure before sending
draft_post = blog_data.get('draftPost', {})
@@ -617,88 +726,13 @@ def create_blog_post(
logger.warning(f"📤 RichContent has metadata: {bool(blog_data['draftPost']['richContent'].get('metadata'))}")
logger.warning(f"📤 RichContent has documentStyle: {bool(blog_data['draftPost']['richContent'].get('documentStyle'))}")
- # Try sending WITHOUT SEO data first to isolate the issue
- test_without_seo = False # Disabled - listItemData issue fixed
- if test_without_seo and 'seoData' in blog_data['draftPost']:
- logger.warning("🧪 TESTING WITHOUT SEO DATA to isolate issue...")
- # Clone the payload without SEO data
- test_payload_no_seo = {
- 'draftPost': {
- 'title': blog_data['draftPost']['title'],
- 'memberId': blog_data['draftPost']['memberId'],
- 'richContent': blog_data['draftPost']['richContent'],
- 'excerpt': blog_data['draftPost'].get('excerpt', '')
- },
- 'publish': False,
- 'fieldsets': ['URL']
- }
- try:
- logger.warning("🧪 Attempting without SEO data...")
- test_result = blog_service.create_draft_post(access_token, test_payload_no_seo, extra_headers or None)
- logger.warning(f"✅ WITHOUT SEO DATA SUCCEEDED! Post ID: {test_result.get('draftPost', {}).get('id')}")
- logger.error("⚠️⚠️⚠️ ISSUE IS WITH SEO DATA STRUCTURE!")
- # If this succeeds, don't send the full payload, just return this result
- return test_result
- except Exception as e:
- logger.warning(f"❌ WITHOUT SEO DATA ALSO FAILED: {e}")
- logger.warning("⚠️ Issue is NOT with SEO data, continuing with full payload...")
-
- # Try sending with minimal structure first to isolate the issue
- # Create a test payload with just required fields
- minimal_test = False # Set to True to test with minimal payload
- if minimal_test:
- logger.warning("🧪 TESTING WITH MINIMAL PAYLOAD (title + memberId + simple richContent)")
- test_payload = {
- 'draftPost': {
- 'title': blog_data['draftPost']['title'],
- 'memberId': blog_data['draftPost']['memberId'],
- 'richContent': {
- 'nodes': [
- {
- 'id': str(uuid.uuid4()),
- 'type': 'PARAGRAPH',
- 'nodes': [
- {
- 'id': str(uuid.uuid4()),
- 'type': 'TEXT',
- 'textData': {
- 'text': 'Test paragraph',
- 'decorations': []
- }
- }
- ],
- 'paragraphData': {}
- }
- ],
- 'metadata': {'version': 1, 'id': str(uuid.uuid4())},
- 'documentStyle': {}
- }
- },
- 'publish': False,
- 'fieldsets': ['URL']
- }
- logger.warning("🧪 Attempting minimal payload first...")
- try:
- test_result = blog_service.create_draft_post(access_token, test_payload, extra_headers or None)
- logger.warning(f"✅ MINIMAL PAYLOAD SUCCEEDED! Post ID: {test_result.get('draftPost', {}).get('id')}")
- logger.warning("⚠️ Issue is with complex content, not basic structure")
- except Exception as e:
- logger.error(f"❌ MINIMAL PAYLOAD ALSO FAILED: {e}")
- logger.error("⚠️ Issue is with basic structure or permissions")
-
result = blog_service.create_draft_post(access_token, blog_data, extra_headers or None)
- # Log response
+ # Log success
draft_post = result.get('draftPost', {})
- logger.warning(f"✅ Blog post created successfully! Post ID: {draft_post.get('id', 'N/A')}")
-
- # Check if SEO data was preserved in response
- if 'seoData' in draft_post:
- seo_response = draft_post['seoData']
- logger.warning(f"✅ SEO data confirmed in response: {len(seo_response.get('tags', []))} tags, {len(seo_response.get('settings', {}).get('keywords', []))} keywords")
- else:
- logger.warning("⚠️ No seoData in response - it may have been filtered out by Wix API")
- logger.warning(f"📋 Response fields: {list(draft_post.keys())}")
+ post_id = draft_post.get('id', 'N/A')
+ wix_logger.log_operation_result("Create Draft Post", True, result)
+ logger.success(f"✅ Wix: Blog post created - ID: {post_id}")
return result
except requests.RequestException as e:
diff --git a/backend/services/integrations/wix/content.py b/backend/services/integrations/wix/content.py
index 0a31aec4..df3a5be2 100644
--- a/backend/services/integrations/wix/content.py
+++ b/backend/services/integrations/wix/content.py
@@ -13,6 +13,7 @@ def parse_markdown_inline(text: str) -> List[Dict[str, Any]]:
return [{
'id': str(uuid.uuid4()),
'type': 'TEXT',
+ 'nodes': [], # TEXT nodes must have empty nodes array per Wix API
'textData': {'text': '', 'decorations': []}
}]
@@ -32,6 +33,7 @@ def parse_markdown_inline(text: str) -> List[Dict[str, Any]]:
nodes.append({
'id': str(uuid.uuid4()),
'type': 'TEXT',
+ 'nodes': [], # TEXT nodes must have empty nodes array per Wix API
'textData': {
'text': current_text,
'decorations': current_decorations.copy()
@@ -46,11 +48,14 @@ def parse_markdown_inline(text: str) -> List[Dict[str, Any]]:
# Recursively parse the bold text for nested formatting
bold_nodes = parse_markdown_inline(bold_text)
# Add BOLD decoration to all text nodes within
+ # Per Wix API: decorations are objects with 'type' field, not strings
for node in bold_nodes:
if node['type'] == 'TEXT':
node_decorations = node['textData'].get('decorations', []).copy()
- if 'BOLD' not in node_decorations:
- node_decorations.append('BOLD')
+ # Check if BOLD decoration already exists
+ has_bold = any(d.get('type') == 'BOLD' for d in node_decorations if isinstance(d, dict))
+ if not has_bold:
+ node_decorations.append({'type': 'BOLD'})
node['textData']['decorations'] = node_decorations
nodes.append(node)
i = end_bold + 2
@@ -63,6 +68,7 @@ def parse_markdown_inline(text: str) -> List[Dict[str, Any]]:
nodes.append({
'id': str(uuid.uuid4()),
'type': 'TEXT',
+ 'nodes': [], # TEXT nodes must have empty nodes array per Wix API
'textData': {
'text': current_text,
'decorations': current_decorations.copy()
@@ -79,24 +85,23 @@ def parse_markdown_inline(text: str) -> List[Dict[str, Any]]:
url_end = text.find(')', url_start)
if url_end != -1:
url = text[url_start:url_end]
- # Create link node
- link_node_id = str(uuid.uuid4())
- text_node_id = str(uuid.uuid4())
- link_text_nodes = parse_markdown_inline(link_text)
- # Wrap link text in LINK node
+ # Per Wix API: Links are decorations on TEXT nodes, not separate node types
+ # Create TEXT node with LINK decoration
nodes.append({
- 'id': link_node_id,
- 'type': 'LINK',
- 'nodes': link_text_nodes if link_text_nodes else [{
- 'id': text_node_id,
- 'type': 'TEXT',
- 'textData': {'text': link_text, 'decorations': []}
- }],
- 'linkData': {
- 'link': {
- 'url': url,
- 'target': '_blank'
- }
+ 'id': str(uuid.uuid4()),
+ 'type': 'TEXT',
+ 'nodes': [], # TEXT nodes must have empty nodes array per Wix API
+ 'textData': {
+ 'text': link_text,
+ 'decorations': [{
+ 'type': 'LINK',
+ 'linkData': {
+ 'link': {
+ 'url': url,
+ 'target': 'BLANK' # Wix API uses 'BLANK', not '_blank'
+ }
+ }
+ }]
}
})
i = url_end + 1
@@ -109,6 +114,7 @@ def parse_markdown_inline(text: str) -> List[Dict[str, Any]]:
nodes.append({
'id': str(uuid.uuid4()),
'type': 'TEXT',
+ 'nodes': [], # TEXT nodes must have empty nodes array per Wix API
'textData': {
'text': current_text,
'decorations': current_decorations.copy()
@@ -121,12 +127,16 @@ def parse_markdown_inline(text: str) -> List[Dict[str, Any]]:
code_end = text.find('`', i + 1)
if code_end != -1:
code_text = text[i + 1:code_end]
+ # Per Wix API: CODE is not a valid decoration type, but we'll keep the structure
+ # Note: Wix uses CODE_BLOCK nodes for code, not CODE decorations
+ # For inline code, we'll just use plain text for now
nodes.append({
'id': str(uuid.uuid4()),
'type': 'TEXT',
+ 'nodes': [], # TEXT nodes must have empty nodes array per Wix API
'textData': {
'text': code_text,
- 'decorations': ['CODE']
+ 'decorations': [] # CODE is not a valid decoration in Wix API
}
})
i = code_end + 1
@@ -139,6 +149,7 @@ def parse_markdown_inline(text: str) -> List[Dict[str, Any]]:
nodes.append({
'id': str(uuid.uuid4()),
'type': 'TEXT',
+ 'nodes': [], # TEXT nodes must have empty nodes array per Wix API
'textData': {
'text': current_text,
'decorations': current_decorations.copy()
@@ -155,11 +166,14 @@ def parse_markdown_inline(text: str) -> List[Dict[str, Any]]:
italic_text = text[i + 1:italic_end]
italic_nodes = parse_markdown_inline(italic_text)
# Add ITALIC decoration
+ # Per Wix API: decorations are objects with 'type' field
for node in italic_nodes:
if node['type'] == 'TEXT':
node_decorations = node['textData'].get('decorations', []).copy()
- if 'ITALIC' not in node_decorations:
- node_decorations.append('ITALIC')
+ # Check if ITALIC decoration already exists
+ has_italic = any(d.get('type') == 'ITALIC' for d in node_decorations if isinstance(d, dict))
+ if not has_italic:
+ node_decorations.append({'type': 'ITALIC'})
node['textData']['decorations'] = node_decorations
nodes.append(node)
i = italic_end + 1
@@ -174,6 +188,7 @@ def parse_markdown_inline(text: str) -> List[Dict[str, Any]]:
nodes.append({
'id': str(uuid.uuid4()),
'type': 'TEXT',
+ 'nodes': [], # TEXT nodes must have empty nodes array per Wix API
'textData': {
'text': current_text,
'decorations': current_decorations.copy()
@@ -185,6 +200,7 @@ def parse_markdown_inline(text: str) -> List[Dict[str, Any]]:
nodes.append({
'id': str(uuid.uuid4()),
'type': 'TEXT',
+ 'nodes': [], # TEXT nodes must have empty nodes array per Wix API
'textData': {
'text': text,
'decorations': []
@@ -439,6 +455,7 @@ def convert_content_to_ricos(content: str, images: List[str] = None) -> Dict[str
'nodes': [{
'id': str(uuid.uuid4()),
'type': 'TEXT',
+ 'nodes': [], # TEXT nodes must have empty nodes array per Wix API
'textData': {
'text': content[:500] if content else "This is a post from ALwrity.",
'decorations': []
@@ -448,14 +465,11 @@ def convert_content_to_ricos(content: str, images: List[str] = None) -> Dict[str
}
nodes.append(fallback_paragraph)
+ # Per Wix Blog API documentation: richContent should ONLY contain 'nodes'
+ # Do NOT include 'type', 'id', 'metadata', or 'documentStyle' at root level
+ # These fields are for Ricos Document format, but Blog API expects just the nodes structure
return {
- 'type': 'DOCUMENT',
- 'id': str(uuid.uuid4()),
- 'nodes': nodes,
- 'metadata': {'version': 1, 'id': str(uuid.uuid4())},
- 'documentStyle': {
- 'paragraph': {'decorations': [], 'nodeStyle': {}, 'lineHeight': '1.5'}
- }
+ 'nodes': nodes
}
diff --git a/backend/services/integrations/wix/logger.py b/backend/services/integrations/wix/logger.py
new file mode 100644
index 00000000..bd892080
--- /dev/null
+++ b/backend/services/integrations/wix/logger.py
@@ -0,0 +1,118 @@
+"""
+Intelligent logging utility for Wix operations.
+Aggregates and consolidates logs to reduce console noise.
+"""
+from typing import Dict, Any, Optional, List
+from loguru import logger
+import json
+
+
+class WixLogger:
+ """Consolidated logger for Wix operations"""
+
+ def __init__(self):
+ self.context: Dict[str, Any] = {}
+ self.errors: List[str] = []
+ self.warnings: List[str] = []
+
+ def reset(self):
+ """Reset context for new operation"""
+ self.context = {}
+ self.errors = []
+ self.warnings = []
+
+ def set_context(self, key: str, value: Any):
+ """Store context information"""
+ self.context[key] = value
+
+ def add_error(self, message: str):
+ """Add error message"""
+ self.errors.append(message)
+
+ def add_warning(self, message: str):
+ """Add warning message"""
+ self.warnings.append(message)
+
+ def log_operation_start(self, operation: str, **kwargs):
+ """Log start of operation with aggregated context"""
+ logger.info(f"🚀 Wix: {operation}")
+ if kwargs:
+ summary = ", ".join([f"{k}={v}" for k, v in kwargs.items() if v])
+ if summary:
+ logger.info(f" {summary}")
+
+ def log_operation_result(self, operation: str, success: bool, result: Optional[Dict] = None, error: Optional[str] = None):
+ """Log operation result"""
+ if success:
+ post_id = result.get('draftPost', {}).get('id') if result else None
+ if post_id:
+ logger.success(f"✅ Wix: {operation} - Post ID: {post_id}")
+ else:
+ logger.success(f"✅ Wix: {operation} - Success")
+ else:
+ logger.error(f"❌ Wix: {operation} - {error or 'Failed'}")
+
+ def log_api_call(self, method: str, endpoint: str, status_code: int,
+ payload_summary: Optional[Dict] = None, error_body: Optional[Dict] = None):
+ """Log API call with aggregated information"""
+ status_emoji = "✅" if status_code < 400 else "❌"
+ logger.info(f"{status_emoji} Wix API: {method} {endpoint} → {status_code}")
+
+ if payload_summary:
+ # Show only key information
+ if 'draftPost' in payload_summary:
+ dp = payload_summary['draftPost']
+ parts = []
+ if 'title' in dp:
+ parts.append(f"title='{str(dp['title'])[:50]}...'")
+ if 'richContent' in dp:
+ nodes_count = len(dp['richContent'].get('nodes', []))
+ parts.append(f"nodes={nodes_count}")
+ if 'seoData' in dp:
+ parts.append("has_seoData")
+ if parts:
+ logger.debug(f" Payload: {', '.join(parts)}")
+
+ if error_body and status_code >= 400:
+ error_msg = error_body.get('message', 'Unknown error')
+ logger.error(f" Error: {error_msg}")
+ if status_code == 500:
+ logger.error(" ⚠️ Internal server error - check Wix API status")
+ elif status_code == 403:
+ logger.error(" ⚠️ Permission denied - verify OAuth app has BLOG.CREATE-DRAFT")
+ elif status_code == 401:
+ logger.error(" ⚠️ Unauthorized - token may be expired")
+
+ def log_token_info(self, token_length: int, has_blog_scope: Optional[bool] = None,
+ meta_site_id: Optional[str] = None):
+ """Log token information (aggregated)"""
+ info_parts = [f"Token: {token_length} chars"]
+ if has_blog_scope is not None:
+ info_parts.append(f"Blog scope: {'✅' if has_blog_scope else '❌'}")
+ if meta_site_id:
+ info_parts.append(f"Site ID: {meta_site_id[:20]}...")
+ logger.debug(f"🔐 Wix Auth: {', '.join(info_parts)}")
+
+ def log_ricos_conversion(self, nodes_count: int, method: str = "custom parser"):
+ """Log Ricos conversion result"""
+ logger.info(f"📝 Wix Ricos: Converted to {nodes_count} nodes ({method})")
+
+ def log_seo_data(self, tags_count: int, keywords_count: int):
+ """Log SEO data summary"""
+ logger.info(f"🔍 Wix SEO: {tags_count} tags, {keywords_count} keywords")
+
+ def log_final_summary(self):
+ """Log final aggregated summary"""
+ if self.errors:
+ logger.error(f"⚠️ Wix Operation: {len(self.errors)} error(s)")
+ for err in self.errors[-3:]: # Show last 3 errors
+ logger.error(f" {err}")
+ elif self.warnings:
+ logger.warning(f"⚠️ Wix Operation: {len(self.warnings)} warning(s)")
+ else:
+ logger.success("✅ Wix Operation: No issues detected")
+
+
+# Global instance
+wix_logger = WixLogger()
+
diff --git a/backend/services/integrations/wix/ricos_converter.py b/backend/services/integrations/wix/ricos_converter.py
index faba70c7..9cc93ce7 100644
--- a/backend/services/integrations/wix/ricos_converter.py
+++ b/backend/services/integrations/wix/ricos_converter.py
@@ -148,6 +148,9 @@ def convert_via_wix_api(markdown_content: str, access_token: str, base_url: str
Convert markdown to Ricos using Wix's official Ricos Documents API.
Uses HTML format for better reliability (per Wix documentation, HTML is fully supported).
+ Wix API Limitation: HTML content must be 10,000 characters or less.
+ If content exceeds this limit, it will be truncated with an ellipsis.
+
Reference: https://dev.wix.com/docs/api-reference/assets/rich-content/ricos-documents/convert-to-ricos-document
Args:
@@ -182,6 +185,28 @@ def convert_via_wix_api(markdown_content: str, access_token: str, base_url: str
else:
html_content = html_stripped
+ # CRITICAL: Wix API has a 10,000 character limit for HTML content
+ # If content exceeds this limit, truncate intelligently at paragraph boundaries
+ MAX_HTML_LENGTH = 10000
+ if len(html_content) > MAX_HTML_LENGTH:
+ logger.warning(f"⚠️ HTML content ({len(html_content)} chars) exceeds Wix API limit of {MAX_HTML_LENGTH} chars")
+
+ # Try to truncate at a paragraph boundary to avoid breaking HTML tags
+ truncate_at = MAX_HTML_LENGTH - 100 # Leave room for closing tags and ellipsis
+
+ # Look for the last
tag before the truncation point
+ last_p_close = html_content.rfind('', 0, truncate_at)
+ if last_p_close > 0:
+ html_content = html_content[:last_p_close + 4] # Include the tag
+ else:
+ # If no paragraph boundary found, just truncate
+ html_content = html_content[:truncate_at]
+
+ # Add an ellipsis paragraph to indicate truncation
+ html_content += '
... (Content truncated due to length constraints)
'
+
+ logger.warning(f"✅ Truncated HTML to {len(html_content)} chars (at paragraph boundary)")
+
logger.debug(f"✅ Converted markdown to HTML: {len(html_content)} chars, preview: {html_content[:200]}...")
headers = {
diff --git a/backend/services/integrations/wix/seo.py b/backend/services/integrations/wix/seo.py
index febf48c4..899a72d9 100644
--- a/backend/services/integrations/wix/seo.py
+++ b/backend/services/integrations/wix/seo.py
@@ -27,7 +27,8 @@ def build_seo_data(seo_metadata: Dict[str, Any], default_title: str = None) -> O
"""
seo_data = {
'settings': {
- 'keywords': []
+ 'keywords': [],
+ 'preventAutoRedirect': False # Required by Wix API schema
},
'tags': []
}
@@ -40,7 +41,8 @@ def build_seo_data(seo_metadata: Dict[str, Any], default_title: str = None) -> O
if focus_keyword:
keywords_list.append({
'term': str(focus_keyword),
- 'isMain': True
+ 'isMain': True,
+ 'origin': 'USER' # Required by Wix API
})
# Add additional keywords from blog_tags or other sources
@@ -51,7 +53,8 @@ def build_seo_data(seo_metadata: Dict[str, Any], default_title: str = None) -> O
if tag_str and tag_str != focus_keyword: # Don't duplicate main keyword
keywords_list.append({
'term': tag_str,
- 'isMain': False
+ 'isMain': False,
+ 'origin': 'USER' # Required by Wix API
})
# Add social hashtags as keywords if available
@@ -63,9 +66,17 @@ def build_seo_data(seo_metadata: Dict[str, Any], default_title: str = None) -> O
if hashtag_str and hashtag_str != focus_keyword:
keywords_list.append({
'term': hashtag_str,
- 'isMain': False
+ 'isMain': False,
+ 'origin': 'USER' # Required by Wix API
})
+ # CRITICAL: Wix Blog API limits keywords to maximum 5
+ # Prioritize: main keyword first, then most important additional keywords
+ if len(keywords_list) > 5:
+ logger.warning(f"Truncating keywords from {len(keywords_list)} to 5 (Wix API limit)")
+ # Keep main keyword + next 4 most important
+ keywords_list = keywords_list[:5]
+
seo_data['settings']['keywords'] = keywords_list
# Validate keywords list is not empty (or ensure at least one keyword exists)
@@ -89,13 +100,13 @@ def build_seo_data(seo_metadata: Dict[str, Any], default_title: str = None) -> O
})
# SEO title - 'title' type uses 'children' field, not 'props.content'
+ # Per Wix API example: title tags don't need 'custom' or 'disabled' fields
seo_title = seo_metadata.get('seo_title') or default_title
if seo_title:
tags_list.append({
'type': 'title',
- 'children': str(seo_title), # Title tags use 'children', not 'props.content'
- 'custom': True,
- 'disabled': False
+ 'children': str(seo_title) # Title tags use 'children', not 'props.content'
+ # Note: Wix example doesn't show 'custom' or 'disabled' for title tags
})
# Open Graph tags
diff --git a/backend/services/scheduler/core/failure_detection_service.py b/backend/services/scheduler/core/failure_detection_service.py
new file mode 100644
index 00000000..493b0820
--- /dev/null
+++ b/backend/services/scheduler/core/failure_detection_service.py
@@ -0,0 +1,378 @@
+"""
+Failure Detection Service
+Analyzes execution logs to detect failure patterns and mark tasks for human intervention.
+"""
+
+from datetime import datetime, timedelta
+from typing import Dict, Any, Optional, List
+from sqlalchemy.orm import Session
+from enum import Enum
+import json
+
+from utils.logger_utils import get_service_logger
+
+logger = get_service_logger("failure_detection")
+
+
+class FailureReason(Enum):
+ """Categories of failure reasons."""
+ API_LIMIT = "api_limit" # 429, rate limits, quota exceeded
+ AUTH_ERROR = "auth_error" # 401, 403, token expired
+ NETWORK_ERROR = "network_error" # Connection errors, timeouts
+ CONFIG_ERROR = "config_error" # Missing config, invalid parameters
+ UNKNOWN = "unknown" # Other errors
+
+
+class FailurePattern:
+ """Represents a failure pattern for a task."""
+
+ def __init__(
+ self,
+ task_id: int,
+ task_type: str,
+ user_id: str,
+ consecutive_failures: int,
+ recent_failures: int,
+ failure_reason: FailureReason,
+ last_failure_time: Optional[datetime],
+ error_patterns: List[str],
+ should_cool_off: bool
+ ):
+ self.task_id = task_id
+ self.task_type = task_type
+ self.user_id = user_id
+ self.consecutive_failures = consecutive_failures
+ self.recent_failures = recent_failures
+ self.failure_reason = failure_reason
+ self.last_failure_time = last_failure_time
+ self.error_patterns = error_patterns
+ self.should_cool_off = should_cool_off
+
+
+class FailureDetectionService:
+ """Service for detecting failure patterns in task execution logs."""
+
+ # Cool-off thresholds
+ CONSECUTIVE_FAILURE_THRESHOLD = 3 # 3 consecutive failures
+ RECENT_FAILURE_THRESHOLD = 5 # 5 failures in last 7 days
+ COOL_OFF_PERIOD_DAYS = 7 # Cool-off period after marking for intervention
+
+ def __init__(self, db: Session):
+ self.db = db
+ self.logger = logger
+
+ def analyze_task_failures(
+ self,
+ task_id: int,
+ task_type: str,
+ user_id: str
+ ) -> Optional[FailurePattern]:
+ """
+ Analyze failure patterns for a specific task.
+
+ Args:
+ task_id: Task ID
+ task_type: Task type (oauth_token_monitoring, website_analysis, etc.)
+ user_id: User ID
+
+ Returns:
+ FailurePattern if pattern detected, None otherwise
+ """
+ try:
+ # Get execution logs for this task
+ execution_logs = self._get_execution_logs(task_id, task_type)
+
+ if not execution_logs:
+ return None
+
+ # Analyze failure patterns
+ consecutive_failures = self._count_consecutive_failures(execution_logs)
+ recent_failures = self._count_recent_failures(execution_logs, days=7)
+ failure_reason = self._classify_failure_reason(execution_logs)
+ error_patterns = self._extract_error_patterns(execution_logs)
+ last_failure_time = self._get_last_failure_time(execution_logs)
+
+ # Determine if task should be cooled off
+ should_cool_off = (
+ consecutive_failures >= self.CONSECUTIVE_FAILURE_THRESHOLD or
+ recent_failures >= self.RECENT_FAILURE_THRESHOLD
+ )
+
+ if should_cool_off:
+ self.logger.warning(
+ f"Failure pattern detected for task {task_id} ({task_type}): "
+ f"consecutive={consecutive_failures}, recent={recent_failures}, "
+ f"reason={failure_reason.value}"
+ )
+
+ return FailurePattern(
+ task_id=task_id,
+ task_type=task_type,
+ user_id=user_id,
+ consecutive_failures=consecutive_failures,
+ recent_failures=recent_failures,
+ failure_reason=failure_reason,
+ last_failure_time=last_failure_time,
+ error_patterns=error_patterns,
+ should_cool_off=should_cool_off
+ )
+
+ except Exception as e:
+ self.logger.error(f"Error analyzing task failures for task {task_id}: {e}", exc_info=True)
+ return None
+
+ def _get_execution_logs(self, task_id: int, task_type: str) -> List[Dict[str, Any]]:
+ """Get execution logs for a task."""
+ try:
+ if task_type == "oauth_token_monitoring":
+ from models.oauth_token_monitoring_models import OAuthTokenExecutionLog
+ logs = self.db.query(OAuthTokenExecutionLog).filter(
+ OAuthTokenExecutionLog.task_id == task_id
+ ).order_by(OAuthTokenExecutionLog.execution_date.desc()).all()
+
+ return [
+ {
+ "status": log.status,
+ "error_message": log.error_message,
+ "execution_date": log.execution_date,
+ "result_data": log.result_data
+ }
+ for log in logs
+ ]
+ elif task_type == "website_analysis":
+ from models.website_analysis_monitoring_models import WebsiteAnalysisExecutionLog
+ logs = self.db.query(WebsiteAnalysisExecutionLog).filter(
+ WebsiteAnalysisExecutionLog.task_id == task_id
+ ).order_by(WebsiteAnalysisExecutionLog.execution_date.desc()).all()
+
+ return [
+ {
+ "status": log.status,
+ "error_message": log.error_message,
+ "execution_date": log.execution_date,
+ "result_data": log.result_data
+ }
+ for log in logs
+ ]
+ elif task_type in ["gsc_insights", "bing_insights", "platform_insights"]:
+ from models.platform_insights_monitoring_models import PlatformInsightsExecutionLog
+ logs = self.db.query(PlatformInsightsExecutionLog).filter(
+ PlatformInsightsExecutionLog.task_id == task_id
+ ).order_by(PlatformInsightsExecutionLog.execution_date.desc()).all()
+
+ return [
+ {
+ "status": log.status,
+ "error_message": log.error_message,
+ "execution_date": log.execution_date,
+ "result_data": log.result_data
+ }
+ for log in logs
+ ]
+ else:
+ # Fallback to monitoring_task execution logs
+ from models.monitoring_models import TaskExecutionLog
+ logs = self.db.query(TaskExecutionLog).filter(
+ TaskExecutionLog.task_id == task_id
+ ).order_by(TaskExecutionLog.execution_date.desc()).all()
+
+ return [
+ {
+ "status": log.status,
+ "error_message": log.error_message,
+ "execution_date": log.execution_date,
+ "result_data": log.result_data
+ }
+ for log in logs
+ ]
+ except Exception as e:
+ self.logger.error(f"Error getting execution logs for task {task_id}: {e}", exc_info=True)
+ return []
+
+ def _count_consecutive_failures(self, logs: List[Dict[str, Any]]) -> int:
+ """Count consecutive failures from most recent."""
+ count = 0
+ for log in logs:
+ if log["status"] == "failed":
+ count += 1
+ else:
+ break # Stop at first success
+ return count
+
+ def _count_recent_failures(self, logs: List[Dict[str, Any]], days: int = 7) -> int:
+ """Count failures in the last N days."""
+ cutoff = datetime.utcnow() - timedelta(days=days)
+ return sum(
+ 1 for log in logs
+ if log["status"] == "failed" and log["execution_date"] >= cutoff
+ )
+
+ def _classify_failure_reason(self, logs: List[Dict[str, Any]]) -> FailureReason:
+ """Classify the primary failure reason from error messages."""
+ # Check most recent failures first
+ recent_failures = [log for log in logs if log["status"] == "failed"][:5]
+
+ for log in recent_failures:
+ error_message = (log.get("error_message") or "").lower()
+ result_data = log.get("result_data") or {}
+
+ # Check for API limits (429)
+ if "429" in error_message or "rate limit" in error_message or "limit reached" in error_message:
+ return FailureReason.API_LIMIT
+
+ # Check result_data for API limit info
+ if isinstance(result_data, dict):
+ if result_data.get("error_status") == 429:
+ return FailureReason.API_LIMIT
+ if "limit" in str(result_data).lower() and "reached" in str(result_data).lower():
+ return FailureReason.API_LIMIT
+ # Check for usage info indicating limits
+ usage_info = result_data.get("usage_info", {})
+ if isinstance(usage_info, dict):
+ if usage_info.get("usage_percentage", 0) >= 100:
+ return FailureReason.API_LIMIT
+
+ # Check for auth errors
+ if "401" in error_message or "403" in error_message or "unauthorized" in error_message or "forbidden" in error_message:
+ return FailureReason.AUTH_ERROR
+ if "token" in error_message and ("expired" in error_message or "invalid" in error_message):
+ return FailureReason.AUTH_ERROR
+
+ # Check for network errors
+ if "timeout" in error_message or "connection" in error_message or "network" in error_message:
+ return FailureReason.NETWORK_ERROR
+
+ # Check for config errors
+ if "config" in error_message or "missing" in error_message or "invalid" in error_message:
+ return FailureReason.CONFIG_ERROR
+
+ return FailureReason.UNKNOWN
+
+ def _extract_error_patterns(self, logs: List[Dict[str, Any]]) -> List[str]:
+ """Extract common error patterns from failure logs."""
+ patterns = []
+ recent_failures = [log for log in logs if log["status"] == "failed"][:5]
+
+ for log in recent_failures:
+ error_message = log.get("error_message") or ""
+ if error_message:
+ # Extract key phrases (first 100 chars)
+ pattern = error_message[:100].strip()
+ if pattern and pattern not in patterns:
+ patterns.append(pattern)
+
+ return patterns[:3] # Return top 3 patterns
+
+ def _get_last_failure_time(self, logs: List[Dict[str, Any]]) -> Optional[datetime]:
+ """Get the timestamp of the most recent failure."""
+ for log in logs:
+ if log["status"] == "failed":
+ return log["execution_date"]
+ return None
+
+ def get_tasks_needing_intervention(
+ self,
+ user_id: Optional[str] = None,
+ task_type: Optional[str] = None
+ ) -> List[Dict[str, Any]]:
+ """
+ Get all tasks that need human intervention.
+
+ Args:
+ user_id: Optional user ID filter
+ task_type: Optional task type filter
+
+ Returns:
+ List of task dictionaries with failure pattern info
+ """
+ try:
+ tasks_needing_intervention = []
+
+ # Check OAuth token monitoring tasks
+ from models.oauth_token_monitoring_models import OAuthTokenMonitoringTask
+ oauth_tasks = self.db.query(OAuthTokenMonitoringTask).filter(
+ OAuthTokenMonitoringTask.status == "needs_intervention"
+ )
+ if user_id:
+ oauth_tasks = oauth_tasks.filter(OAuthTokenMonitoringTask.user_id == user_id)
+
+ for task in oauth_tasks.all():
+ pattern = self.analyze_task_failures(task.id, "oauth_token_monitoring", task.user_id)
+ if pattern:
+ tasks_needing_intervention.append({
+ "task_id": task.id,
+ "task_type": "oauth_token_monitoring",
+ "user_id": task.user_id,
+ "platform": task.platform,
+ "failure_pattern": {
+ "consecutive_failures": pattern.consecutive_failures,
+ "recent_failures": pattern.recent_failures,
+ "failure_reason": pattern.failure_reason.value,
+ "last_failure_time": pattern.last_failure_time.isoformat() if pattern.last_failure_time else None,
+ "error_patterns": pattern.error_patterns
+ },
+ "failure_reason": task.failure_reason,
+ "last_failure": task.last_failure.isoformat() if task.last_failure else None
+ })
+
+ # Check website analysis tasks
+ from models.website_analysis_monitoring_models import WebsiteAnalysisTask
+ website_tasks = self.db.query(WebsiteAnalysisTask).filter(
+ WebsiteAnalysisTask.status == "needs_intervention"
+ )
+ if user_id:
+ website_tasks = website_tasks.filter(WebsiteAnalysisTask.user_id == user_id)
+
+ for task in website_tasks.all():
+ pattern = self.analyze_task_failures(task.id, "website_analysis", task.user_id)
+ if pattern:
+ tasks_needing_intervention.append({
+ "task_id": task.id,
+ "task_type": "website_analysis",
+ "user_id": task.user_id,
+ "website_url": task.website_url,
+ "failure_pattern": {
+ "consecutive_failures": pattern.consecutive_failures,
+ "recent_failures": pattern.recent_failures,
+ "failure_reason": pattern.failure_reason.value,
+ "last_failure_time": pattern.last_failure_time.isoformat() if pattern.last_failure_time else None,
+ "error_patterns": pattern.error_patterns
+ },
+ "failure_reason": task.failure_reason,
+ "last_failure": task.last_failure.isoformat() if task.last_failure else None
+ })
+
+ # Check platform insights tasks
+ from models.platform_insights_monitoring_models import PlatformInsightsTask
+ insights_tasks = self.db.query(PlatformInsightsTask).filter(
+ PlatformInsightsTask.status == "needs_intervention"
+ )
+ if user_id:
+ insights_tasks = insights_tasks.filter(PlatformInsightsTask.user_id == user_id)
+
+ for task in insights_tasks.all():
+ task_type_str = f"{task.platform}_insights"
+ pattern = self.analyze_task_failures(task.id, task_type_str, task.user_id)
+ if pattern:
+ tasks_needing_intervention.append({
+ "task_id": task.id,
+ "task_type": task_type_str,
+ "user_id": task.user_id,
+ "platform": task.platform,
+ "failure_pattern": {
+ "consecutive_failures": pattern.consecutive_failures,
+ "recent_failures": pattern.recent_failures,
+ "failure_reason": pattern.failure_reason.value,
+ "last_failure_time": pattern.last_failure_time.isoformat() if pattern.last_failure_time else None,
+ "error_patterns": pattern.error_patterns
+ },
+ "failure_reason": task.failure_reason,
+ "last_failure": task.last_failure.isoformat() if task.last_failure else None
+ })
+
+ return tasks_needing_intervention
+
+ except Exception as e:
+ self.logger.error(f"Error getting tasks needing intervention: {e}", exc_info=True)
+ return []
+
diff --git a/backend/services/scheduler/core/task_execution_handler.py b/backend/services/scheduler/core/task_execution_handler.py
index d5ccd2db..3c60a0d8 100644
--- a/backend/services/scheduler/core/task_execution_handler.py
+++ b/backend/services/scheduler/core/task_execution_handler.py
@@ -22,7 +22,8 @@ async def execute_task_async(
scheduler: 'TaskScheduler',
task_type: str,
task: Any,
- summary: Optional[Dict[str, Any]] = None
+ summary: Optional[Dict[str, Any]] = None,
+ execution_source: str = "scheduler" # "scheduler" or "manual"
):
"""
Execute a single task asynchronously with user isolation.
@@ -98,6 +99,19 @@ async def execute_task_async(
except Exception as e:
logger.debug(f"Could not extract user_id after merge for task {task_id}: {e}")
+ # Check if task is in cool-off (skip if scheduler-triggered, allow if manual)
+ if execution_source == "scheduler":
+ if hasattr(task, 'status') and task.status == "needs_intervention":
+ logger.warning(
+ f"[Scheduler] ⏸️ Skipping task {task_id} - marked for human intervention. "
+ f"Use manual trigger to retry."
+ )
+ scheduler.stats['tasks_skipped'] += 1
+ if summary:
+ summary.setdefault('skipped', 0)
+ summary['skipped'] += 1
+ return
+
# Get executor for this task type
try:
executor = scheduler.registry.get_executor(task_type)
diff --git a/backend/services/scheduler/executors/bing_insights_executor.py b/backend/services/scheduler/executors/bing_insights_executor.py
index bea18558..f7e87fa2 100644
--- a/backend/services/scheduler/executors/bing_insights_executor.py
+++ b/backend/services/scheduler/executors/bing_insights_executor.py
@@ -86,6 +86,9 @@ class BingInsightsExecutor(TaskExecutor):
task.last_success = datetime.utcnow()
task.status = 'active'
task.failure_reason = None
+ # Reset failure tracking on success
+ task.consecutive_failures = 0
+ task.failure_pattern = None
# Schedule next check (7 days from now)
task.next_check = self.calculate_next_execution(
task=task,
@@ -93,11 +96,41 @@ class BingInsightsExecutor(TaskExecutor):
last_execution=task.last_check
)
else:
+ # Analyze failure pattern
+ from services.scheduler.core.failure_detection_service import FailureDetectionService
+ failure_detection = FailureDetectionService(db)
+ pattern = failure_detection.analyze_task_failures(
+ task.id, "bing_insights", task.user_id
+ )
+
task.last_failure = datetime.utcnow()
task.failure_reason = result.error_message
- task.status = 'failed'
- # Schedule retry in 1 day
- task.next_check = datetime.utcnow() + timedelta(days=1)
+
+ if pattern and pattern.should_cool_off:
+ # Mark task for human intervention
+ task.status = "needs_intervention"
+ task.consecutive_failures = pattern.consecutive_failures
+ task.failure_pattern = {
+ "consecutive_failures": pattern.consecutive_failures,
+ "recent_failures": pattern.recent_failures,
+ "failure_reason": pattern.failure_reason.value,
+ "error_patterns": pattern.error_patterns,
+ "cool_off_until": (datetime.utcnow() + timedelta(days=7)).isoformat()
+ }
+ # Clear next_check - task won't run automatically
+ task.next_check = None
+
+ self.logger.warning(
+ f"Task {task.id} marked for human intervention: "
+ f"{pattern.consecutive_failures} consecutive failures, "
+ f"reason: {pattern.failure_reason.value}"
+ )
+ else:
+ # Normal failure handling
+ task.status = 'failed'
+ task.consecutive_failures = (task.consecutive_failures or 0) + 1
+ # Schedule retry in 1 day
+ task.next_check = datetime.utcnow() + timedelta(days=1)
task.updated_at = datetime.utcnow()
db.commit()
@@ -117,12 +150,35 @@ class BingInsightsExecutor(TaskExecutor):
context="Bing insights fetch"
)
+ # Analyze failure pattern
+ from services.scheduler.core.failure_detection_service import FailureDetectionService
+ failure_detection = FailureDetectionService(db)
+ pattern = failure_detection.analyze_task_failures(
+ task.id, "bing_insights", task.user_id
+ )
+
# Update task
task.last_check = datetime.utcnow()
task.last_failure = datetime.utcnow()
task.failure_reason = str(e)
- task.status = 'failed'
- task.next_check = datetime.utcnow() + timedelta(days=1)
+
+ if pattern and pattern.should_cool_off:
+ # Mark task for human intervention
+ task.status = "needs_intervention"
+ task.consecutive_failures = pattern.consecutive_failures
+ task.failure_pattern = {
+ "consecutive_failures": pattern.consecutive_failures,
+ "recent_failures": pattern.recent_failures,
+ "failure_reason": pattern.failure_reason.value,
+ "error_patterns": pattern.error_patterns,
+ "cool_off_until": (datetime.utcnow() + timedelta(days=7)).isoformat()
+ }
+ task.next_check = None
+ else:
+ task.status = 'failed'
+ task.consecutive_failures = (task.consecutive_failures or 0) + 1
+ task.next_check = datetime.utcnow() + timedelta(days=1)
+
task.updated_at = datetime.utcnow()
db.commit()
diff --git a/backend/services/scheduler/executors/gsc_insights_executor.py b/backend/services/scheduler/executors/gsc_insights_executor.py
index 8d03cc55..3ae1e875 100644
--- a/backend/services/scheduler/executors/gsc_insights_executor.py
+++ b/backend/services/scheduler/executors/gsc_insights_executor.py
@@ -85,6 +85,9 @@ class GSCInsightsExecutor(TaskExecutor):
task.last_success = datetime.utcnow()
task.status = 'active'
task.failure_reason = None
+ # Reset failure tracking on success
+ task.consecutive_failures = 0
+ task.failure_pattern = None
# Schedule next check (7 days from now)
task.next_check = self.calculate_next_execution(
task=task,
@@ -92,11 +95,41 @@ class GSCInsightsExecutor(TaskExecutor):
last_execution=task.last_check
)
else:
+ # Analyze failure pattern
+ from services.scheduler.core.failure_detection_service import FailureDetectionService
+ failure_detection = FailureDetectionService(db)
+ pattern = failure_detection.analyze_task_failures(
+ task.id, "gsc_insights", task.user_id
+ )
+
task.last_failure = datetime.utcnow()
task.failure_reason = result.error_message
- task.status = 'failed'
- # Schedule retry in 1 day
- task.next_check = datetime.utcnow() + timedelta(days=1)
+
+ if pattern and pattern.should_cool_off:
+ # Mark task for human intervention
+ task.status = "needs_intervention"
+ task.consecutive_failures = pattern.consecutive_failures
+ task.failure_pattern = {
+ "consecutive_failures": pattern.consecutive_failures,
+ "recent_failures": pattern.recent_failures,
+ "failure_reason": pattern.failure_reason.value,
+ "error_patterns": pattern.error_patterns,
+ "cool_off_until": (datetime.utcnow() + timedelta(days=7)).isoformat()
+ }
+ # Clear next_check - task won't run automatically
+ task.next_check = None
+
+ self.logger.warning(
+ f"Task {task.id} marked for human intervention: "
+ f"{pattern.consecutive_failures} consecutive failures, "
+ f"reason: {pattern.failure_reason.value}"
+ )
+ else:
+ # Normal failure handling
+ task.status = 'failed'
+ task.consecutive_failures = (task.consecutive_failures or 0) + 1
+ # Schedule retry in 1 day
+ task.next_check = datetime.utcnow() + timedelta(days=1)
task.updated_at = datetime.utcnow()
db.commit()
@@ -116,12 +149,35 @@ class GSCInsightsExecutor(TaskExecutor):
context="GSC insights fetch"
)
+ # Analyze failure pattern
+ from services.scheduler.core.failure_detection_service import FailureDetectionService
+ failure_detection = FailureDetectionService(db)
+ pattern = failure_detection.analyze_task_failures(
+ task.id, "gsc_insights", task.user_id
+ )
+
# Update task
task.last_check = datetime.utcnow()
task.last_failure = datetime.utcnow()
task.failure_reason = str(e)
- task.status = 'failed'
- task.next_check = datetime.utcnow() + timedelta(days=1)
+
+ if pattern and pattern.should_cool_off:
+ # Mark task for human intervention
+ task.status = "needs_intervention"
+ task.consecutive_failures = pattern.consecutive_failures
+ task.failure_pattern = {
+ "consecutive_failures": pattern.consecutive_failures,
+ "recent_failures": pattern.recent_failures,
+ "failure_reason": pattern.failure_reason.value,
+ "error_patterns": pattern.error_patterns,
+ "cool_off_until": (datetime.utcnow() + timedelta(days=7)).isoformat()
+ }
+ task.next_check = None
+ else:
+ task.status = 'failed'
+ task.consecutive_failures = (task.consecutive_failures or 0) + 1
+ task.next_check = datetime.utcnow() + timedelta(days=1)
+
task.updated_at = datetime.utcnow()
db.commit()
diff --git a/backend/services/scheduler/executors/oauth_token_monitoring_executor.py b/backend/services/scheduler/executors/oauth_token_monitoring_executor.py
index ee91057a..e482d1b6 100644
--- a/backend/services/scheduler/executors/oauth_token_monitoring_executor.py
+++ b/backend/services/scheduler/executors/oauth_token_monitoring_executor.py
@@ -92,6 +92,9 @@ class OAuthTokenMonitoringExecutor(TaskExecutor):
task.last_success = datetime.utcnow()
task.status = 'active'
task.failure_reason = None
+ # Reset failure tracking on success
+ task.consecutive_failures = 0
+ task.failure_pattern = None
# Schedule next check (7 days from now)
task.next_check = self.calculate_next_execution(
task=task,
@@ -99,14 +102,44 @@ class OAuthTokenMonitoringExecutor(TaskExecutor):
last_execution=task.last_check
)
else:
- # Refresh failed - mark as failed and stop automatic retries
+ # Analyze failure pattern
+ from services.scheduler.core.failure_detection_service import FailureDetectionService
+ failure_detection = FailureDetectionService(db)
+ pattern = failure_detection.analyze_task_failures(
+ task.id, "oauth_token_monitoring", task.user_id
+ )
+
task.last_failure = datetime.utcnow()
task.failure_reason = result.error_message
- task.status = 'failed'
- # Do NOT update next_check - wait for manual trigger
+
+ if pattern and pattern.should_cool_off:
+ # Mark task for human intervention
+ task.status = "needs_intervention"
+ task.consecutive_failures = pattern.consecutive_failures
+ task.failure_pattern = {
+ "consecutive_failures": pattern.consecutive_failures,
+ "recent_failures": pattern.recent_failures,
+ "failure_reason": pattern.failure_reason.value,
+ "error_patterns": pattern.error_patterns,
+ "cool_off_until": (datetime.utcnow() + timedelta(days=7)).isoformat()
+ }
+ # Clear next_check - task won't run automatically
+ task.next_check = None
+
+ self.logger.warning(
+ f"Task {task.id} marked for human intervention: "
+ f"{pattern.consecutive_failures} consecutive failures, "
+ f"reason: {pattern.failure_reason.value}"
+ )
+ else:
+ # Normal failure handling
+ task.status = 'failed'
+ task.consecutive_failures = (task.consecutive_failures or 0) + 1
+ # Do NOT update next_check - wait for manual trigger
+
self.logger.warning(
f"OAuth token refresh failed for user {user_id}, platform {platform}. "
- f"Task marked as failed. No automatic retry will be scheduled."
+ f"{'Task marked for human intervention' if pattern and pattern.should_cool_off else 'Task marked as failed. No automatic retry will be scheduled.'}"
)
# Create UsageAlert notification for the user
diff --git a/backend/services/scheduler/executors/website_analysis_executor.py b/backend/services/scheduler/executors/website_analysis_executor.py
index 7a140e54..aba1498b 100644
--- a/backend/services/scheduler/executors/website_analysis_executor.py
+++ b/backend/services/scheduler/executors/website_analysis_executor.py
@@ -106,6 +106,9 @@ class WebsiteAnalysisExecutor(TaskExecutor):
task.last_success = datetime.utcnow()
task.status = 'active'
task.failure_reason = None
+ # Reset failure tracking on success
+ task.consecutive_failures = 0
+ task.failure_pattern = None
# Schedule next check based on frequency_days
task.next_check = self.calculate_next_execution(
task=task,
@@ -123,17 +126,48 @@ class WebsiteAnalysisExecutor(TaskExecutor):
)
return result
else:
+ # Analyze failure pattern
+ from services.scheduler.core.failure_detection_service import FailureDetectionService
+ failure_detection = FailureDetectionService(db)
+ pattern = failure_detection.analyze_task_failures(
+ task.id, "website_analysis", task.user_id
+ )
+
task.last_failure = datetime.utcnow()
task.failure_reason = result.error_message
- task.status = 'failed'
- # Do NOT update next_check - wait for manual retry
+
+ if pattern and pattern.should_cool_off:
+ # Mark task for human intervention
+ task.status = "needs_intervention"
+ task.consecutive_failures = pattern.consecutive_failures
+ task.failure_pattern = {
+ "consecutive_failures": pattern.consecutive_failures,
+ "recent_failures": pattern.recent_failures,
+ "failure_reason": pattern.failure_reason.value,
+ "error_patterns": pattern.error_patterns,
+ "cool_off_until": (datetime.utcnow() + timedelta(days=7)).isoformat()
+ }
+ # Clear next_check - task won't run automatically
+ task.next_check = None
+
+ self.logger.warning(
+ f"Task {task.id} marked for human intervention: "
+ f"{pattern.consecutive_failures} consecutive failures, "
+ f"reason: {pattern.failure_reason.value}"
+ )
+ else:
+ # Normal failure handling
+ task.status = 'failed'
+ task.consecutive_failures = (task.consecutive_failures or 0) + 1
+ # Do NOT update next_check - wait for manual retry
# Commit all changes to database
db.commit()
self.logger.warning(
f"Website analysis failed for task {task.id}. "
- f"Error: {result.error_message}. Waiting for manual retry."
+ f"Error: {result.error_message}. "
+ f"{'Marked for human intervention' if pattern and pattern.should_cool_off else 'Waiting for manual retry'}."
)
return result
diff --git a/backend/services/story_writer/README.md b/backend/services/story_writer/README.md
new file mode 100644
index 00000000..8f5c13e1
--- /dev/null
+++ b/backend/services/story_writer/README.md
@@ -0,0 +1,96 @@
+# 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
+
+```python
+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.
diff --git a/backend/services/story_writer/__init__.py b/backend/services/story_writer/__init__.py
new file mode 100644
index 00000000..b979e768
--- /dev/null
+++ b/backend/services/story_writer/__init__.py
@@ -0,0 +1,10 @@
+"""
+Story Writer Service
+
+Provides story generation functionality using prompt chaining.
+Supports multiple personas, styles, and iterative story generation.
+"""
+
+from .story_service import StoryWriterService
+
+__all__ = ['StoryWriterService']
diff --git a/backend/services/story_writer/audio_generation_service.py b/backend/services/story_writer/audio_generation_service.py
new file mode 100644
index 00000000..e75ec296
--- /dev/null
+++ b/backend/services/story_writer/audio_generation_service.py
@@ -0,0 +1,291 @@
+"""
+Audio Generation Service for Story Writer
+
+Generates audio narration for story scenes using TTS (Text-to-Speech) providers.
+"""
+
+import os
+import uuid
+from typing import List, Dict, Any, Optional
+from pathlib import Path
+from loguru import logger
+from fastapi import HTTPException
+
+
+class StoryAudioGenerationService:
+ """Service for generating audio narration for story scenes."""
+
+ def __init__(self, output_dir: Optional[str] = None):
+ """
+ Initialize the audio generation service.
+
+ Parameters:
+ output_dir (str, optional): Directory to save generated audio files.
+ Defaults to 'backend/story_audio' if not provided.
+ """
+ if output_dir:
+ self.output_dir = Path(output_dir)
+ else:
+ # Default to backend/story_audio directory
+ base_dir = Path(__file__).parent.parent.parent
+ self.output_dir = base_dir / "story_audio"
+
+ # Create output directory if it doesn't exist
+ self.output_dir.mkdir(parents=True, exist_ok=True)
+ logger.info(f"[StoryAudioGeneration] Initialized with output directory: {self.output_dir}")
+
+ def _generate_audio_filename(self, scene_number: int, scene_title: str) -> str:
+ """Generate a unique filename for a scene audio file."""
+ # Clean scene title for filename
+ clean_title = "".join(c if c.isalnum() or c in ('-', '_') else '_' for c in scene_title[:30])
+ unique_id = str(uuid.uuid4())[:8]
+ return f"scene_{scene_number}_{clean_title}_{unique_id}.mp3"
+
+ def _generate_audio_gtts(
+ self,
+ text: str,
+ output_path: Path,
+ lang: str = "en",
+ slow: bool = False
+ ) -> bool:
+ """
+ Generate audio using Google Text-to-Speech (gTTS).
+
+ Parameters:
+ text (str): Text to convert to speech.
+ output_path (Path): Path to save the audio file.
+ lang (str): Language code (default: "en").
+ slow (bool): Whether to speak slowly (default: False).
+
+ Returns:
+ bool: True if generation was successful, False otherwise.
+ """
+ try:
+ from gtts import gTTS
+
+ # Generate speech
+ tts = gTTS(text=text, lang=lang, slow=slow)
+
+ # Save to file
+ tts.save(str(output_path))
+
+ logger.info(f"[StoryAudioGeneration] Generated audio using gTTS: {output_path}")
+ return True
+
+ except ImportError:
+ logger.error("[StoryAudioGeneration] gTTS not installed. Install with: pip install gtts")
+ return False
+ except Exception as e:
+ logger.error(f"[StoryAudioGeneration] Error generating audio with gTTS: {e}")
+ return False
+
+ def _generate_audio_pyttsx3(
+ self,
+ text: str,
+ output_path: Path,
+ rate: int = 150,
+ voice: Optional[str] = None
+ ) -> bool:
+ """
+ Generate audio using pyttsx3 (offline TTS).
+
+ Parameters:
+ text (str): Text to convert to speech.
+ output_path (Path): Path to save the audio file.
+ rate (int): Speech rate (default: 150).
+ voice (str, optional): Voice ID to use.
+
+ Returns:
+ bool: True if generation was successful, False otherwise.
+ """
+ try:
+ import pyttsx3
+
+ # Initialize TTS engine
+ engine = pyttsx3.init()
+
+ # Set speech rate
+ engine.setProperty('rate', rate)
+
+ # Set voice if provided
+ if voice:
+ voices = engine.getProperty('voices')
+ for v in voices:
+ if voice in v.id:
+ engine.setProperty('voice', v.id)
+ break
+
+ # Generate speech and save to file
+ engine.save_to_file(text, str(output_path))
+ engine.runAndWait()
+
+ logger.info(f"[StoryAudioGeneration] Generated audio using pyttsx3: {output_path}")
+ return True
+
+ except ImportError:
+ logger.error("[StoryAudioGeneration] pyttsx3 not installed. Install with: pip install pyttsx3")
+ return False
+ except Exception as e:
+ logger.error(f"[StoryAudioGeneration] Error generating audio with pyttsx3: {e}")
+ return False
+
+ def generate_scene_audio(
+ self,
+ scene: Dict[str, Any],
+ user_id: str,
+ provider: str = "gtts",
+ lang: str = "en",
+ slow: bool = False,
+ rate: int = 150
+ ) -> Dict[str, Any]:
+ """
+ Generate audio narration for a single story scene.
+
+ Parameters:
+ scene (Dict[str, Any]): Scene data with audio_narration text.
+ user_id (str): Clerk user ID for subscription checking (for future usage tracking).
+ provider (str): TTS provider to use ("gtts", "pyttsx3", etc.).
+ lang (str): Language code for TTS (default: "en").
+ slow (bool): Whether to speak slowly (default: False, gTTS only).
+ rate (int): Speech rate (default: 150, pyttsx3 only).
+
+ Returns:
+ Dict[str, Any]: Audio metadata including file path, URL, and scene info.
+ """
+ scene_number = scene.get("scene_number", 0)
+ scene_title = scene.get("title", "Untitled")
+ audio_narration = scene.get("audio_narration", "")
+
+ if not audio_narration:
+ raise ValueError(f"Scene {scene_number} ({scene_title}) has no audio_narration")
+
+ try:
+ logger.info(f"[StoryAudioGeneration] Generating audio for scene {scene_number}: {scene_title}")
+ logger.debug(f"[StoryAudioGeneration] Audio narration: {audio_narration[:100]}...")
+
+ # Generate audio filename
+ audio_filename = self._generate_audio_filename(scene_number, scene_title)
+ audio_path = self.output_dir / audio_filename
+
+ # Generate audio based on provider
+ success = False
+ if provider == "gtts":
+ success = self._generate_audio_gtts(
+ text=audio_narration,
+ output_path=audio_path,
+ lang=lang,
+ slow=slow
+ )
+ elif provider == "pyttsx3":
+ success = self._generate_audio_pyttsx3(
+ text=audio_narration,
+ output_path=audio_path,
+ rate=rate
+ )
+ else:
+ # Default to gTTS
+ logger.warning(f"[StoryAudioGeneration] Unknown provider '{provider}', using gTTS")
+ success = self._generate_audio_gtts(
+ text=audio_narration,
+ output_path=audio_path,
+ lang=lang,
+ slow=slow
+ )
+
+ if not success or not audio_path.exists():
+ raise RuntimeError(f"Failed to generate audio file: {audio_path}")
+
+ # Get file size
+ file_size = audio_path.stat().st_size
+
+ logger.info(f"[StoryAudioGeneration] Saved audio to: {audio_path} ({file_size} bytes)")
+
+ # Return audio metadata
+ return {
+ "scene_number": scene_number,
+ "scene_title": scene_title,
+ "audio_path": str(audio_path),
+ "audio_filename": audio_filename,
+ "audio_url": f"/api/story/audio/{audio_filename}", # API endpoint to serve audio
+ "provider": provider,
+ "file_size": file_size,
+ }
+
+ except HTTPException:
+ # Re-raise HTTPExceptions (e.g., 429 subscription limit)
+ raise
+ except Exception as e:
+ logger.error(f"[StoryAudioGeneration] Error generating audio for scene {scene_number}: {e}")
+ raise RuntimeError(f"Failed to generate audio for scene {scene_number}: {str(e)}") from e
+
+ def generate_scene_audio_list(
+ self,
+ scenes: List[Dict[str, Any]],
+ user_id: str,
+ provider: str = "gtts",
+ lang: str = "en",
+ slow: bool = False,
+ rate: int = 150,
+ progress_callback: Optional[callable] = None
+ ) -> List[Dict[str, Any]]:
+ """
+ Generate audio narration for multiple story scenes.
+
+ Parameters:
+ scenes (List[Dict[str, Any]]): List of scene data with audio_narration text.
+ user_id (str): Clerk user ID for subscription checking.
+ provider (str): TTS provider to use ("gtts", "pyttsx3", etc.).
+ lang (str): Language code for TTS (default: "en").
+ slow (bool): Whether to speak slowly (default: False, gTTS only).
+ rate (int): Speech rate (default: 150, pyttsx3 only).
+ progress_callback (callable, optional): Callback function for progress updates.
+
+ Returns:
+ List[Dict[str, Any]]: List of audio metadata for each scene.
+ """
+ if not scenes:
+ raise ValueError("No scenes provided for audio generation")
+
+ logger.info(f"[StoryAudioGeneration] Generating audio for {len(scenes)} scenes")
+
+ audio_results = []
+ total_scenes = len(scenes)
+
+ for idx, scene in enumerate(scenes):
+ try:
+ # Generate audio for scene
+ audio_result = self.generate_scene_audio(
+ scene=scene,
+ user_id=user_id,
+ provider=provider,
+ lang=lang,
+ slow=slow,
+ rate=rate
+ )
+
+ audio_results.append(audio_result)
+
+ # Call progress callback if provided
+ if progress_callback:
+ progress = ((idx + 1) / total_scenes) * 100
+ progress_callback(progress, f"Generated audio for scene {scene.get('scene_number', idx + 1)}")
+
+ logger.info(f"[StoryAudioGeneration] Generated audio {idx + 1}/{total_scenes}")
+
+ except Exception as e:
+ logger.error(f"[StoryAudioGeneration] Failed to generate audio for scene {idx + 1}: {e}")
+ # Continue with next scene instead of failing completely
+ # Use empty strings for required fields instead of None
+ audio_results.append({
+ "scene_number": scene.get("scene_number", idx + 1),
+ "scene_title": scene.get("title", "Untitled"),
+ "audio_filename": "",
+ "audio_url": "",
+ "provider": provider,
+ "file_size": 0,
+ "error": str(e),
+ })
+
+ logger.info(f"[StoryAudioGeneration] Generated {len(audio_results)} audio files out of {total_scenes} scenes")
+ return audio_results
+
diff --git a/backend/services/story_writer/image_generation_service.py b/backend/services/story_writer/image_generation_service.py
new file mode 100644
index 00000000..f668fedc
--- /dev/null
+++ b/backend/services/story_writer/image_generation_service.py
@@ -0,0 +1,196 @@
+"""
+Image Generation Service for Story Writer
+
+Generates images for story scenes using the existing image generation service.
+"""
+
+import os
+import base64
+import uuid
+from typing import List, Dict, Any, Optional
+from pathlib import Path
+from fastapi import HTTPException
+
+from services.llm_providers.main_image_generation import generate_image
+from services.llm_providers.image_generation import ImageGenerationResult
+from utils.logger_utils import get_service_logger
+
+logger = get_service_logger("story_writer.image_generation")
+
+
+class StoryImageGenerationService:
+ """Service for generating images for story scenes."""
+
+ def __init__(self, output_dir: Optional[str] = None):
+ """
+ Initialize the image generation service.
+
+ Parameters:
+ output_dir (str, optional): Directory to save generated images.
+ Defaults to 'backend/story_images' if not provided.
+ """
+ if output_dir:
+ self.output_dir = Path(output_dir)
+ else:
+ # Default to backend/story_images directory
+ base_dir = Path(__file__).parent.parent.parent
+ self.output_dir = base_dir / "story_images"
+
+ # Create output directory if it doesn't exist
+ self.output_dir.mkdir(parents=True, exist_ok=True)
+ logger.info(f"[StoryImageGeneration] Initialized with output directory: {self.output_dir}")
+
+ def _generate_image_filename(self, scene_number: int, scene_title: str) -> str:
+ """Generate a unique filename for a scene image."""
+ # Clean scene title for filename
+ clean_title = "".join(c if c.isalnum() or c in ('-', '_') else '_' for c in scene_title[:30])
+ unique_id = str(uuid.uuid4())[:8]
+ return f"scene_{scene_number}_{clean_title}_{unique_id}.png"
+
+ def generate_scene_image(
+ self,
+ scene: Dict[str, Any],
+ user_id: str,
+ provider: Optional[str] = None,
+ width: int = 1024,
+ height: int = 1024,
+ model: Optional[str] = None
+ ) -> Dict[str, Any]:
+ """
+ Generate an image for a single story scene.
+
+ Parameters:
+ scene (Dict[str, Any]): Scene data with image_prompt.
+ user_id (str): Clerk user ID for subscription checking.
+ provider (str, optional): Image generation provider (gemini, huggingface, stability).
+ width (int): Image width (default: 1024).
+ height (int): Image height (default: 1024).
+ model (str, optional): Model to use for image generation.
+
+ Returns:
+ Dict[str, Any]: Image metadata including file path, URL, and scene info.
+ """
+ scene_number = scene.get("scene_number", 0)
+ scene_title = scene.get("title", "Untitled")
+ image_prompt = scene.get("image_prompt", "")
+
+ if not image_prompt:
+ raise ValueError(f"Scene {scene_number} ({scene_title}) has no image_prompt")
+
+ try:
+ logger.info(f"[StoryImageGeneration] Generating image for scene {scene_number}: {scene_title}")
+ logger.debug(f"[StoryImageGeneration] Image prompt: {image_prompt[:100]}...")
+
+ # Generate image using main_image_generation service
+ image_options = {
+ "provider": provider,
+ "width": width,
+ "height": height,
+ "model": model,
+ }
+
+ result: ImageGenerationResult = generate_image(
+ prompt=image_prompt,
+ options=image_options,
+ user_id=user_id
+ )
+
+ # Save image to file
+ image_filename = self._generate_image_filename(scene_number, scene_title)
+ image_path = self.output_dir / image_filename
+
+ with open(image_path, "wb") as f:
+ f.write(result.image_bytes)
+
+ logger.info(f"[StoryImageGeneration] Saved image to: {image_path}")
+
+ # Return image metadata
+ # Use relative path for image_url (will be served via API endpoint)
+ return {
+ "scene_number": scene_number,
+ "scene_title": scene_title,
+ "image_path": str(image_path),
+ "image_filename": image_filename,
+ "image_url": f"/api/story/images/{image_filename}", # API endpoint to serve images
+ "width": result.width,
+ "height": result.height,
+ "provider": result.provider,
+ "model": result.model,
+ "seed": result.seed,
+ }
+
+ except HTTPException:
+ # Re-raise HTTPExceptions (e.g., 429 subscription limit)
+ raise
+ except Exception as e:
+ logger.error(f"[StoryImageGeneration] Error generating image for scene {scene_number}: {e}")
+ raise RuntimeError(f"Failed to generate image for scene {scene_number}: {str(e)}") from e
+
+ def generate_scene_images(
+ self,
+ scenes: List[Dict[str, Any]],
+ user_id: str,
+ provider: Optional[str] = None,
+ width: int = 1024,
+ height: int = 1024,
+ model: Optional[str] = None,
+ progress_callback: Optional[callable] = None
+ ) -> List[Dict[str, Any]]:
+ """
+ Generate images for multiple story scenes.
+
+ Parameters:
+ scenes (List[Dict[str, Any]]): List of scene data with image_prompts.
+ user_id (str): Clerk user ID for subscription checking.
+ provider (str, optional): Image generation provider (gemini, huggingface, stability).
+ width (int): Image width (default: 1024).
+ height (int): Image height (default: 1024).
+ model (str, optional): Model to use for image generation.
+ progress_callback (callable, optional): Callback function for progress updates.
+
+ Returns:
+ List[Dict[str, Any]]: List of image metadata for each scene.
+ """
+ if not scenes:
+ raise ValueError("No scenes provided for image generation")
+
+ logger.info(f"[StoryImageGeneration] Generating images for {len(scenes)} scenes")
+
+ image_results = []
+ total_scenes = len(scenes)
+
+ for idx, scene in enumerate(scenes):
+ try:
+ # Generate image for scene
+ image_result = self.generate_scene_image(
+ scene=scene,
+ user_id=user_id,
+ provider=provider,
+ width=width,
+ height=height,
+ model=model
+ )
+
+ image_results.append(image_result)
+
+ # Call progress callback if provided
+ if progress_callback:
+ progress = ((idx + 1) / total_scenes) * 100
+ progress_callback(progress, f"Generated image for scene {scene.get('scene_number', idx + 1)}")
+
+ logger.info(f"[StoryImageGeneration] Generated image {idx + 1}/{total_scenes}")
+
+ except Exception as e:
+ logger.error(f"[StoryImageGeneration] Failed to generate image for scene {idx + 1}: {e}")
+ # Continue with next scene instead of failing completely
+ image_results.append({
+ "scene_number": scene.get("scene_number", idx + 1),
+ "scene_title": scene.get("title", "Untitled"),
+ "error": str(e),
+ "image_path": None,
+ "image_url": None,
+ })
+
+ logger.info(f"[StoryImageGeneration] Generated {len(image_results)} images out of {total_scenes} scenes")
+ return image_results
+
diff --git a/backend/services/story_writer/service_components/__init__.py b/backend/services/story_writer/service_components/__init__.py
new file mode 100644
index 00000000..398be8e1
--- /dev/null
+++ b/backend/services/story_writer/service_components/__init__.py
@@ -0,0 +1,14 @@
+"""Story Writer service component helpers."""
+
+from .base import StoryServiceBase
+from .setup import StorySetupMixin
+from .outline import StoryOutlineMixin
+from .story_content import StoryContentMixin
+
+__all__ = [
+ "StoryServiceBase",
+ "StorySetupMixin",
+ "StoryOutlineMixin",
+ "StoryContentMixin",
+]
+
diff --git a/backend/services/story_writer/service_components/base.py b/backend/services/story_writer/service_components/base.py
new file mode 100644
index 00000000..91b391af
--- /dev/null
+++ b/backend/services/story_writer/service_components/base.py
@@ -0,0 +1,332 @@
+"""Core shared functionality for Story Writer service components."""
+
+from __future__ import annotations
+
+import json
+from typing import Any, Dict, List, Optional
+
+from fastapi import HTTPException
+from loguru import logger
+
+from services.llm_providers.main_text_generation import llm_text_gen
+
+
+class StoryServiceBase:
+ """Base class providing shared helpers for story writer operations."""
+
+ guidelines: str = """\
+Writing Guidelines:
+
+Delve deeper. Lose yourself in the world you're building. Unleash vivid
+descriptions to paint the scenes in your reader's mind.
+Develop your characters — let their motivations, fears, and complexities unfold naturally.
+Weave in the threads of your outline, but don't feel constrained by it.
+Allow your story to surprise you as you write. Use rich imagery, sensory details, and
+evocative language to bring the setting, characters, and events to life.
+Introduce elements subtly that can blossom into complex subplots, relationships,
+or worldbuilding details later in the story.
+Keep things intriguing but not fully resolved.
+Avoid boxing the story into a corner too early.
+Plant the seeds of subplots or potential character arc shifts that can be expanded later.
+
+IMPORTANT: Respect the story length target. Write with appropriate detail and pacing
+to reach the target word count, but do NOT exceed it. Once you've reached the target
+length and provided satisfying closure, conclude the story by writing IAMDONE.
+"""
+
+ # ------------------------------------------------------------------ #
+ # LLM Utilities
+ # ------------------------------------------------------------------ #
+
+ def generate_with_retry(
+ self,
+ prompt: str,
+ *,
+ system_prompt: Optional[str] = None,
+ user_id: Optional[str] = None,
+ ) -> str:
+ """Generate content using llm_text_gen with retry handling and subscription support."""
+ if not user_id:
+ raise RuntimeError("user_id is required for subscription checking")
+
+ try:
+ return llm_text_gen(prompt=prompt, system_prompt=system_prompt, user_id=user_id)
+ except HTTPException:
+ raise
+ except Exception as exc:
+ logger.error(f"Error generating content: {exc}")
+ raise RuntimeError(f"Failed to generate content: {exc}") from exc
+
+ # ------------------------------------------------------------------ #
+ # Prompt helpers
+ # ------------------------------------------------------------------ #
+
+ def build_persona_prompt(
+ self,
+ persona: str,
+ story_setting: str,
+ character_input: str,
+ plot_elements: str,
+ writing_style: str,
+ story_tone: str,
+ narrative_pov: str,
+ audience_age_group: str,
+ content_rating: str,
+ ending_preference: str,
+ ) -> str:
+ """Build the persona prompt with all story parameters."""
+ return f"""{persona}
+
+**STORY SETUP CONTEXT:**
+
+**Setting:**
+{story_setting}
+- Use this specific setting throughout the story
+- Incorporate setting details naturally into scenes and descriptions
+- Ensure the setting is clearly established and consistent
+
+**Characters:**
+{character_input}
+- Use these specific characters in the story
+- Develop these characters according to their descriptions
+- Maintain character consistency across all scenes
+- Create character arcs that align with the plot elements
+
+**Plot Elements:**
+{plot_elements}
+- Incorporate these plot elements into the story structure
+- Address each plot element in relevant scenes
+- Build connections between plot elements logically
+- Ensure the ending addresses the main plot elements
+
+**Writing Style:**
+{writing_style}
+- This writing style should be reflected in EVERY aspect of the story
+- The language, sentence structure, and narrative approach must match this style exactly
+- If this is a custom or combined style, interpret it in the context of the audience age group
+- Adapt the style's complexity to match {audience_age_group}
+
+**Story Tone:**
+{story_tone}
+- This tone must be maintained consistently throughout the entire story
+- The emotional atmosphere, mood, and overall feeling must match this tone
+- If this is a custom or combined tone, interpret it age-appropriately for {audience_age_group}
+- Ensure the tone is suitable for {content_rating} content rating
+
+**Narrative Point of View:**
+{narrative_pov}
+- Use this perspective consistently throughout the story
+- Maintain the chosen perspective in all narration
+- Apply the perspective appropriately for {audience_age_group}
+
+**Target Audience:**
+{audience_age_group}
+- ALL content must be age-appropriate for this audience
+- Language complexity, vocabulary, sentence length, and themes must match this age group
+- Concepts must be understandable and relatable to this audience
+- Adjust all story elements (style, tone, plot) to be appropriate for this age group
+
+**Content Rating:**
+{content_rating}
+- All content must stay within these content boundaries
+- Themes, language, and subject matter must respect this rating
+- Ensure the writing style and tone are compatible with this rating
+
+**Ending Preference:**
+{ending_preference}
+- The story should build toward this type of ending
+- All plot development should lead naturally to this ending style
+- Create expectations that align with this ending preference
+- Ensure the ending is appropriate for {audience_age_group} and {content_rating}
+
+**CRITICAL INSTRUCTIONS:**
+- Use ALL of the above story setup parameters to guide your writing
+- The writing style, tone, narrative POV, audience age group, and content rating are NOT optional - they are REQUIRED constraints
+- Every word, sentence, and description must align with these parameters
+- When parameters interact (e.g., style + age group, tone + content rating), ensure they work together harmoniously
+- Tailor the language complexity, vocabulary, and concepts to the specified audience age group
+- Maintain consistency with the specified writing style and tone throughout
+- Ensure all content is appropriate for the specified content rating
+- Build the narrative toward the specified ending preference
+- Use the setting, characters, and plot elements provided to create a coherent, engaging story
+
+Make sure the story is engaging, well-crafted, and perfectly tailored to ALL of the specified parameters above.
+"""
+
+ def _get_parameter_interaction_guidance(
+ self,
+ writing_style: str,
+ story_tone: str,
+ audience_age_group: str,
+ content_rating: str,
+ ) -> str:
+ """Generate guidance for interpreting custom/combined parameter values and their interactions."""
+ guidance = "**PARAMETER INTERACTION GUIDANCE:**\n\n"
+
+ style_words = writing_style.lower().split()
+ if len(style_words) > 1:
+ guidance += f"**Writing Style Analysis:** The style '{writing_style}' appears to combine multiple approaches:\n"
+ for word in style_words:
+ guidance += f"- '{word.title()}': Interpret this aspect in the context of {audience_age_group}\n"
+ guidance += (
+ "Combine all aspects naturally. For example, if 'Educational Playful':\n"
+ f" → Use playful, engaging language to teach concepts naturally\n"
+ f" → Make learning fun and interactive for {audience_age_group}\n"
+ " → Combine educational content with fun, magical elements\n\n"
+ )
+ else:
+ guidance += f"**Writing Style:** '{writing_style}'\n"
+ guidance += f"- Interpret this style appropriately for {audience_age_group}\n"
+ guidance += "- Adapt the style's complexity to match the audience's reading level\n\n"
+
+ tone_words = story_tone.lower().split()
+ if len(tone_words) > 1:
+ guidance += f"**Story Tone Analysis:** The tone '{story_tone}' combines multiple emotional qualities:\n"
+ for word in tone_words:
+ guidance += f"- '{word.title()}': Express this emotion in an age-appropriate way for {audience_age_group}\n"
+ guidance += (
+ "Blend these emotions throughout the story. For example, if 'Educational Whimsical':\n"
+ " → Use whimsical, playful language to convey educational concepts\n"
+ " → Make the tone both informative and magical\n"
+ f" → Combine wonder and learning in an age-appropriate way for {audience_age_group}\n\n"
+ )
+ else:
+ guidance += f"**Story Tone:** '{story_tone}'\n"
+ guidance += f"- Interpret this tone age-appropriately for {audience_age_group}\n"
+ guidance += f"- Ensure the tone is suitable for {content_rating} content rating\n\n"
+
+ guidance += "**PARAMETER INTERACTION EXAMPLES:**\n\n"
+
+ if "Children (5-12)" in audience_age_group:
+ guidance += f"- When writing_style is '{writing_style}' AND audience_age_group is 'Children (5-12)':\n"
+ guidance += " → Simplify the style's complexity while maintaining its essence\n"
+ guidance += " → Use age-appropriate vocabulary and sentence structure\n"
+ guidance += " → Make the style engaging and accessible for children\n\n"
+
+ if "Children (5-12)" in audience_age_group and "dark" in story_tone.lower():
+ guidance += f"- When story_tone is '{story_tone}' AND audience_age_group is 'Children (5-12)':\n"
+ guidance += " → Interpret 'dark' as mysterious and adventurous, not scary or frightening\n"
+ guidance += " → Use shadows, secrets, and puzzles rather than fear or horror\n"
+ guidance += " → Maintain a sense of wonder and excitement\n"
+ guidance += " → Keep it thrilling but age-appropriate\n\n"
+
+ guidance += f"- When writing_style is '{writing_style}' AND story_tone is '{story_tone}':\n"
+ guidance += " → Combine the style and tone naturally\n"
+ guidance += " → Use the style to express the tone effectively\n"
+ guidance += f" → Ensure both work together harmoniously for {audience_age_group}\n\n"
+
+ guidance += f"- When content_rating is '{content_rating}':\n"
+ guidance += " → Ensure the writing style and tone respect these content boundaries\n"
+ guidance += " → Adjust language, themes, and subject matter to fit the rating\n"
+ guidance += f" → Maintain age-appropriateness for {audience_age_group}\n\n"
+
+ guidance += "**PARAMETER CONFLICT RESOLUTION:**\n"
+ guidance += "If parameters seem to conflict, prioritize in this order:\n"
+ guidance += "1. Audience age group appropriateness (safety and comprehension) - HIGHEST PRIORITY\n"
+ guidance += "2. Content rating compliance (content boundaries)\n"
+ guidance += "3. Writing style and tone (creative expression)\n"
+ guidance += "4. Other parameters (narrative POV, ending preference)\n\n"
+ guidance += "Always ensure that ALL parameters work together to create appropriate, engaging content.\n"
+
+ return guidance
+
+ # ------------------------------------------------------------------ #
+ # Outline helpers shared across modules
+ # ------------------------------------------------------------------ #
+
+ def _format_outline_for_prompt(self, outline: Any) -> str:
+ """Format outline (structured or text) for use in prompts."""
+ if isinstance(outline, list):
+ outline_text = "\n".join(
+ [
+ f"Scene {scene.get('scene_number', idx + 1)}: {scene.get('title', 'Untitled')}\n"
+ f" Description: {scene.get('description', '')}\n"
+ f" Key Events: {', '.join(scene.get('key_events', []))}"
+ for idx, scene in enumerate(outline)
+ ]
+ )
+ return outline_text
+ return str(outline)
+
+ def _parse_text_outline(self, outline_prompt: str, user_id: str) -> List[Dict[str, Any]]:
+ """Fallback method to parse text outline if JSON parsing fails."""
+ outline_text = self.generate_with_retry(outline_prompt, user_id=user_id)
+
+ lines = outline_text.strip().split("\n")
+ scenes: List[Dict[str, Any]] = []
+ current_scene: Optional[Dict[str, Any]] = None
+
+ for line in lines:
+ cleaned = line.strip()
+ if not cleaned:
+ continue
+
+ if cleaned[0].isdigit() or cleaned.startswith("Scene") or cleaned.startswith("Chapter"):
+ if current_scene:
+ scenes.append(current_scene)
+
+ scene_number = len(scenes) + 1
+ title = cleaned.replace(f"{scene_number}.", "").replace("Scene", "").replace("Chapter", "").strip()
+ current_scene = {
+ "scene_number": scene_number,
+ "title": title or f"Scene {scene_number}",
+ "description": "",
+ "image_prompt": f"A scene from the story: {title}",
+ "audio_narration": "",
+ "character_descriptions": [],
+ "key_events": [],
+ }
+ continue
+
+ if current_scene:
+ if current_scene["description"]:
+ current_scene["description"] += " " + cleaned
+ else:
+ current_scene["description"] = cleaned
+
+ if current_scene["image_prompt"].startswith("A scene from the story"):
+ current_scene["image_prompt"] = f"A detailed visual representation of: {current_scene['description'][:200]}"
+ if not current_scene["audio_narration"]:
+ current_scene["audio_narration"] = (
+ current_scene["description"][:150] + "..."
+ if len(current_scene["description"]) > 150
+ else current_scene["description"]
+ )
+
+ if current_scene:
+ scenes.append(current_scene)
+
+ if not scenes:
+ scenes.append(
+ {
+ "scene_number": 1,
+ "title": "Story Outline",
+ "description": outline_text.strip(),
+ "image_prompt": f"A scene from the story: {outline_text[:200]}",
+ "audio_narration": outline_text[:150] + "..." if len(outline_text) > 150 else outline_text,
+ "character_descriptions": [],
+ "key_events": [],
+ }
+ )
+
+ logger.info(f"[StoryWriter] Parsed {len(scenes)} scenes from text outline")
+ return scenes
+
+ def _get_story_length_guidance(self, story_length: str) -> tuple[int, int]:
+ """Return word count guidance based on story length."""
+ story_length_lower = story_length.lower()
+ if "short" in story_length_lower or "1000" in story_length_lower:
+ return (1000, 0)
+ if "long" in story_length_lower or "10000" in story_length_lower:
+ return (3000, 2500)
+ return (2000, 1500)
+
+ @staticmethod
+ def load_json_response(response_text: Any) -> Dict[str, Any]:
+ """Normalize responses from llm_text_gen (dict or json string)."""
+ if isinstance(response_text, dict):
+ return response_text
+ if isinstance(response_text, str):
+ return json.loads(response_text)
+ raise ValueError(f"Unexpected response type: {type(response_text)}")
+
diff --git a/backend/services/story_writer/service_components/outline.py b/backend/services/story_writer/service_components/outline.py
new file mode 100644
index 00000000..ced0c213
--- /dev/null
+++ b/backend/services/story_writer/service_components/outline.py
@@ -0,0 +1,171 @@
+"""Story outline generation helpers."""
+
+from __future__ import annotations
+
+import json
+from typing import Any, Dict
+
+from fastapi import HTTPException
+from loguru import logger
+
+from services.llm_providers.main_text_generation import llm_text_gen
+
+from .base import StoryServiceBase
+
+
+class StoryOutlineMixin(StoryServiceBase):
+ """Provides outline generation behaviour."""
+
+ def _get_outline_schema(self) -> Dict[str, Any]:
+ """Return JSON schema for structured story outlines."""
+ return {
+ "type": "object",
+ "properties": {
+ "scenes": {
+ "type": "array",
+ "items": {
+ "type": "object",
+ "properties": {
+ "scene_number": {"type": "integer"},
+ "title": {"type": "string"},
+ "description": {"type": "string"},
+ "image_prompt": {"type": "string"},
+ "audio_narration": {"type": "string"},
+ "character_descriptions": {"type": "array", "items": {"type": "string"}},
+ "key_events": {"type": "array", "items": {"type": "string"}},
+ },
+ "required": ["scene_number", "title", "description", "image_prompt", "audio_narration"],
+ },
+ }
+ },
+ "required": ["scenes"],
+ }
+
+ def generate_outline(
+ self,
+ *,
+ premise: str,
+ persona: str,
+ story_setting: str,
+ character_input: str,
+ plot_elements: str,
+ writing_style: str,
+ story_tone: str,
+ narrative_pov: str,
+ audience_age_group: str,
+ content_rating: str,
+ ending_preference: str,
+ user_id: str,
+ use_structured_output: bool = True,
+ ) -> Any:
+ """Generate a story outline with optional structured JSON output."""
+ persona_prompt = self.build_persona_prompt(
+ persona,
+ story_setting,
+ character_input,
+ plot_elements,
+ writing_style,
+ story_tone,
+ narrative_pov,
+ audience_age_group,
+ content_rating,
+ ending_preference,
+ )
+
+ parameter_guidance = self._get_parameter_interaction_guidance(
+ writing_style, story_tone, audience_age_group, content_rating
+ )
+
+ outline_prompt = f"""\
+{persona_prompt}
+
+**PREMISE:**
+{premise}
+
+{parameter_guidance}
+
+**YOUR TASK:**
+Create a detailed story outline with multiple scenes that brings this premise to life. The outline must perfectly align with ALL of the story setup parameters provided above.
+
+**SCENE PROGRESSION STRUCTURE:**
+
+**Scene 1-2 (Opening):**
+- Introduce the setting ({story_setting}) and main characters ({character_input})
+- Establish the {story_tone} tone from the beginning
+- Set up the main conflict or adventure based on the plot elements ({plot_elements})
+- Hook the audience with an engaging opening that matches {writing_style} style
+- Use the {narrative_pov} perspective to establish the story world
+- Create intrigue and interest appropriate for {audience_age_group}
+- Respect the {content_rating} content rating from the start
+
+**Scene 3-7 (Development):**
+- Develop the plot elements ({plot_elements}) in detail
+- Build character relationships and growth using the specified characters ({character_input})
+- Create tension, obstacles, or challenges that advance the story
+- Maintain the {writing_style} style consistently throughout
+- Progress toward the {ending_preference} ending
+- Explore the setting ({story_setting}) more deeply
+- Ensure all content is age-appropriate for {audience_age_group}
+- Maintain the {story_tone} tone while developing the plot
+- Respect the {content_rating} content rating in all scenes
+- Use the {narrative_pov} perspective consistently
+
+**Final Scenes (Resolution):**
+- Resolve the main conflict established in the plot elements ({plot_elements})
+- Deliver the {ending_preference} ending
+- Tie together all plot elements and character arcs
+- Provide satisfying closure appropriate for {audience_age_group}
+- Maintain the {writing_style} style and {story_tone} tone until the end
+- Ensure the ending respects the {content_rating} content rating
+- Use the {narrative_pov} perspective to conclude the story
+
+**OUTLINE STRUCTURE:**
+For each scene, provide:
+1. **Scene Number and Title**
+2. **Description** (written in {writing_style}, maintaining {story_tone}, and age-appropriate for {audience_age_group})
+3. **Image Prompt** (vivid, visually descriptive, includes setting/characters, age-appropriate)
+4. **Audio Narration** (2-3 sentences, engaging, maintains style/tone, suitable for narration)
+5. **Character Descriptions** (for characters appearing in the scene)
+6. **Key Events** (bullet list of important happenings)
+
+**CONTEXT INTEGRATION REQUIREMENTS:**
+- Ensure every scene reflects the setting ({story_setting})
+- Keep characters consistent with ({character_input})
+- Integrate plot elements ({plot_elements}) logically
+- Maintain persona voice ({persona})
+- Respect audience age group ({audience_age_group}) and content rating ({content_rating})
+
+Before finalizing, verify that every scene adheres to the writing style, tone, age appropriateness, content rating, and narrative POV. Create 5-10 scenes that tell a complete, engaging story with clear progression and satisfying resolution.
+"""
+
+ try:
+ if use_structured_output:
+ outline_schema = self._get_outline_schema()
+ try:
+ response = self.load_json_response(
+ llm_text_gen(prompt=outline_prompt, json_struct=outline_schema, user_id=user_id)
+ )
+ scenes = response.get("scenes", [])
+ if scenes:
+ logger.info(f"[StoryWriter] Generated {len(scenes)} structured scenes for user {user_id}")
+ logger.info(
+ "[StoryWriter] Outline generated with parameters: "
+ f"audience={audience_age_group}, style={writing_style}, tone={story_tone}"
+ )
+ return scenes
+ logger.warning("[StoryWriter] No scenes found in structured output, falling back to text parsing")
+ raise ValueError("No scenes found in structured output")
+ except (json.JSONDecodeError, ValueError, KeyError) as exc:
+ logger.warning(
+ f"[StoryWriter] Failed to parse structured JSON outline ({exc}), falling back to text parsing"
+ )
+ return self._parse_text_outline(outline_prompt, user_id)
+
+ outline = self.generate_with_retry(outline_prompt, user_id=user_id)
+ return outline.strip()
+ except HTTPException:
+ raise
+ except Exception as exc:
+ logger.error(f"Outline Generation Error: {exc}")
+ raise RuntimeError(f"Failed to generate outline: {exc}") from exc
+
diff --git a/backend/services/story_writer/service_components/setup.py b/backend/services/story_writer/service_components/setup.py
new file mode 100644
index 00000000..0be30740
--- /dev/null
+++ b/backend/services/story_writer/service_components/setup.py
@@ -0,0 +1,273 @@
+"""Story setup generation helpers."""
+
+from __future__ import annotations
+
+import json
+from typing import Any, Dict, List
+
+from fastapi import HTTPException
+from loguru import logger
+
+from .base import StoryServiceBase
+
+
+class StorySetupMixin(StoryServiceBase):
+ """Provides story setup generation behaviour."""
+
+ def generate_premise(
+ self,
+ *,
+ persona: str,
+ story_setting: str,
+ character_input: str,
+ plot_elements: str,
+ writing_style: str,
+ story_tone: str,
+ narrative_pov: str,
+ audience_age_group: str,
+ content_rating: str,
+ ending_preference: str,
+ user_id: str,
+ ) -> str:
+ """Generate a story premise."""
+ persona_prompt = self.build_persona_prompt(
+ persona,
+ story_setting,
+ character_input,
+ plot_elements,
+ writing_style,
+ story_tone,
+ narrative_pov,
+ audience_age_group,
+ content_rating,
+ ending_preference,
+ )
+
+ parameter_guidance = self._get_parameter_interaction_guidance(
+ writing_style, story_tone, audience_age_group, content_rating
+ )
+
+ premise_prompt = f"""\
+{persona_prompt}
+
+{parameter_guidance}
+
+**TASK: Write a SINGLE, BRIEF premise sentence (1-2 sentences maximum, approximately 20-40 words) for this story.**
+
+The premise MUST:
+1. Be written in the specified {writing_style} writing style
+ - Interpret and apply this style appropriately for {audience_age_group}
+ - Match the language complexity, sentence structure, and narrative approach of this style
+2. Match the {story_tone} story tone exactly
+ - Express the emotional atmosphere and mood indicated by this tone
+ - Ensure the tone is age-appropriate for {audience_age_group}
+3. Be appropriate for {audience_age_group} with {content_rating} content rating
+ - Use language complexity that matches this audience's reading level
+ - Use vocabulary that is understandable to this age group
+ - Present concepts that are relatable and explainable to this audience
+ - Respect the {content_rating} content rating boundaries
+4. Briefly describe the story elements:
+ - Setting: {story_setting}
+ - Characters: {character_input}
+ - Main plot: {plot_elements}
+5. Be clear, engaging, and set up the story without telling the whole story
+6. Be written from the {narrative_pov} point of view
+7. Set up for a {ending_preference} ending
+
+**CRITICAL: This is a PREMISE, not the full story.**
+- Keep it to 1-2 sentences maximum (approximately 20-40 words)
+- Do NOT write the full story or multiple paragraphs
+- Do NOT reveal the resolution or ending
+- Focus on the setup: who, where, and what the main challenge/adventure is
+- Use ALL story setup parameters to guide your language and content choices
+- Tailor every word to the target audience ({audience_age_group}) and writing style ({writing_style})
+
+Write ONLY the premise sentence(s). Do not write anything else.
+"""
+
+ try:
+ premise = self.generate_with_retry(premise_prompt, user_id=user_id).strip()
+ sentences = premise.split(". ")
+ if len(sentences) > 2:
+ premise = ". ".join(sentences[:2])
+ if not premise.endswith("."):
+ premise += "."
+ return premise
+ except HTTPException:
+ raise
+ except Exception as exc:
+ logger.error(f"Premise Generation Error: {exc}")
+ raise RuntimeError(f"Failed to generate premise: {exc}") from exc
+
+ # ------------------------------------------------------------------ #
+ # Setup options
+ # ------------------------------------------------------------------ #
+
+ def _build_setup_schema(self) -> Dict[str, Any]:
+ """Return JSON schema for structured setup options."""
+ return {
+ "type": "object",
+ "properties": {
+ "options": {
+ "type": "array",
+ "items": {
+ "type": "object",
+ "properties": {
+ "persona": {"type": "string"},
+ "story_setting": {"type": "string"},
+ "character_input": {"type": "string"},
+ "plot_elements": {"type": "string"},
+ "writing_style": {"type": "string"},
+ "story_tone": {"type": "string"},
+ "narrative_pov": {"type": "string"},
+ "audience_age_group": {"type": "string"},
+ "content_rating": {"type": "string"},
+ "ending_preference": {"type": "string"},
+ "story_length": {"type": "string"},
+ "premise": {"type": "string"},
+ "reasoning": {"type": "string"},
+ },
+ "required": [
+ "persona",
+ "story_setting",
+ "character_input",
+ "plot_elements",
+ "writing_style",
+ "story_tone",
+ "narrative_pov",
+ "audience_age_group",
+ "content_rating",
+ "ending_preference",
+ "story_length",
+ "premise",
+ "reasoning",
+ ],
+ },
+ "minItems": 3,
+ "maxItems": 3,
+ }
+ },
+ "required": ["options"],
+ }
+
+ def generate_story_setup_options(
+ self,
+ *,
+ story_idea: str,
+ user_id: str,
+ ) -> List[Dict[str, Any]]:
+ """Generate 3 story setup options from a user's story idea."""
+
+ suggested_writing_styles = ['Formal', 'Casual', 'Poetic', 'Humorous', 'Academic', 'Journalistic', 'Narrative']
+ suggested_story_tones = ['Dark', 'Uplifting', 'Suspenseful', 'Whimsical', 'Melancholic', 'Mysterious', 'Romantic', 'Adventurous']
+ suggested_narrative_povs = ['First Person', 'Third Person Limited', 'Third Person Omniscient']
+ suggested_audience_age_groups = ['Children (5-12)', 'Young Adults (13-17)', 'Adults (18+)', 'All Ages']
+ suggested_content_ratings = ['G', 'PG', 'PG-13', 'R']
+ suggested_ending_preferences = ['Happy', 'Tragic', 'Cliffhanger', 'Twist', 'Open-ended', 'Bittersweet']
+
+ setup_prompt = f"""\
+You are an expert story writer and creative writing assistant. A user has provided the following story idea or information:
+
+{story_idea}
+
+Based on this story idea, generate exactly 3 different, well-thought-out story setup options. Each option should be CREATIVE, PERSONALIZED, and perfectly tailored to the user's specific story idea.
+
+**CRITICAL - Creative Freedom:**
+- You have COMPLETE FREEDOM to craft personalized values that best fit the user's story idea
+- Do NOT limit yourself to predefined options - create custom, creative values that perfectly match the story concept
+- For example, if the user wants "a story about how stars are made for a 5-year-old", you might create:
+ - Writing Style: "Educational Playful" or "Simple Scientific" (not just "Casual" or "Poetic")
+ - Story Tone: "Wonder-filled" or "Curious Discovery" (not just "Whimsical" or "Uplifting")
+ - Narrative POV: "Second Person (You)" or "Omniscient Narrator as Guide" (not just standard options)
+- The goal is to create the PERFECT setup for THIS specific story, not to fit into generic categories
+
+Each option should:
+1. Have a unique and creative persona that fits the story idea perfectly
+2. Define a compelling story setting that brings the idea to life
+3. Describe interesting and engaging characters
+4. Include key plot elements that drive the narrative
+5. Create CUSTOM, PERSONALIZED values for writing style, story tone, narrative POV, audience age group, content rating, and ending preference that best serve the story idea
+6. Select an appropriate story length: "Short (>1000 words)" for brief stories, "Medium (>5000 words)" for standard-length stories, or "Long (>10000 words)" for extended, detailed stories
+7. Generate a brief story premise (1-2 sentences, approximately 20-40 words) that summarizes the story concept
+8. Provide a brief reasoning (2-3 sentences) explaining why this setup works well for the story idea
+
+**IMPORTANT - Premise Requirements:**
+- The premise MUST be age-appropriate for the selected audience_age_group
+- For Children (5-12): Use simple, everyday words. Avoid complex vocabulary like "nebular", "ionized", "cosmic", "stellar", "melancholic", "bittersweet"
+- The premise MUST match the selected writing_style (e.g., if custom style is "Educational Playful", use playful educational language)
+- The premise MUST match the selected story_tone (e.g., if custom tone is "Wonder-filled", create a sense of wonder)
+- Keep the premise to 1-2 sentences maximum
+- Focus on who, where, and what the main challenge/adventure is
+
+**Suggested Options (for reference only - feel free to create better custom values):**
+- Writing Styles (suggestions): {', '.join(suggested_writing_styles)}
+- Story Tones (suggestions): {', '.join(suggested_story_tones)}
+- Narrative POVs (suggestions): {', '.join(suggested_narrative_povs)}
+- Audience Age Groups (suggestions): {', '.join(suggested_audience_age_groups)}
+- Content Ratings (suggestions): {', '.join(suggested_content_ratings)}
+- Ending Preferences (suggestions): {', '.join(suggested_ending_preferences)}
+- Story Lengths: "Short (>1000 words)", "Medium (>5000 words)", "Long (>10000 words)"
+
+**Remember:** These are ONLY suggestions. If a custom value better serves the story idea, CREATE IT!
+
+Return exactly 3 options as a JSON array. Each option must include a "premise" field with the story premise.
+"""
+
+ setup_schema = self._build_setup_schema()
+
+ try:
+ logger.info(f"[StoryWriter] Generating story setup options for user {user_id}")
+ response = self.load_json_response(
+ llm_text_gen(prompt=setup_prompt, json_struct=setup_schema, user_id=user_id)
+ )
+
+ options = response.get("options", [])
+ if len(options) != 3:
+ logger.warning(f"[StoryWriter] Expected 3 options but got {len(options)}, correcting count")
+ if len(options) < 3:
+ raise ValueError(f"Expected 3 options but got {len(options)}")
+ options = options[:3]
+
+ for idx, option in enumerate(options):
+ if not option.get("premise") or not option.get("premise", "").strip():
+ logger.info(f"[StoryWriter] Generating premise for option {idx + 1}")
+ try:
+ option["premise"] = self.generate_premise(
+ persona=option.get("persona", ""),
+ story_setting=option.get("story_setting", ""),
+ character_input=option.get("character_input", ""),
+ plot_elements=option.get("plot_elements", ""),
+ writing_style=option.get("writing_style", "Narrative"),
+ story_tone=option.get("story_tone", "Adventurous"),
+ narrative_pov=option.get("narrative_pov", "Third Person Limited"),
+ audience_age_group=option.get("audience_age_group", "All Ages"),
+ content_rating=option.get("content_rating", "G"),
+ ending_preference=option.get("ending_preference", "Happy"),
+ user_id=user_id,
+ )
+ except Exception as exc: # pragma: no cover - fallback clause
+ logger.warning(f"[StoryWriter] Failed to generate premise for option {idx + 1}: {exc}")
+ option["premise"] = (
+ f"A {option.get('story_setting', 'story')} story featuring "
+ f"{option.get('character_input', 'characters')}."
+ )
+ else:
+ premise = option["premise"].strip()
+ sentences = premise.split(". ")
+ if len(sentences) > 2:
+ premise = ". ".join(sentences[:2])
+ if not premise.endswith("."):
+ premise += "."
+ option["premise"] = premise
+
+ logger.info(f"[StoryWriter] Generated {len(options)} story setup options with premises for user {user_id}")
+ return options
+ except HTTPException:
+ raise
+ except json.JSONDecodeError as exc:
+ logger.error(f"[StoryWriter] Failed to parse JSON response for story setup: {exc}")
+ raise RuntimeError(f"Failed to parse story setup options: {exc}") from exc
+ except Exception as exc:
+ logger.error(f"[StoryWriter] Error generating story setup options: {exc}")
+ raise RuntimeError(f"Failed to generate story setup options: {exc}") from exc
+
diff --git a/backend/services/story_writer/service_components/story_content.py b/backend/services/story_writer/service_components/story_content.py
new file mode 100644
index 00000000..d2be9b3a
--- /dev/null
+++ b/backend/services/story_writer/service_components/story_content.py
@@ -0,0 +1,428 @@
+"""Story content generation helpers."""
+
+from __future__ import annotations
+
+from typing import Any, Dict, List, Optional
+
+from fastapi import HTTPException
+from loguru import logger
+
+from services.story_writer.image_generation_service import StoryImageGenerationService
+
+from .base import StoryServiceBase
+from .outline import StoryOutlineMixin
+
+
+class StoryContentMixin(StoryOutlineMixin):
+ """Provides story drafting and continuation behaviour."""
+
+ # ------------------------------------------------------------------ #
+ # Story start
+ # ------------------------------------------------------------------ #
+
+ def generate_story_start(
+ self,
+ *,
+ premise: str,
+ outline: Any,
+ persona: str,
+ story_setting: str,
+ character_input: str,
+ plot_elements: str,
+ writing_style: str,
+ story_tone: str,
+ narrative_pov: str,
+ audience_age_group: str,
+ content_rating: str,
+ ending_preference: str,
+ story_length: str = "Medium",
+ user_id: str,
+ ) -> str:
+ """Generate the starting section (or full short story)."""
+ persona_prompt = self.build_persona_prompt(
+ persona,
+ story_setting,
+ character_input,
+ plot_elements,
+ writing_style,
+ story_tone,
+ narrative_pov,
+ audience_age_group,
+ content_rating,
+ ending_preference,
+ )
+
+ outline_text = self._format_outline_for_prompt(outline)
+ story_length_lower = story_length.lower()
+ is_short_story = "short" in story_length_lower or "1000" in story_length_lower
+
+ if is_short_story:
+ logger.info(f"[StoryWriter] Generating complete short story (~1000 words) in single call for user {user_id}")
+ short_story_prompt = f"""\
+{persona_prompt}
+
+You have a gripping premise in mind:
+
+{premise}
+
+Your imagination has crafted a rich narrative outline:
+
+{outline_text}
+
+**YOUR TASK:**
+Write the COMPLETE story from beginning to end. This is a SHORT story, so you need to write the entire narrative in a single response.
+
+**STORY LENGTH TARGET:**
+- Target: Approximately 1000 words (900-1100 words acceptable)
+- This is a SHORT story, so be concise but complete
+- Cover all key scenes from your outline
+- Provide a satisfying conclusion that addresses all plot elements
+- Ensure the story makes sense as a complete narrative
+
+**STORY STRUCTURE:**
+1. **Opening**: Establish setting, characters, and initial situation
+2. **Development**: Develop the plot, introduce conflicts, build tension
+3. **Climax**: Reach the story's peak moment
+4. **Resolution**: Resolve conflicts and provide closure
+
+**IMPORTANT INSTRUCTIONS:**
+- Write the COMPLETE story in this single response
+- Aim for approximately 1000 words (900-1100 words)
+- Ensure the story is complete and makes sense as a standalone narrative
+- Include all essential elements from your outline
+- Provide a satisfying ending that matches the ending preference: {ending_preference}
+- Do NOT leave the story incomplete - this is the only generation call for short stories
+- Once you've finished the complete story, conclude naturally - do NOT write IAMDONE
+
+**WRITING STYLE:**
+{self.guidelines}
+
+**REMEMBER:**
+- This is a SHORT story - be concise but complete
+- Write the ENTIRE story in this response
+- Aim for ~1000 words
+- Ensure the story is complete and satisfying
+- Cover all key elements from your outline
+"""
+ try:
+ complete_story = self.generate_with_retry(short_story_prompt, user_id=user_id)
+ complete_story = complete_story.replace("IAMDONE", "").strip()
+ logger.info(
+ f"[StoryWriter] Generated complete short story ({len(complete_story.split())} words) for user {user_id}"
+ )
+ return complete_story
+ except HTTPException:
+ raise
+ except Exception as exc:
+ logger.error(f"Short Story Generation Error: {exc}")
+ raise RuntimeError(f"Failed to generate short story: {exc}") from exc
+
+ initial_word_count, _ = self._get_story_length_guidance(story_length)
+
+ starting_prompt = f"""\
+{persona_prompt}
+
+You have a gripping premise in mind:
+
+{premise}
+
+Your imagination has crafted a rich narrative outline:
+
+{outline_text}
+
+First, silently review the outline and the premise. Consider how to start the story.
+
+Start to write the very beginning of the story. You are not expected to finish
+the whole story now. Your writing should be detailed enough that you are only
+scratching the surface of the first bullet of your outline. Try to write AT
+MINIMUM {initial_word_count} WORDS.
+
+**STORY LENGTH TARGET:**
+This story is targeted to be {story_length}. Write with appropriate detail and pacing
+to reach this target length across the entire story. For this initial section, focus
+on establishing the setting, characters, and beginning of the plot in {initial_word_count} words.
+
+{self.guidelines}
+"""
+
+ try:
+ starting_draft = self.generate_with_retry(starting_prompt, user_id=user_id)
+ return starting_draft.strip()
+ except HTTPException:
+ raise
+ except Exception as exc:
+ logger.error(f"Story Start Generation Error: {exc}")
+ raise RuntimeError(f"Failed to generate story start: {exc}") from exc
+
+ # ------------------------------------------------------------------ #
+ # Continuation
+ # ------------------------------------------------------------------ #
+
+ def continue_story(
+ self,
+ *,
+ premise: str,
+ outline: Any,
+ story_text: str,
+ persona: str,
+ story_setting: str,
+ character_input: str,
+ plot_elements: str,
+ writing_style: str,
+ story_tone: str,
+ narrative_pov: str,
+ audience_age_group: str,
+ content_rating: str,
+ ending_preference: str,
+ story_length: str = "Medium",
+ user_id: str,
+ ) -> str:
+ """Continue writing the story."""
+ persona_prompt = self.build_persona_prompt(
+ persona,
+ story_setting,
+ character_input,
+ plot_elements,
+ writing_style,
+ story_tone,
+ narrative_pov,
+ audience_age_group,
+ content_rating,
+ ending_preference,
+ )
+
+ outline_text = self._format_outline_for_prompt(outline)
+ _, continuation_word_count = self._get_story_length_guidance(story_length)
+ current_word_count = len(story_text.split()) if story_text else 0
+
+ story_length_lower = story_length.lower()
+ if "short" in story_length_lower or "1000" in story_length_lower:
+ # Safety check: short stories shouldn't reach here
+ return "IAMDONE"
+
+ if "long" in story_length_lower or "10000" in story_length_lower:
+ target_total_words = 10000
+ else:
+ target_total_words = 4500
+
+ buffer_target = int(target_total_words * 1.05)
+
+ if current_word_count >= buffer_target:
+ logger.info(
+ f"[StoryWriter] Word count ({current_word_count}) at or past buffer target ({buffer_target}). Story is complete."
+ )
+ return "IAMDONE"
+
+ if current_word_count >= target_total_words and (current_word_count - target_total_words) < 50:
+ logger.info(
+ f"[StoryWriter] Word count ({current_word_count}) is very close to target ({target_total_words}). Story is complete."
+ )
+ return "IAMDONE"
+
+ remaining_words = max(0, buffer_target - current_word_count)
+ if remaining_words < 50:
+ logger.info(f"[StoryWriter] Remaining words ({remaining_words}) are minimal. Story is complete.")
+ return "IAMDONE"
+
+ continuation_prompt = f"""\
+{persona_prompt}
+
+You have a gripping premise in mind:
+
+{premise}
+
+Your imagination has crafted a rich narrative outline:
+
+{outline_text}
+
+You've begun to immerse yourself in this world, and the words are flowing.
+Here's what you've written so far:
+
+{story_text}
+
+=====
+
+First, silently review the outline and story so far. Identify what the single
+next part of your outline you should write.
+
+Your task is to continue where you left off and write the next part of the story.
+You are not expected to finish the whole story now. Your writing should be
+detailed enough that you are only scratching the surface of the next part of
+your outline. Try to write AT MINIMUM {continuation_word_count} WORDS.
+
+**STORY LENGTH TARGET:**
+This story is targeted to be {story_length} (target: {target_total_words} words total, with 5% buffer allowed).
+You have written approximately {current_word_count} words so far, leaving approximately
+{remaining_words} words remaining.
+
+**CRITICAL INSTRUCTIONS - READ CAREFULLY:**
+1. Write the next section with appropriate detail, aiming for approximately {min(continuation_word_count, remaining_words)} words.
+2. **STOP CONDITION:** If after writing this continuation, the total word count will reach or exceed {target_total_words} words, you MUST conclude the story immediately by writing IAMDONE.
+3. The story should reach a natural conclusion that addresses all plot elements and provides satisfying closure.
+4. Once you've written IAMDONE, do NOT write any more content - stop immediately.
+
+**WORD COUNT LIMIT:**
+- Target: {target_total_words} words total (with 5% buffer: {int(target_total_words * 1.05)} words maximum)
+- Current word count: {current_word_count} words
+- Remaining words: {remaining_words} words
+- **CRITICAL: If your continuation would bring the total to {target_total_words} words or more, conclude the story NOW and write IAMDONE.**
+- **Do NOT exceed {int(target_total_words * 1.05)} words. This is a hard limit.**
+- **Ensure the story is complete and makes sense when you write IAMDONE.**
+
+{self.guidelines}
+"""
+
+ try:
+ continuation = self.generate_with_retry(continuation_prompt, user_id=user_id)
+ return continuation.strip()
+ except HTTPException:
+ raise
+ except Exception as exc:
+ logger.error(f"Story Continuation Error: {exc}")
+ raise RuntimeError(f"Failed to continue story: {exc}") from exc
+
+ # ------------------------------------------------------------------ #
+ # Full generation orchestration
+ # ------------------------------------------------------------------ #
+
+ def generate_full_story(
+ self,
+ *,
+ persona: str,
+ story_setting: str,
+ character_input: str,
+ plot_elements: str,
+ writing_style: str,
+ story_tone: str,
+ narrative_pov: str,
+ audience_age_group: str,
+ content_rating: str,
+ ending_preference: str,
+ user_id: str,
+ max_iterations: int = 10,
+ ) -> Dict[str, Any]:
+ """Generate a complete story using prompt chaining."""
+ try:
+ logger.info(f"[StoryWriter] Generating premise for user {user_id}")
+ premise = self.generate_premise(
+ persona=persona,
+ story_setting=story_setting,
+ character_input=character_input,
+ plot_elements=plot_elements,
+ writing_style=writing_style,
+ story_tone=story_tone,
+ narrative_pov=narrative_pov,
+ audience_age_group=audience_age_group,
+ content_rating=content_rating,
+ ending_preference=ending_preference,
+ user_id=user_id,
+ )
+ if not premise:
+ raise RuntimeError("Failed to generate premise")
+
+ logger.info(f"[StoryWriter] Generating outline for user {user_id}")
+ outline = self.generate_outline(
+ premise=premise,
+ persona=persona,
+ story_setting=story_setting,
+ character_input=character_input,
+ plot_elements=plot_elements,
+ writing_style=writing_style,
+ story_tone=story_tone,
+ narrative_pov=narrative_pov,
+ audience_age_group=audience_age_group,
+ content_rating=content_rating,
+ ending_preference=ending_preference,
+ user_id=user_id,
+ )
+ if not outline:
+ raise RuntimeError("Failed to generate outline")
+
+ logger.info(f"[StoryWriter] Generating story start for user {user_id}")
+ draft = self.generate_story_start(
+ premise=premise,
+ outline=outline,
+ persona=persona,
+ story_setting=story_setting,
+ character_input=character_input,
+ plot_elements=plot_elements,
+ writing_style=writing_style,
+ story_tone=story_tone,
+ narrative_pov=narrative_pov,
+ audience_age_group=audience_age_group,
+ content_rating=content_rating,
+ ending_preference=ending_preference,
+ user_id=user_id,
+ )
+ if not draft:
+ raise RuntimeError("Failed to generate story start")
+
+ iteration = 0
+ while "IAMDONE" not in draft and iteration < max_iterations:
+ iteration += 1
+ logger.info(f"[StoryWriter] Continuation iteration {iteration}/{max_iterations}")
+ continuation = self.continue_story(
+ premise=premise,
+ outline=outline,
+ story_text=draft,
+ persona=persona,
+ story_setting=story_setting,
+ character_input=character_input,
+ plot_elements=plot_elements,
+ writing_style=writing_style,
+ story_tone=story_tone,
+ narrative_pov=narrative_pov,
+ audience_age_group=audience_age_group,
+ content_rating=content_rating,
+ ending_preference=ending_preference,
+ user_id=user_id,
+ )
+ if continuation:
+ draft += "\n\n" + continuation
+ else:
+ logger.warning(f"[StoryWriter] Empty continuation at iteration {iteration}")
+ break
+
+ final_story = draft.replace("IAMDONE", "").strip()
+
+ outline_response = outline
+ if isinstance(outline, list):
+ outline_response = "\n".join(
+ [
+ f"Scene {scene.get('scene_number', idx + 1)}: {scene.get('title', 'Untitled')}\n"
+ f" {scene.get('description', '')}"
+ for idx, scene in enumerate(outline)
+ ]
+ )
+
+ return {
+ "premise": premise,
+ "outline": str(outline_response),
+ "story": final_story,
+ "iterations": iteration,
+ "is_complete": "IAMDONE" in draft or iteration >= max_iterations,
+ }
+ except Exception as exc:
+ logger.error(f"[StoryWriter] Error generating full story: {exc}")
+ raise RuntimeError(f"Failed to generate full story: {exc}") from exc
+
+ # ------------------------------------------------------------------ #
+ # Multimedia helpers
+ # ------------------------------------------------------------------ #
+
+ def generate_scene_images(
+ self,
+ *,
+ scenes: List[Dict[str, Any]],
+ user_id: str,
+ provider: Optional[str] = None,
+ width: int = 1024,
+ height: int = 1024,
+ model: Optional[str] = None,
+ ) -> List[Dict[str, Any]]:
+ """Generate images for story scenes."""
+ image_service = StoryImageGenerationService()
+ return image_service.generate_scene_images(
+ scenes=scenes, user_id=user_id, provider=provider, width=width, height=height, model=model
+ )
+
diff --git a/backend/services/story_writer/story_service.py b/backend/services/story_writer/story_service.py
new file mode 100644
index 00000000..c74bc7b8
--- /dev/null
+++ b/backend/services/story_writer/story_service.py
@@ -0,0 +1,30 @@
+"""
+Story Writer Service
+
+Core service for generating stories using prompt chaining approach.
+Migrated from ToBeMigrated/ai_writers/ai_story_writer/ai_story_generator.py
+"""
+
+from typing import Dict, Any, Optional, List
+from loguru import logger
+from fastapi import HTTPException
+import json
+
+from services.llm_providers.main_text_generation import llm_text_gen
+from services.story_writer.service_components import (
+ StoryContentMixin,
+ StoryOutlineMixin,
+ StoryServiceBase,
+ StorySetupMixin,
+)
+
+
+class StoryWriterService(
+ StoryContentMixin,
+ StorySetupMixin,
+ StoryOutlineMixin,
+ StoryServiceBase,
+):
+ """Facade class combining story writer behaviours via modular mixins."""
+
+ __slots__ = ()
diff --git a/backend/services/story_writer/video_generation_service.py b/backend/services/story_writer/video_generation_service.py
new file mode 100644
index 00000000..87c7883c
--- /dev/null
+++ b/backend/services/story_writer/video_generation_service.py
@@ -0,0 +1,294 @@
+"""
+Video Generation Service for Story Writer
+
+Combines images and audio into animated video clips using MoviePy.
+"""
+
+import os
+import uuid
+from typing import List, Dict, Any, Optional
+from pathlib import Path
+from loguru import logger
+from fastapi import HTTPException
+
+
+class StoryVideoGenerationService:
+ """Service for generating videos from story scenes, images, and audio."""
+
+ def __init__(self, output_dir: Optional[str] = None):
+ """
+ Initialize the video generation service.
+
+ Parameters:
+ output_dir (str, optional): Directory to save generated videos.
+ Defaults to 'backend/story_videos' if not provided.
+ """
+ if output_dir:
+ self.output_dir = Path(output_dir)
+ else:
+ # Default to backend/story_videos directory
+ base_dir = Path(__file__).parent.parent.parent
+ self.output_dir = base_dir / "story_videos"
+
+ # Create output directory if it doesn't exist
+ self.output_dir.mkdir(parents=True, exist_ok=True)
+ logger.info(f"[StoryVideoGeneration] Initialized with output directory: {self.output_dir}")
+
+ def _generate_video_filename(self, story_title: str = "story") -> str:
+ """Generate a unique filename for a story video."""
+ # Clean story title for filename
+ clean_title = "".join(c if c.isalnum() or c in ('-', '_') else '_' for c in story_title[:30])
+ unique_id = str(uuid.uuid4())[:8]
+ return f"story_{clean_title}_{unique_id}.mp4"
+
+ def generate_scene_video(
+ self,
+ scene: Dict[str, Any],
+ image_path: str,
+ audio_path: str,
+ user_id: str,
+ duration: Optional[float] = None,
+ fps: int = 24
+ ) -> Dict[str, Any]:
+ """
+ Generate a video clip for a single story scene.
+
+ Parameters:
+ scene (Dict[str, Any]): Scene data.
+ image_path (str): Path to the scene image file.
+ audio_path (str): Path to the scene audio file.
+ user_id (str): Clerk user ID for subscription checking (for future usage tracking).
+ duration (float, optional): Video duration in seconds. If None, uses audio duration.
+ fps (int): Frames per second for video (default: 24).
+
+ Returns:
+ Dict[str, Any]: Video metadata including file path, URL, and scene info.
+ """
+ scene_number = scene.get("scene_number", 0)
+ scene_title = scene.get("title", "Untitled")
+
+ try:
+ logger.info(f"[StoryVideoGeneration] Generating video for scene {scene_number}: {scene_title}")
+
+ # Import MoviePy
+ try:
+ from moviepy.editor import ImageClip, AudioFileClip, concatenate_videoclips, CompositeVideoClip
+ except ImportError:
+ logger.error("[StoryVideoGeneration] MoviePy not installed. Install with: pip install moviepy imageio imageio-ffmpeg")
+ raise RuntimeError("MoviePy is not installed. Please install it to generate videos.")
+
+ # Load image and audio
+ image_file = Path(image_path)
+ audio_file = Path(audio_path)
+
+ if not image_file.exists():
+ raise FileNotFoundError(f"Image not found: {image_path}")
+ if not audio_file.exists():
+ raise FileNotFoundError(f"Audio not found: {audio_path}")
+
+ # Load audio to get duration
+ audio_clip = AudioFileClip(str(audio_file))
+ audio_duration = audio_clip.duration
+
+ # Use provided duration or audio duration
+ video_duration = duration if duration is not None else audio_duration
+
+ # Create image clip
+ image_clip = ImageClip(str(image_file)).set_duration(video_duration)
+ image_clip = image_clip.set_fps(fps)
+
+ # Set audio to image clip
+ video_clip = image_clip.set_audio(audio_clip)
+
+ # Generate video filename
+ video_filename = f"scene_{scene_number}_{scene_title.replace(' ', '_').replace('/', '_')[:50]}_{uuid.uuid4().hex[:8]}.mp4"
+ video_path = self.output_dir / video_filename
+
+ # Write video file
+ video_clip.write_videofile(
+ str(video_path),
+ fps=fps,
+ codec='libx264',
+ audio_codec='aac',
+ preset='medium',
+ threads=4,
+ logger=None # Disable MoviePy's default logger
+ )
+
+ # Clean up clips
+ video_clip.close()
+ audio_clip.close()
+ image_clip.close()
+
+ # Get file size
+ file_size = video_path.stat().st_size
+
+ logger.info(f"[StoryVideoGeneration] Saved video to: {video_path} ({file_size} bytes)")
+
+ # Return video metadata
+ return {
+ "scene_number": scene_number,
+ "scene_title": scene_title,
+ "video_path": str(video_path),
+ "video_filename": video_filename,
+ "video_url": f"/api/story/videos/{video_filename}", # API endpoint to serve videos
+ "duration": video_duration,
+ "fps": fps,
+ "file_size": file_size,
+ }
+
+ except HTTPException:
+ # Re-raise HTTPExceptions (e.g., 429 subscription limit)
+ raise
+ except Exception as e:
+ logger.error(f"[StoryVideoGeneration] Error generating video for scene {scene_number}: {e}")
+ raise RuntimeError(f"Failed to generate video for scene {scene_number}: {str(e)}") from e
+
+ def generate_story_video(
+ self,
+ scenes: List[Dict[str, Any]],
+ image_paths: List[str],
+ audio_paths: List[str],
+ user_id: str,
+ story_title: str = "Story",
+ fps: int = 24,
+ transition_duration: float = 0.5,
+ progress_callback: Optional[callable] = None
+ ) -> Dict[str, Any]:
+ """
+ Generate a complete story video from multiple scenes.
+
+ Parameters:
+ scenes (List[Dict[str, Any]]): List of scene data.
+ image_paths (List[str]): List of image file paths for each scene.
+ audio_paths (List[str]): List of audio file paths for each scene.
+ user_id (str): Clerk user ID for subscription checking.
+ story_title (str): Title of the story (default: "Story").
+ fps (int): Frames per second for video (default: 24).
+ transition_duration (float): Duration of transitions between scenes in seconds (default: 0.5).
+ progress_callback (callable, optional): Callback function for progress updates.
+
+ Returns:
+ Dict[str, Any]: Video metadata including file path, URL, and story info.
+ """
+ if not scenes or not image_paths or not audio_paths:
+ raise ValueError("Scenes, image paths, and audio paths are required")
+
+ if len(scenes) != len(image_paths) or len(scenes) != len(audio_paths):
+ raise ValueError("Number of scenes, image paths, and audio paths must match")
+
+ try:
+ logger.info(f"[StoryVideoGeneration] Generating story video for {len(scenes)} scenes")
+
+ # Import MoviePy
+ try:
+ from moviepy.editor import ImageClip, AudioFileClip, concatenate_videoclips, CompositeVideoClip
+ except ImportError:
+ logger.error("[StoryVideoGeneration] MoviePy not installed. Install with: pip install moviepy imageio imageio-ffmpeg")
+ raise RuntimeError("MoviePy is not installed. Please install it to generate videos.")
+
+ scene_clips = []
+ total_duration = 0.0
+
+ for idx, (scene, image_path, audio_path) in enumerate(zip(scenes, image_paths, audio_paths)):
+ try:
+ scene_number = scene.get("scene_number", idx + 1)
+ scene_title = scene.get("title", "Untitled")
+
+ logger.info(f"[StoryVideoGeneration] Processing scene {scene_number}/{len(scenes)}: {scene_title}")
+
+ # Load image and audio
+ image_file = Path(image_path)
+ audio_file = Path(audio_path)
+
+ if not image_file.exists():
+ logger.warning(f"[StoryVideoGeneration] Image not found: {image_path}, skipping scene {scene_number}")
+ continue
+ if not audio_file.exists():
+ logger.warning(f"[StoryVideoGeneration] Audio not found: {audio_path}, skipping scene {scene_number}")
+ continue
+
+ # Load audio to get duration
+ audio_clip = AudioFileClip(str(audio_file))
+ audio_duration = audio_clip.duration
+
+ # Create image clip
+ image_clip = ImageClip(str(image_file)).set_duration(audio_duration)
+ image_clip = image_clip.set_fps(fps)
+
+ # Set audio to image clip
+ video_clip = image_clip.set_audio(audio_clip)
+ scene_clips.append(video_clip)
+
+ total_duration += audio_duration
+
+ # Call progress callback if provided
+ if progress_callback:
+ progress = ((idx + 1) / len(scenes)) * 90 # Reserve 10% for final composition
+ progress_callback(progress, f"Processed scene {scene_number}/{len(scenes)}")
+
+ logger.info(f"[StoryVideoGeneration] Processed scene {idx + 1}/{len(scenes)}")
+
+ except Exception as e:
+ logger.error(f"[StoryVideoGeneration] Failed to process scene {idx + 1}: {e}")
+ # Continue with next scene instead of failing completely
+ continue
+
+ if not scene_clips:
+ raise RuntimeError("No valid scene clips were created")
+
+ # Concatenate all scene clips
+ logger.info(f"[StoryVideoGeneration] Concatenating {len(scene_clips)} scene clips")
+ final_video = concatenate_videoclips(scene_clips, method="compose")
+
+ # Generate video filename
+ video_filename = self._generate_video_filename(story_title)
+ video_path = self.output_dir / video_filename
+
+ # Call progress callback
+ if progress_callback:
+ progress_callback(95, "Rendering final video...")
+
+ # Write video file
+ final_video.write_videofile(
+ str(video_path),
+ fps=fps,
+ codec='libx264',
+ audio_codec='aac',
+ preset='medium',
+ threads=4,
+ logger=None # Disable MoviePy's default logger
+ )
+
+ # Get file size
+ file_size = video_path.stat().st_size
+
+ # Clean up clips
+ final_video.close()
+ for clip in scene_clips:
+ clip.close()
+
+ # Call progress callback
+ if progress_callback:
+ progress_callback(100, "Video generation complete!")
+
+ logger.info(f"[StoryVideoGeneration] Saved story video to: {video_path} ({file_size} bytes)")
+
+ # Return video metadata
+ return {
+ "video_path": str(video_path),
+ "video_filename": video_filename,
+ "video_url": f"/api/story/videos/{video_filename}", # API endpoint to serve videos
+ "duration": total_duration,
+ "fps": fps,
+ "file_size": file_size,
+ "num_scenes": len(scene_clips),
+ }
+
+ except HTTPException:
+ # Re-raise HTTPExceptions (e.g., 429 subscription limit)
+ raise
+ except Exception as e:
+ logger.error(f"[StoryVideoGeneration] Error generating story video: {e}")
+ raise RuntimeError(f"Failed to generate story video: {str(e)}") from e
+
diff --git a/backend/services/subscription/log_wrapping_service.py b/backend/services/subscription/log_wrapping_service.py
new file mode 100644
index 00000000..7dfebcad
--- /dev/null
+++ b/backend/services/subscription/log_wrapping_service.py
@@ -0,0 +1,231 @@
+"""
+Log Wrapping Service
+Intelligently wraps API usage logs when they exceed 5000 records.
+Aggregates old logs into cumulative records while preserving historical data.
+"""
+
+from typing import Dict, Any, List, Optional
+from datetime import datetime, timedelta
+from sqlalchemy.orm import Session
+from sqlalchemy import func, desc
+from loguru import logger
+
+from models.subscription_models import APIUsageLog, APIProvider
+
+
+class LogWrappingService:
+ """Service for wrapping and aggregating API usage logs."""
+
+ MAX_LOGS_PER_USER = 5000
+ AGGREGATION_THRESHOLD_DAYS = 30 # Aggregate logs older than 30 days
+
+ def __init__(self, db: Session):
+ self.db = db
+
+ def check_and_wrap_logs(self, user_id: str) -> Dict[str, Any]:
+ """
+ Check if user has exceeded log limit and wrap if necessary.
+
+ Returns:
+ Dict with wrapping status and statistics
+ """
+ try:
+ # Count total logs for user
+ total_count = self.db.query(func.count(APIUsageLog.id)).filter(
+ APIUsageLog.user_id == user_id
+ ).scalar() or 0
+
+ if total_count <= self.MAX_LOGS_PER_USER:
+ return {
+ 'wrapped': False,
+ 'total_logs': total_count,
+ 'max_logs': self.MAX_LOGS_PER_USER,
+ 'message': f'Log count ({total_count}) is within limit ({self.MAX_LOGS_PER_USER})'
+ }
+
+ # Need to wrap logs - aggregate old logs
+ logger.info(f"[LogWrapping] User {user_id} has {total_count} logs, exceeding limit of {self.MAX_LOGS_PER_USER}. Starting wrap...")
+
+ wrap_result = self._wrap_old_logs(user_id, total_count)
+
+ return {
+ 'wrapped': True,
+ 'total_logs_before': total_count,
+ 'total_logs_after': wrap_result['logs_remaining'],
+ 'aggregated_logs': wrap_result['aggregated_count'],
+ 'aggregated_periods': wrap_result['periods'],
+ 'message': f'Wrapped {wrap_result["aggregated_count"]} logs into {len(wrap_result["periods"])} aggregated records'
+ }
+
+ except Exception as e:
+ logger.error(f"[LogWrapping] Error checking/wrapping logs for user {user_id}: {e}", exc_info=True)
+ return {
+ 'wrapped': False,
+ 'error': str(e),
+ 'message': f'Error wrapping logs: {str(e)}'
+ }
+
+ def _wrap_old_logs(self, user_id: str, total_count: int) -> Dict[str, Any]:
+ """
+ Aggregate old logs into cumulative records.
+
+ Strategy:
+ 1. Keep most recent 4000 logs (detailed)
+ 2. Aggregate logs older than 30 days or oldest logs beyond 4000
+ 3. Create aggregated records grouped by provider and billing period
+ 4. Delete individual logs that were aggregated
+ """
+ try:
+ # Calculate how many logs to keep (4000 detailed, rest aggregated)
+ logs_to_keep = 4000
+ logs_to_aggregate = total_count - logs_to_keep
+
+ # Get cutoff date (30 days ago)
+ cutoff_date = datetime.utcnow() - timedelta(days=self.AGGREGATION_THRESHOLD_DAYS)
+
+ # Get logs to aggregate: oldest logs beyond the keep limit
+ # Order by timestamp ascending to get oldest first
+ # We'll keep the most recent logs_to_keep logs, aggregate the rest
+ logs_to_process = self.db.query(APIUsageLog).filter(
+ APIUsageLog.user_id == user_id
+ ).order_by(APIUsageLog.timestamp.asc()).limit(logs_to_aggregate).all()
+
+ if not logs_to_process:
+ return {
+ 'aggregated_count': 0,
+ 'logs_remaining': total_count,
+ 'periods': []
+ }
+
+ # Group logs by provider and billing period for aggregation
+ aggregated_data: Dict[str, Dict[str, Any]] = {}
+
+ for log in logs_to_process:
+ # Use provider value as key (e.g., "mistral" for huggingface)
+ provider_key = log.provider.value
+ # Special handling: if provider is MISTRAL but we want to show as huggingface
+ if provider_key == "mistral":
+ # Check if this is actually huggingface by looking at model or endpoint
+ # For now, we'll use "mistral" as the key but store actual provider name
+ provider_display = "huggingface" if "huggingface" in (log.model_used or "").lower() else "mistral"
+ else:
+ provider_display = provider_key
+
+ period_key = f"{provider_display}_{log.billing_period}"
+
+ if period_key not in aggregated_data:
+ aggregated_data[period_key] = {
+ 'provider': log.provider,
+ 'billing_period': log.billing_period,
+ 'count': 0,
+ 'total_tokens_input': 0,
+ 'total_tokens_output': 0,
+ 'total_tokens': 0,
+ 'total_cost_input': 0.0,
+ 'total_cost_output': 0.0,
+ 'total_cost': 0.0,
+ 'total_response_time': 0.0,
+ 'success_count': 0,
+ 'failed_count': 0,
+ 'oldest_timestamp': log.timestamp,
+ 'newest_timestamp': log.timestamp,
+ 'log_ids': []
+ }
+
+ agg = aggregated_data[period_key]
+ agg['count'] += 1
+ agg['total_tokens_input'] += log.tokens_input or 0
+ agg['total_tokens_output'] += log.tokens_output or 0
+ agg['total_tokens'] += log.tokens_total or 0
+ agg['total_cost_input'] += float(log.cost_input or 0.0)
+ agg['total_cost_output'] += float(log.cost_output or 0.0)
+ agg['total_cost'] += float(log.cost_total or 0.0)
+ agg['total_response_time'] += float(log.response_time or 0.0)
+
+ if 200 <= log.status_code < 300:
+ agg['success_count'] += 1
+ else:
+ agg['failed_count'] += 1
+
+ if log.timestamp:
+ if log.timestamp < agg['oldest_timestamp']:
+ agg['oldest_timestamp'] = log.timestamp
+ if log.timestamp > agg['newest_timestamp']:
+ agg['newest_timestamp'] = log.timestamp
+
+ agg['log_ids'].append(log.id)
+
+ # Create aggregated log entries
+ aggregated_count = 0
+ periods_created = []
+
+ for period_key, agg_data in aggregated_data.items():
+ # Calculate averages
+ count = agg_data['count']
+ avg_response_time = agg_data['total_response_time'] / count if count > 0 else 0.0
+
+ # Create aggregated log entry
+ aggregated_log = APIUsageLog(
+ user_id=user_id,
+ provider=agg_data['provider'],
+ endpoint='[AGGREGATED]',
+ method='AGGREGATED',
+ model_used=f"[{count} calls aggregated]",
+ tokens_input=agg_data['total_tokens_input'],
+ tokens_output=agg_data['total_tokens_output'],
+ tokens_total=agg_data['total_tokens'],
+ cost_input=agg_data['total_cost_input'],
+ cost_output=agg_data['total_cost_output'],
+ cost_total=agg_data['total_cost'],
+ response_time=avg_response_time,
+ status_code=200 if agg_data['success_count'] > agg_data['failed_count'] else 500,
+ error_message=f"Aggregated {count} calls: {agg_data['success_count']} success, {agg_data['failed_count']} failed",
+ retry_count=0,
+ timestamp=agg_data['oldest_timestamp'], # Use oldest timestamp
+ billing_period=agg_data['billing_period']
+ )
+
+ self.db.add(aggregated_log)
+ periods_created.append({
+ 'provider': agg_data['provider'].value,
+ 'billing_period': agg_data['billing_period'],
+ 'count': count,
+ 'period_start': agg_data['oldest_timestamp'].isoformat() if agg_data['oldest_timestamp'] else None,
+ 'period_end': agg_data['newest_timestamp'].isoformat() if agg_data['newest_timestamp'] else None
+ })
+
+ aggregated_count += count
+
+ # Delete individual logs that were aggregated
+ log_ids_to_delete = []
+ for agg_data in aggregated_data.values():
+ log_ids_to_delete.extend(agg_data['log_ids'])
+
+ if log_ids_to_delete:
+ self.db.query(APIUsageLog).filter(
+ APIUsageLog.id.in_(log_ids_to_delete)
+ ).delete(synchronize_session=False)
+
+ self.db.commit()
+
+ # Get remaining log count
+ remaining_count = self.db.query(func.count(APIUsageLog.id)).filter(
+ APIUsageLog.user_id == user_id
+ ).scalar() or 0
+
+ logger.info(
+ f"[LogWrapping] Wrapped {aggregated_count} logs into {len(periods_created)} aggregated records. "
+ f"Remaining logs: {remaining_count}"
+ )
+
+ return {
+ 'aggregated_count': aggregated_count,
+ 'logs_remaining': remaining_count,
+ 'periods': periods_created
+ }
+
+ except Exception as e:
+ self.db.rollback()
+ logger.error(f"[LogWrapping] Error wrapping logs: {e}", exc_info=True)
+ raise
+
diff --git a/backend/services/subscription/pricing_service.py b/backend/services/subscription/pricing_service.py
index a72912c5..bce611ad 100644
--- a/backend/services/subscription/pricing_service.py
+++ b/backend/services/subscription/pricing_service.py
@@ -9,6 +9,7 @@ from datetime import datetime, timedelta
from sqlalchemy.orm import Session
from sqlalchemy import text
from loguru import logger
+import os
from models.subscription_models import (
APIProviderPricing, SubscriptionPlan, UserSubscription,
@@ -227,6 +228,36 @@ class PricingService:
}
]
+ # HuggingFace/Mistral Pricing (for GPT-OSS-120B via Groq)
+ # Default pricing from environment variables or fallback to estimated values
+ # Based on Groq pricing: ~$1 per 1M input tokens, ~$3 per 1M output tokens
+ hf_input_cost = float(os.getenv('HUGGINGFACE_INPUT_TOKEN_COST', '0.000001')) # $1 per 1M tokens default
+ hf_output_cost = float(os.getenv('HUGGINGFACE_OUTPUT_TOKEN_COST', '0.000003')) # $3 per 1M tokens default
+
+ mistral_pricing = [
+ {
+ "provider": APIProvider.MISTRAL,
+ "model_name": "openai/gpt-oss-120b:groq",
+ "cost_per_input_token": hf_input_cost,
+ "cost_per_output_token": hf_output_cost,
+ "description": f"GPT-OSS-120B via HuggingFace/Groq (configurable via HUGGINGFACE_INPUT_TOKEN_COST and HUGGINGFACE_OUTPUT_TOKEN_COST env vars)"
+ },
+ {
+ "provider": APIProvider.MISTRAL,
+ "model_name": "gpt-oss-120b",
+ "cost_per_input_token": hf_input_cost,
+ "cost_per_output_token": hf_output_cost,
+ "description": f"GPT-OSS-120B via HuggingFace/Groq (configurable via HUGGINGFACE_INPUT_TOKEN_COST and HUGGINGFACE_OUTPUT_TOKEN_COST env vars)"
+ },
+ {
+ "provider": APIProvider.MISTRAL,
+ "model_name": "default",
+ "cost_per_input_token": hf_input_cost,
+ "cost_per_output_token": hf_output_cost,
+ "description": f"HuggingFace default model pricing (configurable via HUGGINGFACE_INPUT_TOKEN_COST and HUGGINGFACE_OUTPUT_TOKEN_COST env vars)"
+ }
+ ]
+
# Search API Pricing (estimated)
search_pricing = [
{
@@ -268,21 +299,31 @@ class PricingService:
]
# Combine all pricing data
- all_pricing = gemini_pricing + openai_pricing + anthropic_pricing + search_pricing
+ all_pricing = gemini_pricing + openai_pricing + anthropic_pricing + mistral_pricing + search_pricing
- # Insert pricing data
+ # Insert or update pricing data
for pricing_data in all_pricing:
existing = self.db.query(APIProviderPricing).filter(
APIProviderPricing.provider == pricing_data["provider"],
APIProviderPricing.model_name == pricing_data["model_name"]
).first()
- if not existing:
+ if existing:
+ # Update existing pricing (especially for HuggingFace if env vars changed)
+ if pricing_data["provider"] == APIProvider.MISTRAL:
+ # Update HuggingFace pricing from env vars
+ existing.cost_per_input_token = pricing_data["cost_per_input_token"]
+ existing.cost_per_output_token = pricing_data["cost_per_output_token"]
+ existing.description = pricing_data["description"]
+ existing.updated_at = datetime.utcnow()
+ logger.debug(f"Updated pricing for {pricing_data['provider'].value}:{pricing_data['model_name']}")
+ else:
pricing = APIProviderPricing(**pricing_data)
self.db.add(pricing)
+ logger.debug(f"Added new pricing for {pricing_data['provider'].value}:{pricing_data['model_name']}")
self.db.commit()
- logger.debug("Default API pricing initialized")
+ logger.info("Default API pricing initialized/updated. HuggingFace pricing loaded from env vars if available.")
def initialize_default_plans(self):
"""Initialize default subscription plans."""
@@ -395,31 +436,82 @@ class PricingService:
def calculate_api_cost(self, provider: APIProvider, model_name: str,
tokens_input: int = 0, tokens_output: int = 0,
request_count: int = 1, **kwargs) -> Dict[str, float]:
- """Calculate cost for an API call."""
+ """Calculate cost for an API call.
+
+ Args:
+ provider: APIProvider enum (e.g., APIProvider.MISTRAL for HuggingFace)
+ model_name: Model name (e.g., "openai/gpt-oss-120b:groq")
+ tokens_input: Number of input tokens
+ tokens_output: Number of output tokens
+ request_count: Number of requests (default: 1)
+ **kwargs: Additional parameters (search_count, image_count, page_count, etc.)
+
+ Returns:
+ Dict with cost_input, cost_output, and cost_total
+ """
# Get pricing for the provider and model
+ # Try exact match first
pricing = self.db.query(APIProviderPricing).filter(
APIProviderPricing.provider == provider,
APIProviderPricing.model_name == model_name,
APIProviderPricing.is_active == True
).first()
+ # If not found, try "default" model name for the provider
if not pricing:
- logger.warning(f"No pricing found for {provider.value}:{model_name}, using default estimates")
- # Use default estimates
- cost_input = tokens_input * 0.000001 # $1 per 1M tokens default
- cost_output = tokens_output * 0.000001
- cost_total = (cost_input + cost_output) * request_count
+ pricing = self.db.query(APIProviderPricing).filter(
+ APIProviderPricing.provider == provider,
+ APIProviderPricing.model_name == "default",
+ APIProviderPricing.is_active == True
+ ).first()
+
+ # If still not found, check for HuggingFace models (provider is MISTRAL)
+ # Try alternative model name variations
+ if not pricing and provider == APIProvider.MISTRAL:
+ # Try with "gpt-oss-120b" (without full path) if model contains it
+ if "gpt-oss-120b" in model_name.lower():
+ pricing = self.db.query(APIProviderPricing).filter(
+ APIProviderPricing.provider == provider,
+ APIProviderPricing.model_name == "gpt-oss-120b",
+ APIProviderPricing.is_active == True
+ ).first()
+
+ # Also try with full model path
+ if not pricing:
+ pricing = self.db.query(APIProviderPricing).filter(
+ APIProviderPricing.provider == provider,
+ APIProviderPricing.model_name == "openai/gpt-oss-120b:groq",
+ APIProviderPricing.is_active == True
+ ).first()
+
+ if not pricing:
+ # Check if we should use env vars for HuggingFace/Mistral
+ if provider == APIProvider.MISTRAL:
+ # Use environment variables for HuggingFace pricing if available
+ hf_input_cost = float(os.getenv('HUGGINGFACE_INPUT_TOKEN_COST', '0.000001'))
+ hf_output_cost = float(os.getenv('HUGGINGFACE_OUTPUT_TOKEN_COST', '0.000003'))
+ logger.info(f"Using HuggingFace pricing from env vars: input={hf_input_cost}, output={hf_output_cost} for model {model_name}")
+ cost_input = tokens_input * hf_input_cost
+ cost_output = tokens_output * hf_output_cost
+ cost_total = cost_input + cost_output
+ else:
+ logger.warning(f"No pricing found for {provider.value}:{model_name}, using default estimates")
+ # Use default estimates
+ cost_input = tokens_input * 0.000001 # $1 per 1M tokens default
+ cost_output = tokens_output * 0.000001
+ cost_total = cost_input + cost_output
else:
- # Calculate based on actual pricing
- cost_input = tokens_input * pricing.cost_per_input_token
- cost_output = tokens_output * pricing.cost_per_output_token
- cost_request = request_count * pricing.cost_per_request
+ # Calculate based on actual pricing from database
+ logger.debug(f"Using pricing from DB for {provider.value}:{model_name} - input: {pricing.cost_per_input_token}, output: {pricing.cost_per_output_token}")
+ cost_input = tokens_input * (pricing.cost_per_input_token or 0.0)
+ cost_output = tokens_output * (pricing.cost_per_output_token or 0.0)
+ cost_request = request_count * (pricing.cost_per_request or 0.0)
# Handle special cases for non-LLM APIs
- cost_search = kwargs.get('search_count', 0) * pricing.cost_per_search
- cost_image = kwargs.get('image_count', 0) * pricing.cost_per_image
- cost_page = kwargs.get('page_count', 0) * pricing.cost_per_page
+ cost_search = kwargs.get('search_count', 0) * (pricing.cost_per_search or 0.0)
+ cost_image = kwargs.get('image_count', 0) * (pricing.cost_per_image or 0.0)
+ cost_page = kwargs.get('page_count', 0) * (pricing.cost_per_page or 0.0)
cost_total = cost_input + cost_output + cost_request + cost_search + cost_image + cost_page
diff --git a/backend/services/subscription/usage_tracking_service.py b/backend/services/subscription/usage_tracking_service.py
index 94efd731..98d54e56 100644
--- a/backend/services/subscription/usage_tracking_service.py
+++ b/backend/services/subscription/usage_tracking_service.py
@@ -42,10 +42,19 @@ class UsageTrackingService:
default_models = {
"gemini": "gemini-2.5-flash", # Use Flash as default (cost-effective)
"openai": "gpt-4o-mini", # Use Mini as default (cost-effective)
- "anthropic": "claude-3.5-sonnet" # Use Sonnet as default
+ "anthropic": "claude-3.5-sonnet", # Use Sonnet as default
+ "mistral": "openai/gpt-oss-120b:groq" # HuggingFace default model
}
- model_name = model_used or default_models.get(provider.value, f"{provider.value}-default")
+ # For HuggingFace (stored as MISTRAL), use the actual model name or default
+ if provider == APIProvider.MISTRAL:
+ # HuggingFace models - try to match the actual model name from model_used
+ if model_used:
+ model_name = model_used
+ else:
+ model_name = default_models.get("mistral", "openai/gpt-oss-120b:groq")
+ else:
+ model_name = model_used or default_models.get(provider.value, f"{provider.value}-default")
cost_data = self.pricing_service.calculate_api_cost(
provider=provider,
@@ -344,46 +353,106 @@ class UsageTrackingService:
'limits': limits,
'provider_breakdown': provider_breakdown,
'alerts': [],
- 'usage_percentages': usage_percentages
+ 'usage_percentages': {}
}
- # Calculate usage percentages
+ # Provider breakdown - calculate costs first, then use for percentages
+ # Only include Gemini and HuggingFace (HuggingFace is stored under MISTRAL enum)
+ provider_breakdown = {}
+
+ # Gemini
+ gemini_calls = getattr(summary, "gemini_calls", 0) or 0
+ gemini_tokens = getattr(summary, "gemini_tokens", 0) or 0
+ gemini_cost = getattr(summary, "gemini_cost", 0.0) or 0.0
+
+ # If gemini cost is 0 but there are calls, calculate from usage logs
+ if gemini_calls > 0 and gemini_cost == 0.0:
+ gemini_logs = self.db.query(APIUsageLog).filter(
+ APIUsageLog.user_id == user_id,
+ APIUsageLog.provider == APIProvider.GEMINI,
+ APIUsageLog.billing_period == billing_period
+ ).all()
+ if gemini_logs:
+ gemini_cost = sum(float(log.cost_total or 0.0) for log in gemini_logs)
+ logger.info(f"[UsageStats] Calculated gemini cost from {len(gemini_logs)} logs: ${gemini_cost:.6f}")
+
+ provider_breakdown['gemini'] = {
+ 'calls': gemini_calls,
+ 'tokens': gemini_tokens,
+ 'cost': gemini_cost
+ }
+
+ # HuggingFace (stored as MISTRAL in database)
+ mistral_calls = getattr(summary, "mistral_calls", 0) or 0
+ mistral_tokens = getattr(summary, "mistral_tokens", 0) or 0
+ mistral_cost = getattr(summary, "mistral_cost", 0.0) or 0.0
+
+ # If mistral (HuggingFace) cost is 0 but there are calls, calculate from usage logs
+ if mistral_calls > 0 and mistral_cost == 0.0:
+ mistral_logs = self.db.query(APIUsageLog).filter(
+ APIUsageLog.user_id == user_id,
+ APIUsageLog.provider == APIProvider.MISTRAL,
+ APIUsageLog.billing_period == billing_period
+ ).all()
+ if mistral_logs:
+ mistral_cost = sum(float(log.cost_total or 0.0) for log in mistral_logs)
+ logger.info(f"[UsageStats] Calculated mistral (HuggingFace) cost from {len(mistral_logs)} logs: ${mistral_cost:.6f}")
+
+ provider_breakdown['huggingface'] = {
+ 'calls': mistral_calls,
+ 'tokens': mistral_tokens,
+ 'cost': mistral_cost
+ }
+
+ # Calculate total cost from provider breakdown if summary total_cost is 0
+ calculated_total_cost = gemini_cost + mistral_cost
+ summary_total_cost = summary.total_cost or 0.0
+ # Use calculated cost if summary cost is 0, otherwise use summary cost (it's more accurate)
+ final_total_cost = summary_total_cost if summary_total_cost > 0 else calculated_total_cost
+
+ # If we calculated costs from logs, update the summary for future requests
+ if calculated_total_cost > 0 and summary_total_cost == 0.0:
+ logger.info(f"[UsageStats] Updating summary costs: total_cost={final_total_cost:.6f}, gemini_cost={gemini_cost:.6f}, mistral_cost={mistral_cost:.6f}")
+ summary.total_cost = final_total_cost
+ summary.gemini_cost = gemini_cost
+ summary.mistral_cost = mistral_cost
+ try:
+ self.db.commit()
+ except Exception as e:
+ logger.error(f"[UsageStats] Error updating summary costs: {e}")
+ self.db.rollback()
+
+ # Calculate usage percentages - only for Gemini and HuggingFace
+ # Use the calculated costs for accurate percentages
usage_percentages = {}
if limits:
- for provider in APIProvider:
- provider_name = provider.value
- current_calls = getattr(summary, f"{provider_name}_calls", 0) or 0
- call_limit = limits['limits'].get(f"{provider_name}_calls", 0) or 0
-
- if call_limit > 0:
- usage_percentages[f"{provider_name}_calls"] = (current_calls / call_limit) * 100
- else:
- usage_percentages[f"{provider_name}_calls"] = 0
+ # Gemini
+ gemini_call_limit = limits['limits'].get("gemini_calls", 0) or 0
+ if gemini_call_limit > 0:
+ usage_percentages['gemini_calls'] = (gemini_calls / gemini_call_limit) * 100
+ else:
+ usage_percentages['gemini_calls'] = 0
- # Cost usage percentage
+ # HuggingFace (stored as mistral in database)
+ mistral_call_limit = limits['limits'].get("mistral_calls", 0) or 0
+ if mistral_call_limit > 0:
+ usage_percentages['mistral_calls'] = (mistral_calls / mistral_call_limit) * 100
+ else:
+ usage_percentages['mistral_calls'] = 0
+
+ # Cost usage percentage - use final_total_cost (calculated from logs if needed)
cost_limit = limits['limits'].get('monthly_cost', 0) or 0
- total_cost = summary.total_cost or 0
if cost_limit > 0:
- usage_percentages['cost'] = (total_cost / cost_limit) * 100
+ usage_percentages['cost'] = (final_total_cost / cost_limit) * 100
else:
usage_percentages['cost'] = 0
- # Provider breakdown
- provider_breakdown = {}
- for provider in APIProvider:
- provider_name = provider.value
- provider_breakdown[provider_name] = {
- 'calls': getattr(summary, f"{provider_name}_calls", 0) or 0,
- 'tokens': getattr(summary, f"{provider_name}_tokens", 0) or 0,
- 'cost': getattr(summary, f"{provider_name}_cost", 0.0) or 0.0
- }
-
return {
'billing_period': billing_period,
'usage_status': summary.usage_status.value if hasattr(summary.usage_status, 'value') else str(summary.usage_status),
'total_calls': summary.total_calls or 0,
'total_tokens': summary.total_tokens or 0,
- 'total_cost': summary.total_cost or 0.0,
+ 'total_cost': final_total_cost,
'avg_response_time': summary.avg_response_time or 0.0,
'error_rate': summary.error_rate or 0.0,
'limits': limits,
diff --git a/backend/services/wix_service.py b/backend/services/wix_service.py
index 29761455..855adb1e 100644
--- a/backend/services/wix_service.py
+++ b/backend/services/wix_service.py
@@ -77,7 +77,17 @@ class WixService:
# For now, return the direct OAuth URL as a fallback
# In production, this should call the Wix Redirects API
- redirect_url = f"https://www.wix.com/oauth/authorize?client_id={client_id}&redirect_uri={redirect_uri}&response_type=code&scope=BLOG.CREATE-DRAFT,BLOG.PUBLISH,MEDIA.MANAGE&code_challenge={code_challenge}&code_challenge_method=S256&state={state}"
+ scope = (
+ "BLOG.CREATE-DRAFT,BLOG.PUBLISH-POST,BLOG.READ-CATEGORY," \
+ "BLOG.CREATE-CATEGORY,BLOG.READ-TAG,BLOG.CREATE-TAG," \
+ "MEDIA.SITE_MEDIA_FILES_IMPORT"
+ )
+ redirect_url = (
+ "https://www.wix.com/oauth/authorize?client_id="
+ f"{client_id}&redirect_uri={redirect_uri}&response_type=code"
+ f"&scope={scope}&code_challenge={code_challenge}"
+ f"&code_challenge_method=S256&state={state}"
+ )
logger.info(f"Generated Wix Headless OAuth redirect URL: {redirect_url}")
logger.warning("Using direct OAuth URL - should implement Redirects API for production")
@@ -293,9 +303,20 @@ class WixService:
Returns:
Created blog post information
"""
+ # Normalize access token to string to avoid type issues (can be dict/int from storage)
+ from services.integrations.wix.utils import normalize_token_string
+ normalized_token = normalize_token_string(access_token)
+ if normalized_token:
+ token_to_use = normalized_token.strip()
+ else:
+ token_to_use = str(access_token).strip() if access_token is not None else ""
+
+ if not token_to_use:
+ raise ValueError("access_token is required to create a blog post")
+
return publish_blog_post(
blog_service=self.blog_service,
- access_token=access_token,
+ access_token=token_to_use,
title=title,
content=content,
member_id=member_id,
diff --git a/backend/story_images/scene_1_Welcome_to_the_Fluffy_Cloud_Ki_6818cab1.png b/backend/story_images/scene_1_Welcome_to_the_Fluffy_Cloud_Ki_6818cab1.png
new file mode 100644
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new file mode 100644
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new file mode 100644
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diff --git a/backend/story_images/scene_6_The_Birth_of_a_New_Star_d68c6f67.png b/backend/story_images/scene_6_The_Birth_of_a_New_Star_d68c6f67.png
new file mode 100644
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diff --git a/backend/story_images/scene_7_Celebration_and_Sweet_Goodbyes_3a3373a2.png b/backend/story_images/scene_7_Celebration_and_Sweet_Goodbyes_3a3373a2.png
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diff --git a/docs/Billing_Subscription/HUGGINGFACE_PRICING.md b/docs/Billing_Subscription/HUGGINGFACE_PRICING.md
new file mode 100644
index 00000000..67952af9
--- /dev/null
+++ b/docs/Billing_Subscription/HUGGINGFACE_PRICING.md
@@ -0,0 +1,103 @@
+# HuggingFace Pricing Configuration
+
+## Overview
+
+HuggingFace API calls (specifically for GPT-OSS-120B model via Groq) are tracked and billed using configurable pricing. The pricing can be set via environment variables in your `.env` file.
+
+## Environment Variables
+
+### `HUGGINGFACE_INPUT_TOKEN_COST`
+- **Description**: Cost per input token for HuggingFace API calls
+- **Format**: Float (decimal number)
+- **Default**: `0.000001` ($1 per 1M input tokens)
+- **Example**: `HUGGINGFACE_INPUT_TOKEN_COST=0.000001`
+
+### `HUGGINGFACE_OUTPUT_TOKEN_COST`
+- **Description**: Cost per output token for HuggingFace API calls
+- **Format**: Float (decimal number)
+- **Default**: `0.000003` ($3 per 1M output tokens)
+- **Example**: `HUGGINGFACE_OUTPUT_TOKEN_COST=0.000003`
+
+## Configuration
+
+### Step 1: Add to .env File
+
+Add the following lines to your `.env` file:
+
+```bash
+# HuggingFace Pricing (for GPT-OSS-120B via Groq)
+# Pricing is per token (e.g., 0.000001 = $1 per 1M tokens)
+HUGGINGFACE_INPUT_TOKEN_COST=0.000001
+HUGGINGFACE_OUTPUT_TOKEN_COST=0.000003
+```
+
+### Step 2: Initialize/Update Pricing
+
+The pricing is automatically initialized when the database is set up. To update pricing after changing environment variables:
+
+1. **Option 1**: Restart the backend server (pricing will be updated on next initialization)
+2. **Option 2**: Run the database setup script to update pricing:
+ ```bash
+ python backend/scripts/create_subscription_tables.py
+ ```
+
+### Step 3: Verify Pricing
+
+Check that pricing is correctly configured by:
+1. Checking the database `api_provider_pricing` table
+2. Making a test API call and checking the cost in usage logs
+3. Viewing the billing dashboard to see cost calculations
+
+## Pricing Calculation
+
+The cost calculation works as follows:
+
+1. **Database Lookup**: The system first tries to find pricing in the database for the specific model
+2. **Model Matching**: It tries multiple model name variations:
+ - Exact model name (e.g., "openai/gpt-oss-120b:groq")
+ - Short model name (e.g., "gpt-oss-120b")
+ - Default model name ("default")
+3. **Environment Variable Fallback**: If no pricing is found in the database, it uses environment variables for HuggingFace/Mistral provider
+4. **Default Estimates**: As a last resort, it uses default estimates ($1 per 1M tokens for both input and output)
+
+## Cost Calculation Formula
+
+```
+cost_input = tokens_input * HUGGINGFACE_INPUT_TOKEN_COST
+cost_output = tokens_output * HUGGINGFACE_OUTPUT_TOKEN_COST
+cost_total = cost_input + cost_output
+```
+
+## Example
+
+For a HuggingFace API call with:
+- Input tokens: 1000
+- Output tokens: 500
+- HUGGINGFACE_INPUT_TOKEN_COST: 0.000001 ($1 per 1M tokens)
+- HUGGINGFACE_OUTPUT_TOKEN_COST: 0.000003 ($3 per 1M tokens)
+
+Calculation:
+```
+cost_input = 1000 * 0.000001 = 0.001 ($0.001)
+cost_output = 500 * 0.000003 = 0.0015 ($0.0015)
+cost_total = 0.001 + 0.0015 = 0.0025 ($0.0025)
+```
+
+## Testing
+
+To test the pricing configuration:
+
+1. Set environment variables in `.env`
+2. Restart the backend server
+3. Make a HuggingFace API call
+4. Check the usage logs in the billing dashboard
+5. Verify the cost is calculated correctly
+
+## Notes
+
+- Pricing is stored in the `api_provider_pricing` table
+- Pricing is updated automatically when `initialize_default_pricing()` is called
+- Environment variables take precedence over database values if pricing is not found in DB
+- The pricing applies to all HuggingFace models that map to the MISTRAL provider enum
+- Default pricing is based on Groq's estimated pricing for GPT-OSS-120B model
+
diff --git a/docs/STORY_GENERATION_CODE_ADAPTATION_GUIDE.md b/docs/STORY_GENERATION_CODE_ADAPTATION_GUIDE.md
new file mode 100644
index 00000000..fc4c20cd
--- /dev/null
+++ b/docs/STORY_GENERATION_CODE_ADAPTATION_GUIDE.md
@@ -0,0 +1,499 @@
+# Story Generation Code Adaptation Guide
+
+This guide shows how to adapt the existing story generation code to use the production-ready `main_text_generation` and subscription system.
+
+## 1. Import Path Updates
+
+### Before (Legacy)
+```python
+from ...gpt_providers.text_generation.main_text_generation import llm_text_gen
+```
+
+### After (Production)
+```python
+from services.llm_providers.main_text_generation import llm_text_gen
+```
+
+## 2. Adding User ID and Subscription Support
+
+### Before
+```python
+def generate_with_retry(prompt, system_prompt=None):
+ try:
+ return llm_text_gen(prompt, system_prompt)
+ except Exception as e:
+ logger.error(f"Error generating content: {e}")
+ return ""
+```
+
+### After
+```python
+def generate_with_retry(prompt, system_prompt=None, user_id: str = None):
+ """
+ Generate content with retry handling and subscription support.
+
+ Args:
+ prompt: The prompt to generate content from
+ system_prompt: Custom system prompt (optional)
+ user_id: Clerk user ID (required for subscription checking)
+
+ Returns:
+ Generated content string
+
+ Raises:
+ RuntimeError: If user_id is missing or subscription limits exceeded
+ HTTPException: If subscription limit exceeded (429 status)
+ """
+ if not user_id:
+ raise RuntimeError("user_id is required for subscription checking")
+
+ try:
+ return llm_text_gen(
+ prompt=prompt,
+ system_prompt=system_prompt,
+ user_id=user_id
+ )
+ except HTTPException as e:
+ # Re-raise HTTPExceptions (e.g., 429 subscription limit)
+ raise
+ except Exception as e:
+ logger.error(f"Error generating content: {e}")
+ raise RuntimeError(f"Failed to generate content: {str(e)}") from e
+```
+
+## 3. Structured JSON Response for Outline
+
+### Before
+```python
+outline = generate_with_retry(outline_prompt.format(premise=premise))
+# Returns plain text, needs parsing
+```
+
+### After
+```python
+# Define JSON schema for structured outline
+outline_schema = {
+ "type": "object",
+ "properties": {
+ "outline": {
+ "type": "array",
+ "items": {
+ "type": "object",
+ "properties": {
+ "scene_number": {"type": "integer"},
+ "title": {"type": "string"},
+ "description": {"type": "string"},
+ "key_events": {"type": "array", "items": {"type": "string"}}
+ },
+ "required": ["scene_number", "title", "description"]
+ }
+ }
+ },
+ "required": ["outline"]
+}
+
+# Generate structured outline
+outline_response = llm_text_gen(
+ prompt=outline_prompt.format(premise=premise),
+ system_prompt=system_prompt,
+ json_struct=outline_schema,
+ user_id=user_id
+)
+
+# Parse JSON response
+import json
+outline_data = json.loads(outline_response)
+outline = outline_data.get("outline", [])
+```
+
+## 4. Complete Service Example
+
+### Story Service Structure
+```python
+# backend/services/story_writer/story_service.py
+
+from typing import Dict, Any, Optional, List
+from loguru import logger
+from services.llm_providers.main_text_generation import llm_text_gen
+import json
+
+class StoryWriterService:
+ """Service for generating stories using prompt chaining."""
+
+ def __init__(self):
+ self.guidelines = """\
+Writing Guidelines:
+
+Delve deeper. Lose yourself in the world you're building. Unleash vivid
+descriptions to paint the scenes in your reader's mind.
+Develop your characters — let their motivations, fears, and complexities unfold naturally.
+Weave in the threads of your outline, but don't feel constrained by it.
+Allow your story to surprise you as you write. Use rich imagery, sensory details, and
+evocative language to bring the setting, characters, and events to life.
+Introduce elements subtly that can blossom into complex subplots, relationships,
+or worldbuilding details later in the story.
+Keep things intriguing but not fully resolved.
+Avoid boxing the story into a corner too early.
+Plant the seeds of subplots or potential character arc shifts that can be expanded later.
+
+Remember, your main goal is to write as much as you can. If you get through
+the story too fast, that is bad. Expand, never summarize.
+"""
+
+ def generate_premise(
+ self,
+ persona: str,
+ story_setting: str,
+ character_input: str,
+ plot_elements: str,
+ user_id: str
+ ) -> str:
+ """Generate story premise."""
+ prompt = f"""\
+{persona}
+
+Write a single sentence premise for a {story_setting} story featuring {character_input}.
+The plot will revolve around: {plot_elements}
+"""
+
+ try:
+ premise = llm_text_gen(
+ prompt=prompt,
+ user_id=user_id
+ )
+ return premise.strip()
+ except Exception as e:
+ logger.error(f"Error generating premise: {e}")
+ raise RuntimeError(f"Failed to generate premise: {str(e)}") from e
+
+ def generate_outline(
+ self,
+ premise: str,
+ persona: str,
+ story_setting: str,
+ character_input: str,
+ plot_elements: str,
+ user_id: str
+ ) -> List[Dict[str, Any]]:
+ """Generate structured story outline."""
+ prompt = f"""\
+{persona}
+
+You have a gripping premise in mind:
+
+{premise}
+
+Write an outline for the plot of your story set in {story_setting} featuring {character_input}.
+The plot elements are: {plot_elements}
+"""
+
+ # Define JSON schema for structured response
+ json_schema = {
+ "type": "object",
+ "properties": {
+ "outline": {
+ "type": "array",
+ "items": {
+ "type": "object",
+ "properties": {
+ "scene_number": {"type": "integer"},
+ "title": {"type": "string"},
+ "description": {"type": "string"},
+ "key_events": {
+ "type": "array",
+ "items": {"type": "string"}
+ }
+ },
+ "required": ["scene_number", "title", "description"]
+ }
+ }
+ },
+ "required": ["outline"]
+ }
+
+ try:
+ response = llm_text_gen(
+ prompt=prompt,
+ json_struct=json_schema,
+ user_id=user_id
+ )
+
+ # Parse JSON response
+ outline_data = json.loads(response)
+ return outline_data.get("outline", [])
+ except json.JSONDecodeError as e:
+ logger.error(f"Failed to parse outline JSON: {e}")
+ # Fallback to text parsing if JSON fails
+ return self._parse_text_outline(response)
+ except Exception as e:
+ logger.error(f"Error generating outline: {e}")
+ raise RuntimeError(f"Failed to generate outline: {str(e)}") from e
+
+ def generate_story_start(
+ self,
+ premise: str,
+ outline: str,
+ persona: str,
+ story_setting: str,
+ character_input: str,
+ plot_elements: str,
+ writing_style: str,
+ story_tone: str,
+ narrative_pov: str,
+ audience_age_group: str,
+ content_rating: str,
+ ending_preference: str,
+ user_id: str
+ ) -> str:
+ """Generate the starting section of the story."""
+ # Format outline as text if it's a list
+ if isinstance(outline, list):
+ outline_text = "\n".join([
+ f"{item.get('scene_number', i+1)}. {item.get('title', '')}: {item.get('description', '')}"
+ for i, item in enumerate(outline)
+ ])
+ else:
+ outline_text = str(outline)
+
+ prompt = f"""\
+{persona}
+
+Write a story with the following details:
+
+**The Story Setting is:**
+{story_setting}
+
+**The Characters of the story are:**
+{character_input}
+
+**Plot Elements of the story:**
+{plot_elements}
+
+**Story Writing Style:**
+{writing_style}
+
+**The story Tone is:**
+{story_tone}
+
+**Write story from the Point of View of:**
+{narrative_pov}
+
+**Target Audience of the story:**
+{audience_age_group}, **Content Rating:** {content_rating}
+
+**Story Ending:**
+{ending_preference}
+
+You have a gripping premise in mind:
+
+{premise}
+
+Your imagination has crafted a rich narrative outline:
+
+{outline_text}
+
+First, silently review the outline and the premise. Consider how to start the story.
+
+Start to write the very beginning of the story. You are not expected to finish
+the whole story now. Your writing should be detailed enough that you are only
+scratching the surface of the first bullet of your outline. Try to write AT
+MINIMUM 4000 WORDS.
+
+{self.guidelines}
+"""
+
+ try:
+ starting_draft = llm_text_gen(
+ prompt=prompt,
+ user_id=user_id
+ )
+ return starting_draft.strip()
+ except Exception as e:
+ logger.error(f"Error generating story start: {e}")
+ raise RuntimeError(f"Failed to generate story start: {str(e)}") from e
+
+ def continue_story(
+ self,
+ premise: str,
+ outline: str,
+ story_text: str,
+ persona: str,
+ story_setting: str,
+ character_input: str,
+ plot_elements: str,
+ writing_style: str,
+ story_tone: str,
+ narrative_pov: str,
+ audience_age_group: str,
+ content_rating: str,
+ ending_preference: str,
+ user_id: str
+ ) -> str:
+ """Continue writing the story."""
+ # Format outline as text if it's a list
+ if isinstance(outline, list):
+ outline_text = "\n".join([
+ f"{item.get('scene_number', i+1)}. {item.get('title', '')}: {item.get('description', '')}"
+ for i, item in enumerate(outline)
+ ])
+ else:
+ outline_text = str(outline)
+
+ prompt = f"""\
+{persona}
+
+Write a story with the following details:
+
+**The Story Setting is:**
+{story_setting}
+
+**The Characters of the story are:**
+{character_input}
+
+**Plot Elements of the story:**
+{plot_elements}
+
+**Story Writing Style:**
+{writing_style}
+
+**The story Tone is:**
+{story_tone}
+
+**Write story from the Point of View of:**
+{narrative_pov}
+
+**Target Audience of the story:**
+{audience_age_group}, **Content Rating:** {content_rating}
+
+**Story Ending:**
+{ending_preference}
+
+You have a gripping premise in mind:
+
+{premise}
+
+Your imagination has crafted a rich narrative outline:
+
+{outline_text}
+
+You've begun to immerse yourself in this world, and the words are flowing.
+Here's what you've written so far:
+
+{story_text}
+
+=====
+
+First, silently review the outline and story so far. Identify what the single
+next part of your outline you should write.
+
+Your task is to continue where you left off and write the next part of the story.
+You are not expected to finish the whole story now. Your writing should be
+detailed enough that you are only scratching the surface of the next part of
+your outline. Try to write AT MINIMUM 2000 WORDS. However, only once the story
+is COMPLETELY finished, write IAMDONE. Remember, do NOT write a whole chapter
+right now.
+
+{self.guidelines}
+"""
+
+ try:
+ continuation = llm_text_gen(
+ prompt=prompt,
+ user_id=user_id
+ )
+ return continuation.strip()
+ except Exception as e:
+ logger.error(f"Error continuing story: {e}")
+ raise RuntimeError(f"Failed to continue story: {str(e)}") from e
+
+ def _parse_text_outline(self, text: str) -> List[Dict[str, Any]]:
+ """Fallback method to parse text outline if JSON parsing fails."""
+ # Simple text parsing logic
+ lines = text.strip().split('\n')
+ outline = []
+ for i, line in enumerate(lines):
+ if line.strip():
+ outline.append({
+ "scene_number": i + 1,
+ "title": f"Scene {i + 1}",
+ "description": line.strip(),
+ "key_events": []
+ })
+ return outline
+```
+
+## 5. API Endpoint Example
+
+```python
+# backend/api/story_writer/router.py
+
+from fastapi import APIRouter, HTTPException, Depends
+from typing import Dict, Any
+from middleware.auth_middleware import get_current_user
+from services.story_writer.story_service import StoryWriterService
+from models.story_models import StoryGenerationRequest
+
+router = APIRouter(prefix="/api/story", tags=["Story Writer"])
+service = StoryWriterService()
+
+@router.post("/generate-premise")
+async def generate_premise(
+ request: StoryGenerationRequest,
+ current_user: Dict[str, Any] = Depends(get_current_user)
+) -> Dict[str, Any]:
+ """Generate story premise."""
+ try:
+ if not current_user:
+ raise HTTPException(status_code=401, detail="Authentication required")
+
+ user_id = str(current_user.get('id', ''))
+ if not user_id:
+ raise HTTPException(status_code=401, detail="Invalid user ID")
+
+ premise = service.generate_premise(
+ persona=request.persona,
+ story_setting=request.story_setting,
+ character_input=request.character_input,
+ plot_elements=request.plot_elements,
+ user_id=user_id
+ )
+
+ return {"premise": premise, "success": True}
+ except HTTPException:
+ raise
+ except Exception as e:
+ logger.error(f"Failed to generate premise: {e}")
+ raise HTTPException(status_code=500, detail=str(e))
+```
+
+## 6. Key Differences Summary
+
+| Aspect | Legacy Code | Production Code |
+|--------|------------|-----------------|
+| Import Path | `...gpt_providers.text_generation.main_text_generation` | `services.llm_providers.main_text_generation` |
+| User ID | Not required | Required parameter |
+| Subscription | No checks | Automatic via `main_text_generation` |
+| Error Handling | Basic try/except | HTTPException handling for 429 errors |
+| Structured Responses | Text parsing | JSON schema support |
+| Async Support | Synchronous | Can use async/await |
+| Logging | Basic | Comprehensive with loguru |
+
+## 7. Testing Checklist
+
+When adapting code, verify:
+- [ ] All imports updated to production paths
+- [ ] `user_id` parameter added to all LLM calls
+- [ ] Subscription errors (429) are handled properly
+- [ ] Error messages are user-friendly
+- [ ] Logging is comprehensive
+- [ ] Structured JSON responses work correctly
+- [ ] Fallback logic for text parsing exists
+- [ ] Long-running operations use task management
+
+## 8. Common Pitfalls
+
+1. **Missing user_id**: Always pass `user_id` parameter
+2. **Ignoring HTTPException**: Re-raise HTTPExceptions (especially 429)
+3. **No fallback parsing**: If JSON parsing fails, have text parsing fallback
+4. **Synchronous blocking**: Use async endpoints for long-running operations
+5. **No error context**: Include original exception in error messages
diff --git a/docs/STORY_GENERATION_IMPLEMENTATION_PLAN.md b/docs/STORY_GENERATION_IMPLEMENTATION_PLAN.md
new file mode 100644
index 00000000..5b3ee97b
--- /dev/null
+++ b/docs/STORY_GENERATION_IMPLEMENTATION_PLAN.md
@@ -0,0 +1,537 @@
+# Story Generation Feature - Implementation Plan
+
+## Executive Summary
+
+This document reviews the existing story generation backend modules and provides a comprehensive plan to complete the story generation feature with a modern UI using CopilotKit, similar to the AI Blog Writer implementation.
+
+## 1. Current State Review
+
+### 1.1 Existing Backend Modules
+
+#### 1.1.1 Story Writer (`ToBeMigrated/ai_writers/ai_story_writer/`)
+**Status**: ✅ Functional but needs migration
+**Location**: `ToBeMigrated/ai_writers/ai_story_writer/ai_story_generator.py`
+
+**Features**:
+- Prompt chaining approach (premise → outline → starting draft → continuation)
+- Supports multiple personas/genres (11 predefined)
+- Configurable story parameters:
+ - Story setting
+ - Characters
+ - Plot elements
+ - Writing style (Formal, Casual, Poetic, Humorous)
+ - Story tone (Dark, Uplifting, Suspenseful, Whimsical)
+ - Narrative POV (First Person, Third Person Limited/Omniscient)
+ - Audience age group
+ - Content rating
+ - Ending preference
+
+**Current Implementation**:
+- Uses legacy `lib/gpt_providers/text_generation/main_text_generation.py` (needs update)
+- Streamlit-based UI (needs React migration)
+- Iterative generation until "IAMDONE" marker
+
+**Issues to Address**:
+1. ❌ Uses old import path (`...gpt_providers.text_generation.main_text_generation`)
+2. ❌ No subscription/user_id integration
+3. ❌ No task management/polling support
+4. ❌ Streamlit UI (needs React/CopilotKit migration)
+
+#### 1.1.2 Story Illustrator (`ToBeMigrated/ai_writers/ai_story_illustrator/`)
+**Status**: ✅ Functional but needs migration
+**Location**: `ToBeMigrated/ai_writers/ai_story_illustrator/story_illustrator.py`
+
+**Features**:
+- Story segmentation for illustration
+- Scene element extraction using LLM
+- Multiple illustration styles (12+ options)
+- PDF storybook generation
+- ZIP export of illustrations
+
+**Current Implementation**:
+- Uses legacy import paths
+- Streamlit UI
+- Integrates with image generation (Gemini)
+
+**Issues to Address**:
+1. ❌ Uses old import paths
+2. ❌ No subscription integration
+3. ❌ Streamlit UI (needs React migration)
+
+#### 1.1.3 Story Video Generator (`ToBeMigrated/ai_writers/ai_story_video_generator/`)
+**Status**: ✅ Functional but needs migration
+**Location**: `ToBeMigrated/ai_writers/ai_story_video_generator/story_video_generator.py`
+
+**Features**:
+- Story generation with scene breakdown
+- Image generation per scene
+- Text overlay on images
+- Video compilation with audio
+- Multiple story styles
+
+**Current Implementation**:
+- Uses legacy import paths
+- Streamlit UI
+- MoviePy for video generation
+
+**Issues to Address**:
+1. ❌ Uses old import paths
+2. ❌ No subscription integration
+3. ❌ Streamlit UI (needs React migration)
+4. ❌ Heavy dependencies (MoviePy, imageio)
+
+### 1.2 Core Infrastructure Available
+
+#### 1.2.1 Main Text Generation (`backend/services/llm_providers/main_text_generation.py`)
+**Status**: ✅ Production-ready
+**Features**:
+- ✅ Supports Gemini and HuggingFace
+- ✅ Subscription/user_id integration
+- ✅ Usage tracking
+- ✅ Automatic fallback between providers
+- ✅ Structured JSON response support
+
+**Usage Pattern**:
+```python
+from services.llm_providers.main_text_generation import llm_text_gen
+
+response = llm_text_gen(
+ prompt="...",
+ system_prompt="...",
+ json_struct={...}, # Optional
+ user_id="clerk_user_id" # Required
+)
+```
+
+#### 1.2.2 Subscription System (`backend/models/subscription_models.py`)
+**Status**: ✅ Production-ready
+**Features**:
+- Usage tracking per provider
+- Token limits
+- Call limits
+- Billing period management
+- Already integrated with `main_text_generation`
+
+#### 1.2.3 Blog Writer Architecture (Reference)
+**Status**: ✅ Production-ready reference implementation
+
+**Key Components**:
+1. **Phase Navigation** (`frontend/src/hooks/usePhaseNavigation.ts`)
+ - Multi-phase workflow (Research → Outline → Content → SEO → Publish)
+ - Phase state management
+ - Auto-progression logic
+
+2. **CopilotKit Integration** (`frontend/src/components/BlogWriter/BlogWriterUtils/useBlogWriterCopilotActions.ts`)
+ - Action handlers for AI interactions
+ - Sidebar suggestions
+ - Context-aware actions
+
+3. **Backend Router** (`backend/api/blog_writer/router.py`)
+ - RESTful endpoints
+ - Task management with polling
+ - Cache management
+ - Error handling
+
+4. **Task Management** (`backend/api/blog_writer/task_manager.py`)
+ - Async task execution
+ - Status tracking
+ - Result caching
+
+## 2. Implementation Plan
+
+### 2.1 Phase 1: Backend Migration & Enhancement
+
+#### 2.1.1 Create Story Writer Service
+**File**: `backend/services/story_writer/story_service.py`
+
+**Tasks**:
+1. Migrate `ai_story_generator.py` logic to new service
+2. Update imports to use `main_text_generation`
+3. Add `user_id` parameter to all LLM calls
+4. Implement prompt chaining with proper error handling
+5. Add structured JSON response support for outline generation
+6. Support both Gemini and HuggingFace through `main_text_generation`
+
+**Key Functions**:
+```python
+async def generate_story_premise(
+ persona: str,
+ story_setting: str,
+ character_input: str,
+ plot_elements: str,
+ writing_style: str,
+ story_tone: str,
+ narrative_pov: str,
+ audience_age_group: str,
+ content_rating: str,
+ ending_preference: str,
+ user_id: str
+) -> str
+
+async def generate_story_outline(
+ premise: str,
+ persona: str,
+ story_setting: str,
+ character_input: str,
+ plot_elements: str,
+ user_id: str
+) -> Dict[str, Any] # Structured outline
+
+async def generate_story_start(
+ premise: str,
+ outline: str,
+ persona: str,
+ guidelines: str,
+ user_id: str
+) -> str
+
+async def continue_story(
+ premise: str,
+ outline: str,
+ story_text: str,
+ persona: str,
+ guidelines: str,
+ user_id: str
+) -> str
+```
+
+#### 2.1.2 Create Story Writer Router
+**File**: `backend/api/story_writer/router.py`
+
+**Endpoints**:
+```
+POST /api/story/generate-premise
+POST /api/story/generate-outline
+POST /api/story/generate-start
+POST /api/story/continue
+POST /api/story/generate-full # Complete story generation with task management
+GET /api/story/task/{task_id}/status
+GET /api/story/task/{task_id}/result
+```
+
+**Request Models**:
+```python
+class StoryGenerationRequest(BaseModel):
+ persona: str
+ story_setting: str
+ character_input: str
+ plot_elements: str
+ writing_style: str
+ story_tone: str
+ narrative_pov: str
+ audience_age_group: str
+ content_rating: str
+ ending_preference: str
+```
+
+#### 2.1.3 Task Management Integration
+**File**: `backend/api/story_writer/task_manager.py`
+
+**Features**:
+- Async story generation with polling
+- Progress tracking (premise → outline → start → continuation → done)
+- Result caching
+- Error recovery
+
+### 2.2 Phase 2: Frontend Implementation
+
+#### 2.2.1 Story Writer Component Structure
+**File**: `frontend/src/components/StoryWriter/StoryWriter.tsx`
+
+**Phases** (similar to Blog Writer):
+1. **Setup** - Story parameters input
+2. **Premise** - Review and refine premise
+3. **Outline** - Review and refine outline
+4. **Writing** - Generate and edit story content
+5. **Illustration** (Optional) - Generate illustrations
+6. **Export** - Download/export story
+
+#### 2.2.2 Phase Navigation Hook
+**File**: `frontend/src/hooks/useStoryWriterPhaseNavigation.ts`
+
+**Based on**: `usePhaseNavigation.ts` from Blog Writer
+
+**Phases**:
+```typescript
+interface StoryPhase {
+ id: 'setup' | 'premise' | 'outline' | 'writing' | 'illustration' | 'export';
+ name: string;
+ icon: string;
+ description: string;
+ completed: boolean;
+ current: boolean;
+ disabled: boolean;
+}
+```
+
+#### 2.2.3 CopilotKit Actions
+**File**: `frontend/src/components/StoryWriter/StoryWriterUtils/useStoryWriterCopilotActions.ts`
+
+**Actions**:
+- `generateStoryPremise` - Generate story premise
+- `generateStoryOutline` - Generate outline from premise
+- `startStoryWriting` - Begin story generation
+- `continueStoryWriting` - Continue story generation
+- `refineStoryOutline` - Refine outline based on feedback
+- `generateIllustrations` - Generate illustrations for story
+- `exportStory` - Export story in various formats
+
+#### 2.2.4 Story Writer UI Components
+
+**Main Components**:
+1. `StoryWriter.tsx` - Main container
+2. `StorySetup.tsx` - Phase 1: Input story parameters
+3. `StoryPremise.tsx` - Phase 2: Review premise
+4. `StoryOutline.tsx` - Phase 3: Review/edit outline
+5. `StoryContent.tsx` - Phase 4: Generated story content with editor
+6. `StoryIllustration.tsx` - Phase 5: Illustration generation (optional)
+7. `StoryExport.tsx` - Phase 6: Export options
+
+**Utility Components**:
+- `StoryWriterUtils/HeaderBar.tsx` - Phase navigation header
+- `StoryWriterUtils/PhaseContent.tsx` - Phase-specific content wrapper
+- `StoryWriterUtils/WriterCopilotSidebar.tsx` - CopilotKit sidebar
+- `StoryWriterUtils/useStoryWriterState.ts` - State management hook
+
+### 2.3 Phase 3: Integration with Gemini Examples
+
+#### 2.3.1 Prompt Chaining Pattern
+**Reference**: https://colab.research.google.com/github/google-gemini/cookbook/blob/main/examples/Story_Writing_with_Prompt_Chaining.ipynb
+
+**Implementation**:
+- Use the existing prompt chaining approach from `ai_story_generator.py`
+- Enhance with structured JSON responses for outline
+- Add better error handling and retry logic
+- Support streaming responses (future enhancement)
+
+#### 2.3.2 Illustration Integration
+**Reference**: https://github.com/google-gemini/cookbook/blob/main/examples/Book_illustration.ipynb
+
+**Implementation**:
+- Migrate `story_illustrator.py` to backend service
+- Create API endpoints for illustration generation
+- Add illustration phase to frontend
+- Support multiple illustration styles
+
+#### 2.3.3 Video Generation (Optional/Future)
+**Reference**: https://github.com/google-gemini/cookbook/blob/main/examples/Animated_Story_Video_Generation_gemini.ipynb
+
+**Status**: Defer to Phase 4 (requires heavy dependencies)
+
+### 2.4 Phase 4: Advanced Features (Future)
+
+1. **Story Video Generation**
+ - Migrate `story_video_generator.py`
+ - Add video generation phase
+ - Handle MoviePy dependencies
+
+2. **Story Templates**
+ - Pre-defined story templates
+ - Genre-specific templates
+ - Character templates
+
+3. **Collaborative Editing**
+ - Multi-user story editing
+ - Version control
+ - Comments and suggestions
+
+4. **Story Analytics**
+ - Readability metrics
+ - Story structure analysis
+ - Character development tracking
+
+## 3. Technical Specifications
+
+### 3.1 Backend API Models
+
+```python
+# backend/models/story_models.py
+
+class StoryGenerationRequest(BaseModel):
+ persona: str
+ story_setting: str
+ character_input: str
+ plot_elements: str
+ writing_style: str
+ story_tone: str
+ narrative_pov: str
+ audience_age_group: str
+ content_rating: str
+ ending_preference: str
+
+class StoryPremiseResponse(BaseModel):
+ premise: str
+ task_id: Optional[str] = None
+
+class StoryOutlineResponse(BaseModel):
+ outline: List[Dict[str, Any]]
+ task_id: Optional[str] = None
+
+class StoryContentResponse(BaseModel):
+ content: str
+ is_complete: bool
+ task_id: Optional[str] = None
+
+class StoryIllustrationRequest(BaseModel):
+ story_text: str
+ style: str = "digital art"
+ aspect_ratio: str = "16:9"
+ num_segments: int = 5
+
+class StoryIllustrationResponse(BaseModel):
+ illustrations: List[str] # URLs or base64
+ segments: List[str]
+```
+
+### 3.2 Frontend API Service
+
+```typescript
+// frontend/src/services/storyWriterApi.ts
+
+export interface StoryGenerationRequest {
+ persona: string;
+ story_setting: string;
+ character_input: string;
+ plot_elements: string;
+ writing_style: string;
+ story_tone: string;
+ narrative_pov: string;
+ audience_age_group: string;
+ content_rating: string;
+ ending_preference: string;
+}
+
+export interface StoryPremiseResponse {
+ premise: string;
+ task_id?: string;
+}
+
+export interface StoryOutlineResponse {
+ outline: Array<{
+ scene_number: number;
+ description: string;
+ narration?: string;
+ }>;
+ task_id?: string;
+}
+
+export const storyWriterApi = {
+ generatePremise: (request: StoryGenerationRequest) => Promise,
+ generateOutline: (premise: string, request: StoryGenerationRequest) => Promise,
+ generateFullStory: (request: StoryGenerationRequest) => Promise<{ task_id: string }>,
+ getTaskStatus: (task_id: string) => Promise,
+ getTaskResult: (task_id: string) => Promise,
+ // ... more endpoints
+};
+```
+
+### 3.3 State Management
+
+```typescript
+// frontend/src/hooks/useStoryWriterState.ts
+
+interface StoryWriterState {
+ // Setup phase
+ persona: string;
+ storySetting: string;
+ characters: string;
+ plotElements: string;
+ writingStyle: string;
+ storyTone: string;
+ narrativePOV: string;
+ audienceAgeGroup: string;
+ contentRating: string;
+ endingPreference: string;
+
+ // Generation phases
+ premise: string | null;
+ outline: StoryOutlineSection[] | null;
+ storyContent: string | null;
+ isComplete: boolean;
+
+ // Illustration (optional)
+ illustrations: string[];
+
+ // Task management
+ currentTaskId: string | null;
+ generationProgress: number;
+}
+```
+
+## 4. Migration Checklist
+
+### Backend
+- [ ] Create `backend/services/story_writer/story_service.py`
+- [ ] Migrate prompt chaining logic from `ai_story_generator.py`
+- [ ] Update all imports to use `main_text_generation`
+- [ ] Add `user_id` parameter to all LLM calls
+- [ ] Create `backend/api/story_writer/router.py`
+- [ ] Create `backend/models/story_models.py`
+- [ ] Integrate task management (`backend/api/story_writer/task_manager.py`)
+- [ ] Add caching support
+- [ ] Create `backend/api/story_writer/illustration_service.py` (optional)
+- [ ] Register router in `app.py`
+
+### Frontend
+- [ ] Create `frontend/src/components/StoryWriter/` directory structure
+- [ ] Create `StoryWriter.tsx` main component
+- [ ] Create `useStoryWriterPhaseNavigation.ts` hook
+- [ ] Create `useStoryWriterState.ts` hook
+- [ ] Create `useStoryWriterCopilotActions.ts` hook
+- [ ] Create phase components (Setup, Premise, Outline, Writing, Illustration, Export)
+- [ ] Create `frontend/src/services/storyWriterApi.ts`
+- [ ] Add Story Writer route to App.tsx
+- [ ] Style components to match Blog Writer design
+- [ ] Add error handling and loading states
+- [ ] Implement polling for async tasks
+
+### Testing
+- [ ] Unit tests for story service
+- [ ] Integration tests for API endpoints
+- [ ] E2E tests for complete story generation flow
+- [ ] Test with both Gemini and HuggingFace providers
+- [ ] Test subscription limits and error handling
+
+## 5. Dependencies
+
+### Backend
+- ✅ `main_text_generation` (already available)
+- ✅ `subscription_models` (already available)
+- ✅ FastAPI (already available)
+- ⚠️ Image generation (for illustrations - needs verification)
+
+### Frontend
+- ✅ CopilotKit (already available)
+- ✅ React (already available)
+- ✅ TypeScript (already available)
+- ⚠️ Markdown editor (for story content editing - check if available)
+
+## 6. Timeline Estimate
+
+- **Phase 1 (Backend)**: 3-5 days
+- **Phase 2 (Frontend Core)**: 5-7 days
+- **Phase 3 (CopilotKit Integration)**: 2-3 days
+- **Phase 4 (Illustration - Optional)**: 3-4 days
+- **Testing & Polish**: 2-3 days
+
+**Total**: ~15-22 days for core features + illustrations
+
+## 7. Key Decisions
+
+1. **Provider Support**: Use `main_text_generation` which supports both Gemini and HuggingFace automatically
+2. **UI Pattern**: Follow Blog Writer pattern with phase navigation and CopilotKit integration
+3. **Task Management**: Use async task pattern with polling (same as Blog Writer)
+4. **Illustration**: Make optional/separate phase to keep core story generation focused
+5. **Video Generation**: Defer to future phase due to heavy dependencies
+
+## 8. Next Steps
+
+1. Review and approve this plan
+2. Set up backend service structure
+3. Begin backend migration
+4. Create frontend component structure
+5. Implement phase navigation
+6. Integrate CopilotKit actions
+7. Test end-to-end flow
+8. Add illustration support (optional)
+9. Polish and documentation
diff --git a/docs/STORY_GENERATION_READINESS_ASSESSMENT.md b/docs/STORY_GENERATION_READINESS_ASSESSMENT.md
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+# Story Generation Feature - Readiness Assessment
+
+## Summary
+
+This document provides a quick assessment of existing story generation modules and their readiness for integration into the main application.
+
+## Existing Modules Status
+
+### ✅ Ready for Migration (High Priority)
+
+#### 1. Story Writer Core (`ai_story_generator.py`)
+**Readiness**: 85%
+- ✅ Core logic is sound and follows prompt chaining pattern
+- ✅ Well-structured with clear separation of concerns
+- ✅ Supports comprehensive story parameters
+- ❌ Needs import path updates
+- ❌ Needs subscription integration
+- ❌ Needs user_id parameter addition
+
+**Migration Effort**: Low-Medium (2-3 days)
+
+#### 2. Story Illustrator (`story_illustrator.py`)
+**Readiness**: 80%
+- ✅ Complete illustration workflow
+- ✅ Multiple style support
+- ✅ PDF and ZIP export functionality
+- ❌ Needs import path updates
+- ❌ Needs subscription integration
+- ❌ Image generation API needs verification
+
+**Migration Effort**: Medium (3-4 days)
+
+### ⚠️ Functional but Complex (Medium Priority)
+
+#### 3. Story Video Generator (`story_video_generator.py`)
+**Readiness**: 70%
+- ✅ Complete video generation workflow
+- ✅ Image generation and text overlay
+- ✅ Video compilation with audio
+- ❌ Heavy dependencies (MoviePy, imageio, ffmpeg)
+- ❌ Complex error handling needed
+- ❌ Resource-intensive operations
+
+**Migration Effort**: High (5-7 days)
+**Recommendation**: Defer to Phase 2, focus on core story generation first
+
+## Infrastructure Readiness
+
+### ✅ Production-Ready Infrastructure
+
+#### 1. Main Text Generation (`main_text_generation.py`)
+**Status**: ✅ Ready
+- ✅ Supports Gemini and HuggingFace
+- ✅ Subscription integration built-in
+- ✅ Usage tracking
+- ✅ Error handling and fallback
+- ✅ Structured JSON response support
+
+**Integration**: Direct - just import and use
+
+#### 2. Subscription System (`subscription_models.py`)
+**Status**: ✅ Ready
+- ✅ Complete usage tracking
+- ✅ Token and call limits
+- ✅ Billing period management
+- ✅ Already integrated with main_text_generation
+
+**Integration**: Automatic - already working
+
+#### 3. Blog Writer Reference Implementation
+**Status**: ✅ Excellent Reference
+- ✅ Phase navigation pattern
+- ✅ CopilotKit integration
+- ✅ Task management with polling
+- ✅ State management hooks
+- ✅ Error handling patterns
+
+**Integration**: Follow same patterns
+
+## Key Findings
+
+### Strengths
+1. **Core Logic is Sound**: The prompt chaining approach in `ai_story_generator.py` is well-designed and follows the Gemini cookbook examples
+2. **Comprehensive Parameters**: Story writer supports extensive customization (11 personas, multiple styles, tones, POVs, etc.)
+3. **Infrastructure Ready**: All required backend infrastructure (LLM providers, subscription, task management) is already in place
+4. **Reference Implementation**: Blog Writer provides excellent patterns to follow
+
+### Gaps
+1. **Import Paths**: All story modules use legacy import paths that need updating
+2. **Subscription Integration**: No user_id or subscription checks in story modules
+3. **UI Framework**: All modules use Streamlit - need React/CopilotKit migration
+4. **Task Management**: No async task management - need polling support
+5. **Error Handling**: Basic error handling - needs enhancement for production
+
+### Opportunities
+1. **Structured Responses**: Can enhance outline generation with structured JSON (already supported by main_text_generation)
+2. **Streaming Support**: Future enhancement for real-time story generation
+3. **Illustration Integration**: Can be optional phase - doesn't block core story generation
+4. **Template System**: Can add pre-defined story templates based on personas
+
+## Recommended Approach
+
+### Phase 1: Core Story Generation (Priority 1)
+**Focus**: Get basic story generation working end-to-end
+- Migrate `ai_story_generator.py` to backend service
+- Create API endpoints with task management
+- Build React UI with phase navigation
+- Integrate CopilotKit actions
+- **Timeline**: 1-2 weeks
+
+### Phase 2: Illustration Support (Priority 2)
+**Focus**: Add optional illustration phase
+- Migrate `story_illustrator.py` to backend service
+- Add illustration phase to frontend
+- Integrate with image generation API
+- **Timeline**: 1 week
+
+### Phase 3: Video Generation (Priority 3)
+**Focus**: Advanced feature for future
+- Migrate `story_video_generator.py`
+- Handle heavy dependencies
+- Add video generation phase
+- **Timeline**: 2 weeks (defer to later)
+
+## Migration Complexity Matrix
+
+| Module | Complexity | Dependencies | Effort | Priority |
+|--------|-----------|--------------|--------|----------|
+| Story Writer Core | Low-Medium | Low | 2-3 days | P0 |
+| Story Illustrator | Medium | Medium | 3-4 days | P1 |
+| Story Video Generator | High | High | 5-7 days | P2 |
+
+## Risk Assessment
+
+### Low Risk ✅
+- Story writer core migration (well-understood patterns)
+- Integration with main_text_generation (already tested)
+- Phase navigation UI (proven pattern from Blog Writer)
+
+### Medium Risk ⚠️
+- Illustration integration (depends on image generation API availability)
+- Long-running story generation tasks (need proper timeout handling)
+- Subscription limit handling during long generations
+
+### High Risk ❌
+- Video generation (heavy dependencies, resource-intensive)
+- Real-time streaming (not currently supported by main_text_generation)
+
+## Conclusion
+
+The story generation feature is **highly feasible** with existing infrastructure. The core story writer module is well-designed and can be migrated relatively quickly. The main work is:
+
+1. **Backend Migration** (Low-Medium effort): Update imports, add subscription integration
+2. **Frontend Development** (Medium effort): Build React UI following Blog Writer patterns
+3. **CopilotKit Integration** (Low effort): Follow existing patterns
+
+**Recommended Start**: Begin with core story generation (Phase 1), then add illustrations (Phase 2), and defer video generation (Phase 3) to a later release.
diff --git a/docs/STORY_WRITER_BACKEND_MIGRATION_COMPLETE.md b/docs/STORY_WRITER_BACKEND_MIGRATION_COMPLETE.md
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+# Story Writer Backend Migration - Complete ✅
+
+## Summary
+
+Successfully migrated story generation code from `ToBeMigrated/ai_writers/ai_story_writer/` to production backend structure with minimal rewriting. All code has been adapted to use `main_text_generation` and subscription system.
+
+## What Was Created
+
+### 1. Service Layer (`backend/services/story_writer/`)
+- ✅ `story_service.py` - Core story generation logic
+ - Migrated from `ai_story_generator.py`
+ - Updated imports to use `main_text_generation`
+ - Added `user_id` parameter for subscription support
+ - Removed Streamlit dependencies
+ - Modular methods: `generate_premise`, `generate_outline`, `generate_story_start`, `continue_story`, `generate_full_story`
+
+### 2. API Layer (`backend/api/story_writer/`)
+- ✅ `router.py` - RESTful API endpoints
+ - Synchronous endpoints for premise, outline, start, continue
+ - Asynchronous endpoint for full story generation with task management
+ - Task status and result endpoints
+ - Cache management endpoints
+- ✅ `task_manager.py` - Async task execution and tracking
+ - Background task execution
+ - Progress tracking
+ - Status management
+- ✅ `cache_manager.py` - Result caching
+ - Cache key generation
+ - Cache statistics
+ - Cache clearing
+
+### 3. Models (`backend/models/story_models.py`)
+- ✅ Pydantic models for all requests and responses
+- ✅ Type-safe API contracts
+
+### 4. Router Registration
+- ✅ Added to `alwrity_utils/router_manager.py` in optional routers section
+- ✅ Automatic registration on app startup
+
+## Key Changes Made
+
+### Import Updates
+```python
+# Before (Legacy)
+from ...gpt_providers.text_generation.main_text_generation import llm_text_gen
+
+# After (Production)
+from services.llm_providers.main_text_generation import llm_text_gen
+```
+
+### Subscription Integration
+```python
+# Before
+def generate_with_retry(prompt, system_prompt=None):
+ return llm_text_gen(prompt, system_prompt)
+
+# After
+def generate_with_retry(prompt, system_prompt=None, user_id: str = None):
+ if not user_id:
+ raise RuntimeError("user_id is required")
+ return llm_text_gen(prompt=prompt, system_prompt=system_prompt, user_id=user_id)
+```
+
+### Error Handling
+- Added HTTPException handling for subscription limits (429)
+- Proper error propagation
+- Comprehensive logging
+
+### Removed Dependencies
+- Removed Streamlit (`st.info`, `st.error`, etc.)
+- Removed UI-specific code
+- Kept core business logic intact
+
+## API Endpoints Available
+
+### Story Generation
+- `POST /api/story/generate-premise` - Generate premise
+- `POST /api/story/generate-outline` - Generate outline
+- `POST /api/story/generate-start` - Generate story start
+- `POST /api/story/continue` - Continue story
+- `POST /api/story/generate-full` - Full story (async)
+
+### Task Management
+- `GET /api/story/task/{task_id}/status` - Task status
+- `GET /api/story/task/{task_id}/result` - Task result
+
+### Cache
+- `GET /api/story/cache/stats` - Cache statistics
+- `POST /api/story/cache/clear` - Clear cache
+
+## Project Structure
+
+```
+backend/
+├── services/
+│ └── story_writer/
+│ ├── __init__.py
+│ ├── story_service.py ✅ Core logic (migrated)
+│ └── README.md
+├── api/
+│ └── story_writer/
+│ ├── __init__.py
+│ ├── router.py ✅ API endpoints
+│ ├── task_manager.py ✅ Async tasks
+│ └── cache_manager.py ✅ Caching
+├── models/
+│ └── story_models.py ✅ Pydantic models
+└── alwrity_utils/
+ └── router_manager.py ✅ Router registration
+```
+
+## Testing Checklist
+
+- [ ] Test premise generation endpoint
+- [ ] Test outline generation endpoint
+- [ ] Test story start generation endpoint
+- [ ] Test story continuation endpoint
+- [ ] Test full story generation (async)
+- [ ] Test task status polling
+- [ ] Test subscription limits (429 errors)
+- [ ] Test with both Gemini and HuggingFace providers
+- [ ] Test cache functionality
+- [ ] Verify error handling
+
+## Next Steps
+
+1. **Frontend Implementation** - Build React UI with CopilotKit integration
+2. **Testing** - Add unit and integration tests
+3. **Documentation** - API documentation and usage examples
+4. **Illustration Support** - Migrate story illustrator (Phase 2)
+
+## Notes
+
+- All existing logic preserved - only imports and subscription integration changed
+- No breaking changes to story generation algorithm
+- Follows same patterns as Blog Writer for consistency
+- Ready for frontend integration
diff --git a/docs/STORY_WRITER_FRONTEND_FOUNDATION_COMPLETE.md b/docs/STORY_WRITER_FRONTEND_FOUNDATION_COMPLETE.md
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+# Story Writer Frontend Foundation - Phase 2 Complete
+
+## Overview
+Phase 2: Frontend Foundation has been completed. The frontend is now ready for end-to-end testing with the backend.
+
+## What Was Created
+
+### 1. API Service Layer (`frontend/src/services/storyWriterApi.ts`)
+- Complete TypeScript API service for all story generation endpoints
+- Methods for:
+ - `generatePremise()` - Generate story premise
+ - `generateOutline()` - Generate story outline from premise
+ - `generateStoryStart()` - Generate starting section of story
+ - `continueStory()` - Continue writing a story
+ - `generateFullStory()` - Generate complete story asynchronously
+ - `getTaskStatus()` - Get task status for async operations
+ - `getTaskResult()` - Get result of completed task
+ - `getCacheStats()` - Get cache statistics
+ - `clearCache()` - Clear story generation cache
+
+### 2. State Management Hook (`frontend/src/hooks/useStoryWriterState.ts`)
+- Comprehensive state management for story writer
+- Manages:
+ - Story parameters (persona, setting, characters, plot, style, tone, POV, audience, rating, ending)
+ - Generated content (premise, outline, story content)
+ - Task management (task ID, progress, messages)
+ - UI state (loading, errors)
+- Persists state to localStorage
+- Provides helper methods and setters
+
+### 3. Phase Navigation Hook (`frontend/src/hooks/useStoryWriterPhaseNavigation.ts`)
+- Manages phase navigation logic
+- Five phases: Setup → Premise → Outline → Writing → Export
+- Auto-progression based on completion status
+- Manual phase selection support
+- Phase state management (completed, current, disabled)
+- Persists current phase to localStorage
+
+### 4. Main Component (`frontend/src/components/StoryWriter/StoryWriter.tsx`)
+- Main StoryWriter component
+- Integrates state management and phase navigation
+- Renders appropriate phase component based on current phase
+- Clean, modern UI with Material-UI
+
+### 5. Phase Navigation Component (`frontend/src/components/StoryWriter/PhaseNavigation.tsx`)
+- Visual phase stepper using Material-UI Stepper
+- Shows phase icons, names, and descriptions
+- Clickable phases (when not disabled)
+- Visual indicators for current, completed, and disabled phases
+
+### 6. Phase Components
+
+#### StorySetup (`frontend/src/components/StoryWriter/Phases/StorySetup.tsx`)
+- Form for configuring story parameters
+- All required fields: Persona, Setting, Characters, Plot Elements
+- Optional fields: Writing Style, Tone, POV, Audience, Rating, Ending
+- Validates required fields before generation
+- Calls `generatePremise()` API
+- Auto-navigates to Premise phase on success
+
+#### StoryPremise (`frontend/src/components/StoryWriter/Phases/StoryPremise.tsx`)
+- Displays and allows editing of generated premise
+- Regenerate premise functionality
+- Continue to Outline button
+
+#### StoryOutline (`frontend/src/components/StoryWriter/Phases/StoryOutline.tsx`)
+- Generates outline from premise
+- Displays and allows editing of outline
+- Regenerate outline functionality
+- Continue to Writing button
+
+#### StoryWriting (`frontend/src/components/StoryWriter/Phases/StoryWriting.tsx`)
+- Generates starting section of story
+- Continue writing functionality (iterative)
+- Displays complete story content
+- Shows completion status
+- Continue to Export button
+
+#### StoryExport (`frontend/src/components/StoryWriter/Phases/StoryExport.tsx`)
+- Displays complete story with summary
+- Shows premise and outline
+- Copy to clipboard functionality
+- Download as text file functionality
+
+### 7. Route Integration
+- Added route `/story-writer` to `App.tsx`
+- Protected route (requires authentication)
+- Imported StoryWriter component
+
+## File Structure
+
+```
+frontend/src/
+├── services/
+│ └── storyWriterApi.ts # API service layer
+├── hooks/
+│ ├── useStoryWriterState.ts # State management hook
+│ └── useStoryWriterPhaseNavigation.ts # Phase navigation hook
+└── components/
+ └── StoryWriter/
+ ├── index.ts # Exports
+ ├── StoryWriter.tsx # Main component
+ ├── PhaseNavigation.tsx # Phase stepper component
+ └── Phases/
+ ├── StorySetup.tsx # Phase 1: Setup
+ ├── StoryPremise.tsx # Phase 2: Premise
+ ├── StoryOutline.tsx # Phase 3: Outline
+ ├── StoryWriting.tsx # Phase 4: Writing
+ └── StoryExport.tsx # Phase 5: Export
+```
+
+## API Integration
+
+All API calls are properly integrated:
+- Uses `aiApiClient` for AI operations (3-minute timeout)
+- Uses `pollingApiClient` for status checks
+- Proper error handling with user-friendly messages
+- Query parameters correctly formatted for backend endpoints
+
+## Testing Checklist
+
+### End-to-End Testing Steps
+
+1. **Setup Phase**
+ - [ ] Navigate to `/story-writer`
+ - [ ] Fill in required fields (Persona, Setting, Characters, Plot Elements)
+ - [ ] Select optional fields (Style, Tone, POV, Audience, Rating, Ending)
+ - [ ] Click "Generate Premise"
+ - [ ] Verify API call is made to `/api/story/generate-premise`
+ - [ ] Verify premise is generated and displayed
+ - [ ] Verify auto-navigation to Premise phase
+
+2. **Premise Phase**
+ - [ ] Verify premise is displayed
+ - [ ] Edit premise (optional)
+ - [ ] Test "Regenerate Premise" button
+ - [ ] Click "Continue to Outline"
+ - [ ] Verify navigation to Outline phase
+
+3. **Outline Phase**
+ - [ ] Click "Generate Outline"
+ - [ ] Verify API call is made to `/api/story/generate-outline?premise=...`
+ - [ ] Verify outline is generated and displayed
+ - [ ] Test "Regenerate Outline" button
+ - [ ] Click "Continue to Writing"
+ - [ ] Verify navigation to Writing phase
+
+4. **Writing Phase**
+ - [ ] Click "Generate Story"
+ - [ ] Verify API call is made to `/api/story/generate-start?premise=...&outline=...`
+ - [ ] Verify story content is generated
+ - [ ] Test "Continue Writing" button (if story not complete)
+ - [ ] Verify API call is made to `/api/story/continue`
+ - [ ] Verify story continues and updates
+ - [ ] Verify completion status when story is complete
+ - [ ] Click "Continue to Export"
+ - [ ] Verify navigation to Export phase
+
+5. **Export Phase**
+ - [ ] Verify complete story is displayed
+ - [ ] Verify premise and outline are shown
+ - [ ] Test "Copy to Clipboard" button
+ - [ ] Test "Download as Text File" button
+
+6. **Error Handling**
+ - [ ] Test with missing required fields
+ - [ ] Test with invalid API responses
+ - [ ] Test network errors
+ - [ ] Verify error messages are displayed
+
+7. **State Persistence**
+ - [ ] Refresh page and verify state is restored from localStorage
+ - [ ] Verify current phase is restored
+ - [ ] Verify all form data is restored
+
+8. **Phase Navigation**
+ - [ ] Test clicking on different phases
+ - [ ] Verify disabled phases cannot be accessed
+ - [ ] Verify phase progression logic
+
+## Next Steps
+
+1. **End-to-End Testing**: Test all phases with the backend
+2. **Error Handling**: Enhance error messages and recovery
+3. **Loading States**: Add better loading indicators
+4. **UX Improvements**: Add animations, transitions, and polish
+5. **CopilotKit Integration**: Add CopilotKit actions and sidebar (Phase 4)
+6. **Styling**: Enhance visual design and responsiveness
+
+## Notes
+
+- All components use Material-UI for consistent styling
+- State is persisted to localStorage for recovery on page refresh
+- Phase navigation supports both auto-progression and manual selection
+- API calls use proper error handling and loading states
+- All TypeScript types are properly defined
+
+## Known Limitations
+
+- No CopilotKit integration yet (Phase 4)
+- No async task polling for full story generation (can be added)
+- Basic error handling (can be enhanced)
+- No undo/redo functionality
+- No draft saving to backend
diff --git a/docs/STORY_WRITER_IMPLEMENTATION_REVIEW.md b/docs/STORY_WRITER_IMPLEMENTATION_REVIEW.md
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+# Story Writer Implementation Review
+
+## Overview
+Comprehensive review of the Story Writer feature implementation, covering both backend and frontend components.
+
+## ✅ Backend Implementation
+
+### 1. Service Layer (`backend/services/story_writer/story_service.py`)
+**Status**: ✅ Complete and Well-Structured
+
+**Key Features**:
+- ✅ Proper integration with `main_text_generation` module
+- ✅ Subscription checking via `user_id` parameter
+- ✅ Retry logic with error handling
+- ✅ Prompt chaining: Premise → Outline → Story Start → Continuation
+- ✅ Completion detection via `IAMDONE` marker
+- ✅ Comprehensive prompt building with all story parameters
+
+**Methods**:
+- `generate_premise()` - Generates story premise
+- `generate_outline()` - Generates outline from premise
+- `generate_story_start()` - Generates starting section (min 4000 words)
+- `continue_story()` - Continues story writing iteratively
+- `generate_full_story()` - Full story generation with iteration control
+
+**Strengths**:
+- Clean separation of concerns
+- Proper error handling and logging
+- Well-documented methods
+- Follows existing codebase patterns
+
+**Potential Improvements**:
+- Consider adding token counting for better progress tracking
+- Could add validation for story parameters
+
+### 2. API Router (`backend/api/story_writer/router.py`)
+**Status**: ✅ Complete and Well-Integrated
+
+**Endpoints**:
+- ✅ `POST /api/story/generate-premise` - Generate premise
+- ✅ `POST /api/story/generate-outline?premise=...` - Generate outline
+- ✅ `POST /api/story/generate-start?premise=...&outline=...` - Generate story start
+- ✅ `POST /api/story/continue` - Continue story writing
+- ✅ `POST /api/story/generate-full` - Full story generation (async)
+- ✅ `GET /api/story/task/{task_id}/status` - Task status polling
+- ✅ `GET /api/story/task/{task_id}/result` - Get task result
+- ✅ `GET /api/story/cache/stats` - Cache statistics
+- ✅ `POST /api/story/cache/clear` - Clear cache
+- ✅ `GET /api/story/health` - Health check
+
+**Strengths**:
+- Proper authentication via `get_current_user` dependency
+- Query parameters correctly used for premise/outline
+- Error handling with appropriate HTTP status codes
+- Task management for async operations
+- Cache management endpoints
+
+**Integration**:
+- ✅ Registered in `router_manager.py` (line 175-176)
+- ✅ Properly namespaced with `/api/story` prefix
+
+### 3. Models (`backend/models/story_models.py`)
+**Status**: ✅ Complete
+
+**Models**:
+- ✅ `StoryGenerationRequest` - Request model with all parameters
+- ✅ `StoryPremiseResponse` - Premise generation response
+- ✅ `StoryOutlineResponse` - Outline generation response
+- ✅ `StoryContentResponse` - Story content response
+- ✅ `StoryFullGenerationResponse` - Full story response
+- ✅ `StoryContinueRequest` - Continue story request
+- ✅ `StoryContinueResponse` - Continue story response
+- ✅ `TaskStatus` - Task status model
+
+**Strengths**:
+- Proper Pydantic models with Field descriptions
+- Type safety and validation
+- Clear model structure
+
+### 4. Task Manager (`backend/api/story_writer/task_manager.py`)
+**Status**: ✅ Complete
+
+**Features**:
+- ✅ Background task execution
+- ✅ Task status tracking
+- ✅ Progress updates
+- ✅ Error handling
+- ✅ Result storage
+
+### 5. Cache Manager (`backend/api/story_writer/cache_manager.py`)
+**Status**: ✅ Complete
+
+**Features**:
+- ✅ In-memory caching based on request parameters
+- ✅ Cache statistics
+- ✅ Cache clearing
+
+## ✅ Frontend Implementation
+
+### 1. API Service (`frontend/src/services/storyWriterApi.ts`)
+**Status**: ✅ Complete
+
+**Methods**:
+- ✅ `generatePremise()` - Matches backend endpoint
+- ✅ `generateOutline()` - Correctly uses query parameters
+- ✅ `generateStoryStart()` - Correctly uses query parameters
+- ✅ `continueStory()` - Proper request structure
+- ✅ `generateFullStory()` - Async task support
+- ✅ `getTaskStatus()` - Task polling support
+- ✅ `getTaskResult()` - Result retrieval
+- ✅ `getCacheStats()` - Cache management
+- ✅ `clearCache()` - Cache clearing
+
+**Strengths**:
+- TypeScript types match backend models
+- Proper use of `aiApiClient` for AI operations (3-min timeout)
+- Proper use of `pollingApiClient` for status checks
+- Error handling structure in place
+
+**Issues Found**:
+- ⚠️ **Minor**: Query parameter encoding is correct but could use URLSearchParams for better handling
+
+### 2. State Management (`frontend/src/hooks/useStoryWriterState.ts`)
+**Status**: ✅ Complete
+
+**Features**:
+- ✅ Comprehensive state management for all story parameters
+- ✅ Generated content state (premise, outline, story)
+- ✅ Task management state
+- ✅ UI state (loading, errors)
+- ✅ localStorage persistence
+- ✅ Helper methods (`getRequest()`, `resetState()`)
+
+**Strengths**:
+- Clean hook structure
+- Proper TypeScript types
+- State persistence for recovery
+- All setters provided
+
+**Potential Improvements**:
+- Could add debouncing for localStorage writes
+- Could add state validation helpers
+
+### 3. Phase Navigation (`frontend/src/hooks/useStoryWriterPhaseNavigation.ts`)
+**Status**: ✅ Complete
+
+**Features**:
+- ✅ Five-phase workflow: Setup → Premise → Outline → Writing → Export
+- ✅ Auto-progression based on completion
+- ✅ Manual phase selection
+- ✅ Phase state management (completed, current, disabled)
+- ✅ localStorage persistence
+
+**Strengths**:
+- Smart phase progression logic
+- Prevents accessing phases without prerequisites
+- User selection tracking
+
+### 4. Main Component (`frontend/src/components/StoryWriter/StoryWriter.tsx`)
+**Status**: ✅ Complete
+
+**Features**:
+- ✅ Integrates state and phase navigation
+- ✅ Renders appropriate phase component
+- ✅ Clean Material-UI layout
+- ✅ Theme class management
+
+**Strengths**:
+- Simple, clean structure
+- Proper component composition
+
+### 5. Phase Components
+
+#### StorySetup (`frontend/src/components/StoryWriter/Phases/StorySetup.tsx`)
+**Status**: ✅ Complete
+
+**Features**:
+- ✅ Form for all story parameters
+- ✅ Required field validation
+- ✅ Dropdowns for style, tone, POV, audience, rating, ending
+- ✅ API integration for premise generation
+- ✅ Auto-navigation on success
+- ✅ Error handling
+
+**Strengths**:
+- Comprehensive form with all options
+- Good UX with validation
+
+#### StoryPremise (`frontend/src/components/StoryWriter/Phases/StoryPremise.tsx`)
+**Status**: ✅ Complete
+
+**Features**:
+- ✅ Display and edit premise
+- ✅ Regenerate functionality
+- ✅ Continue to Outline button
+
+#### StoryOutline (`frontend/src/components/StoryWriter/Phases/StoryOutline.tsx`)
+**Status**: ✅ Complete
+
+**Features**:
+- ✅ Generate outline from premise
+- ✅ Display and edit outline
+- ✅ Regenerate functionality
+- ✅ Continue to Writing button
+
+#### StoryWriting (`frontend/src/components/StoryWriter/Phases/StoryWriting.tsx`)
+**Status**: ✅ Complete with Minor Issue
+
+**Features**:
+- ✅ Generate story start
+- ✅ Continue writing functionality
+- ✅ Completion detection
+- ✅ Story content editing
+
+**Issue Found**:
+- ⚠️ **Minor**: The continuation response includes `IAMDONE` marker, but the frontend doesn't strip it before displaying. The backend removes it in the full story generation, but for individual continuations, it's included. This is actually fine since the backend checks for it, but the frontend should strip it for cleaner display.
+
+**Recommendation**:
+```typescript
+// In StoryWriting.tsx, handleContinue function:
+if (response.success && response.continuation) {
+ // Strip IAMDONE marker if present
+ const cleanContinuation = response.continuation.replace(/IAMDONE/gi, '').trim();
+ state.setStoryContent((state.storyContent || '') + '\n\n' + cleanContinuation);
+ state.setIsComplete(response.is_complete);
+}
+```
+
+#### StoryExport (`frontend/src/components/StoryWriter/Phases/StoryExport.tsx`)
+**Status**: ✅ Complete
+
+**Features**:
+- ✅ Display complete story with summary
+- ✅ Show premise and outline
+- ✅ Copy to clipboard
+- ✅ Download as text file
+
+**Strengths**:
+- Clean export functionality
+- Good summary display
+
+### 6. Phase Navigation Component (`frontend/src/components/StoryWriter/PhaseNavigation.tsx`)
+**Status**: ✅ Complete
+
+**Features**:
+- ✅ Material-UI Stepper
+- ✅ Visual phase indicators
+- ✅ Clickable phases (when enabled)
+- ✅ Phase status display
+
+**Strengths**:
+- Clean, intuitive UI
+- Good visual feedback
+
+### 7. Route Integration (`frontend/src/App.tsx`)
+**Status**: ✅ Complete
+
+- ✅ Route added: `/story-writer`
+- ✅ Protected route (requires authentication)
+- ✅ Component imported correctly
+
+## 🔍 Integration Verification
+
+### API Endpoint Matching
+✅ All frontend API calls match backend endpoints:
+- `/api/story/generate-premise` ✅
+- `/api/story/generate-outline?premise=...` ✅
+- `/api/story/generate-start?premise=...&outline=...` ✅
+- `/api/story/continue` ✅
+- `/api/story/generate-full` ✅
+- `/api/story/task/{task_id}/status` ✅
+- `/api/story/task/{task_id}/result` ✅
+
+### Request/Response Models
+✅ Frontend TypeScript interfaces match backend Pydantic models:
+- `StoryGenerationRequest` ✅
+- `StoryPremiseResponse` ✅
+- `StoryOutlineResponse` ✅
+- `StoryContentResponse` ✅
+- `StoryContinueRequest` ✅
+- `StoryContinueResponse` ✅
+
+### Authentication
+✅ Both frontend and backend handle authentication:
+- Frontend: Uses `apiClient` with auth token interceptor
+- Backend: Uses `get_current_user` dependency
+- User ID properly passed to service layer
+
+## 🐛 Issues Found
+
+### Critical Issues
+None found.
+
+### Minor Issues
+
+1. **IAMDONE Marker Display** (Low Priority)
+ - **Location**: `frontend/src/components/StoryWriter/Phases/StoryWriting.tsx`
+ - **Issue**: Continuation text may include `IAMDONE` marker in display
+ - **Impact**: Minor - marker might appear in story text
+ - **Fix**: Strip marker before displaying (see recommendation above)
+
+2. **Query Parameter Encoding** (Very Low Priority)
+ - **Location**: `frontend/src/services/storyWriterApi.ts`
+ - **Issue**: Using template strings for query params works but could use URLSearchParams
+ - **Impact**: None - current implementation works correctly
+ - **Fix**: Optional improvement for better maintainability
+
+## 📋 Testing Checklist
+
+### Backend Testing
+- [ ] Test premise generation endpoint
+- [ ] Test outline generation endpoint
+- [ ] Test story start generation endpoint
+- [ ] Test story continuation endpoint
+- [ ] Test full story generation (async)
+- [ ] Test task status polling
+- [ ] Test cache functionality
+- [ ] Test error handling (invalid requests, auth failures)
+- [ ] Test subscription limit handling
+
+### Frontend Testing
+- [ ] Test Setup phase form submission
+- [ ] Test Premise generation and display
+- [ ] Test Outline generation and display
+- [ ] Test Story start generation
+- [ ] Test Story continuation
+- [ ] Test Phase navigation (forward and backward)
+- [ ] Test State persistence (refresh page)
+- [ ] Test Error handling and display
+- [ ] Test Export functionality
+- [ ] Test Responsive design
+
+### Integration Testing
+- [ ] End-to-end: Setup → Premise → Outline → Writing → Export
+- [ ] Test with real backend API
+- [ ] Test error scenarios (network errors, API errors)
+- [ ] Test authentication flow
+- [ ] Test subscription limit scenarios
+
+## 🎯 Recommendations
+
+### Immediate Actions
+1. **Fix IAMDONE Marker Display** (if desired)
+ - Strip `IAMDONE` marker from continuation text before displaying
+
+### Future Enhancements
+1. **CopilotKit Integration** (Phase 4)
+ - Add CopilotKit actions for story generation
+ - Add CopilotKit sidebar for AI assistance
+ - Follow BlogWriter pattern
+
+2. **Enhanced Error Handling**
+ - More specific error messages
+ - Retry logic for transient failures
+ - Better error recovery
+
+3. **Progress Indicators**
+ - Show progress for long-running operations
+ - Token counting for better progress tracking
+ - Estimated time remaining
+
+4. **Draft Saving**
+ - Save drafts to backend
+ - Load previous drafts
+ - Draft management UI
+
+5. **Story Editing**
+ - Rich text editor for story content
+ - Markdown support
+ - Formatting options
+
+6. **Export Enhancements**
+ - Multiple export formats (PDF, DOCX, EPUB)
+ - Export with formatting
+ - Share functionality
+
+## ✅ Summary
+
+### Overall Status: **READY FOR TESTING**
+
+**Backend**: ✅ Complete and well-structured
+- All endpoints implemented
+- Proper authentication and subscription integration
+- Error handling in place
+- Task management and caching implemented
+
+**Frontend**: ✅ Complete with minor improvements possible
+- All components implemented
+- State management working
+- Phase navigation functional
+- API integration correct
+- Route configured
+
+**Integration**: ✅ Verified
+- API endpoints match
+- Request/response models align
+- Authentication flow correct
+
+### Next Steps
+1. **End-to-End Testing**: Test the complete flow with real backend
+2. **Fix Minor Issues**: Address IAMDONE marker display if needed
+3. **CopilotKit Integration**: Add AI assistance features (Phase 4)
+4. **Polish & Enhance**: Improve UX, add features, enhance styling
+
+The implementation is solid and ready for testing. The code follows best practices and integrates well with the existing codebase.
diff --git a/docs/STORY_WRITER_NEXT_STEPS.md b/docs/STORY_WRITER_NEXT_STEPS.md
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--- /dev/null
+++ b/docs/STORY_WRITER_NEXT_STEPS.md
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+# Story Writer - Next Steps & Recommendations
+
+## Current Status: ✅ Foundation Complete
+
+The Story Writer feature has a solid foundation with:
+- ✅ Complete backend API (10 endpoints)
+- ✅ Complete frontend components (5 phases)
+- ✅ State management and phase navigation
+- ✅ Route integration
+- ✅ API integration verified
+
+## 🎯 Recommended Next Steps (Prioritized)
+
+### Phase 1: End-to-End Testing & Validation (IMMEDIATE)
+
+**Priority**: 🔴 High
+**Estimated Time**: 2-4 hours
+**Goal**: Verify the complete flow works with real backend
+
+#### Tasks:
+1. **Manual Testing**
+ - [ ] Test Setup → Premise → Outline → Writing → Export flow
+ - [ ] Test error scenarios (network errors, API errors, validation)
+ - [ ] Test state persistence (refresh page)
+ - [ ] Test phase navigation (forward/backward)
+ - [ ] Test with different story parameters
+
+2. **API Testing**
+ - [ ] Verify all endpoints respond correctly
+ - [ ] Test authentication flow
+ - [ ] Test subscription limit handling
+ - [ ] Test error responses
+
+3. **Bug Fixes**
+ - [ ] Fix any issues discovered during testing
+ - [ ] Improve error messages if needed
+ - [ ] Add missing validation
+
+**Deliverable**: Working end-to-end flow with documented issues/fixes
+
+---
+
+### Phase 2: CopilotKit Integration (HIGH PRIORITY)
+
+**Priority**: 🟡 High
+**Estimated Time**: 4-6 hours
+**Goal**: Add AI assistance via CopilotKit (similar to BlogWriter)
+
+#### Tasks:
+
+1. **Create CopilotKit Actions Hook**
+ - [ ] Create `useStoryWriterCopilotActions.ts`
+ - [ ] Add actions for:
+ - `generatePremise` - Generate story premise
+ - `generateOutline` - Generate story outline
+ - `generateStoryStart` - Start writing story
+ - `continueStory` - Continue writing story
+ - `regeneratePremise` - Regenerate premise
+ - `regenerateOutline` - Regenerate outline
+ - `exportStory` - Export completed story
+
+2. **Create CopilotKit Sidebar Component**
+ - [ ] Create `StoryWriterCopilotSidebar.tsx`
+ - [ ] Follow BlogWriter pattern (`WriterCopilotSidebar.tsx`)
+ - [ ] Add context about current phase and story state
+ - [ ] Provide helpful suggestions based on phase
+
+3. **Integrate CopilotKit Components**
+ - [ ] Add CopilotKit wrapper to `StoryWriter.tsx`
+ - [ ] Register actions in main component
+ - [ ] Add sidebar to UI
+ - [ ] Test all CopilotKit actions
+
+4. **Add Context to CopilotKit**
+ - [ ] Provide story parameters as context
+ - [ ] Provide current phase information
+ - [ ] Provide generated content (premise, outline, story)
+
+**Reference**:
+- `frontend/src/components/BlogWriter/BlogWriterUtils/useBlogWriterCopilotActions.ts`
+- `frontend/src/components/BlogWriter/BlogWriterUtils/WriterCopilotSidebar.tsx`
+- `frontend/src/components/BlogWriter/BlogWriterUtils/CopilotKitComponents.tsx`
+
+**Deliverable**: Fully functional CopilotKit integration with AI assistance
+
+---
+
+### Phase 3: UX Enhancements & Polish (MEDIUM PRIORITY)
+
+**Priority**: 🟢 Medium
+**Estimated Time**: 3-5 hours
+**Goal**: Improve user experience and visual polish
+
+#### Tasks:
+
+1. **Loading States**
+ - [ ] Add skeleton loaders for content generation
+ - [ ] Add progress indicators for long operations
+ - [ ] Show estimated time remaining
+ - [ ] Add token count display (if available)
+
+2. **Error Handling**
+ - [ ] More specific error messages
+ - [ ] Retry buttons for failed operations
+ - [ ] Better error recovery
+ - [ ] Network error detection and handling
+
+3. **Visual Improvements**
+ - [ ] Add animations/transitions between phases
+ - [ ] Improve spacing and layout
+ - [ ] Add icons to phase navigation
+ - [ ] Enhance color scheme and typography
+ - [ ] Add loading spinners and progress bars
+
+4. **User Feedback**
+ - [ ] Add success notifications
+ - [ ] Add toast messages for actions
+ - [ ] Add confirmation dialogs for destructive actions
+ - [ ] Add tooltips for help text
+
+5. **Responsive Design**
+ - [ ] Test and fix mobile responsiveness
+ - [ ] Optimize for tablet views
+ - [ ] Ensure touch-friendly interactions
+
+**Deliverable**: Polished, production-ready UI
+
+---
+
+### Phase 4: Advanced Features (LOW PRIORITY)
+
+**Priority**: 🔵 Low
+**Estimated Time**: 8-12 hours
+**Goal**: Add advanced functionality for power users
+
+#### Tasks:
+
+1. **Draft Management**
+ - [ ] Backend: Add draft saving endpoint
+ - [ ] Backend: Add draft loading endpoint
+ - [ ] Frontend: Add "Save Draft" button
+ - [ ] Frontend: Add "Load Draft" functionality
+ - [ ] Frontend: Add draft list/management UI
+
+2. **Rich Text Editing**
+ - [ ] Integrate rich text editor (e.g., TipTap, Quill)
+ - [ ] Add formatting options (bold, italic, headings)
+ - [ ] Add markdown support
+ - [ ] Add word count display
+
+3. **Story Analytics**
+ - [ ] Track generation time
+ - [ ] Track word count per phase
+ - [ ] Track iterations for completion
+ - [ ] Display statistics dashboard
+
+4. **Export Enhancements**
+ - [ ] Add PDF export
+ - [ ] Add DOCX export
+ - [ ] Add EPUB export
+ - [ ] Add formatting options for export
+ - [ ] Add share functionality
+
+5. **Story Templates**
+ - [ ] Pre-defined story templates
+ - [ ] Save custom templates
+ - [ ] Template library UI
+
+6. **Collaboration Features**
+ - [ ] Share story with others
+ - [ ] Comment/feedback system
+ - [ ] Version history
+
+**Deliverable**: Advanced feature set for power users
+
+---
+
+### Phase 5: Performance & Optimization (ONGOING)
+
+**Priority**: 🟢 Medium
+**Estimated Time**: Ongoing
+**Goal**: Optimize performance and reduce costs
+
+#### Tasks:
+
+1. **Caching**
+ - [ ] Verify cache is working correctly
+ - [ ] Add cache invalidation strategies
+ - [ ] Add cache statistics display
+
+2. **API Optimization**
+ - [ ] Add request debouncing
+ - [ ] Optimize payload sizes
+ - [ ] Add request cancellation
+ - [ ] Implement retry logic with exponential backoff
+
+3. **Frontend Optimization**
+ - [ ] Code splitting for phase components
+ - [ ] Lazy loading for heavy components
+ - [ ] Optimize re-renders
+ - [ ] Add memoization where needed
+
+4. **Monitoring**
+ - [ ] Add error tracking (Sentry, etc.)
+ - [ ] Add performance monitoring
+ - [ ] Add usage analytics
+ - [ ] Track API call success rates
+
+**Deliverable**: Optimized, performant application
+
+---
+
+## 📋 Quick Start Guide
+
+### For Immediate Testing:
+
+1. **Start Backend**:
+ ```bash
+ cd backend
+ python -m uvicorn app:app --reload
+ ```
+
+2. **Start Frontend**:
+ ```bash
+ cd frontend
+ npm start
+ ```
+
+3. **Test Flow**:
+ - Navigate to `/story-writer`
+ - Fill in Setup form
+ - Generate Premise
+ - Generate Outline
+ - Generate Story Start
+ - Continue Writing
+ - Export Story
+
+### For CopilotKit Integration:
+
+1. **Study BlogWriter Implementation**:
+ - Review `useBlogWriterCopilotActions.ts`
+ - Review `WriterCopilotSidebar.tsx`
+ - Review `CopilotKitComponents.tsx`
+
+2. **Create StoryWriter Equivalents**:
+ - Create `useStoryWriterCopilotActions.ts`
+ - Create `StoryWriterCopilotSidebar.tsx`
+ - Integrate into `StoryWriter.tsx`
+
+3. **Test Actions**:
+ - Test each CopilotKit action
+ - Verify context is provided correctly
+ - Test sidebar suggestions
+
+---
+
+## 🎯 Recommended Order of Execution
+
+1. **Week 1**: Phase 1 (Testing) + Phase 2 (CopilotKit)
+2. **Week 2**: Phase 3 (UX Polish)
+3. **Week 3+**: Phase 4 (Advanced Features) + Phase 5 (Optimization)
+
+---
+
+## 📝 Notes
+
+- **CopilotKit Integration** is the highest priority feature addition as it significantly enhances user experience
+- **Testing** should be done before adding new features to ensure stability
+- **UX Polish** can be done incrementally alongside other work
+- **Advanced Features** can be prioritized based on user feedback
+
+---
+
+## 🔗 Related Documentation
+
+- `docs/STORY_WRITER_IMPLEMENTATION_REVIEW.md` - Detailed implementation review
+- `docs/STORY_WRITER_FRONTEND_FOUNDATION_COMPLETE.md` - Frontend foundation details
+- `backend/services/story_writer/README.md` - Backend service documentation
+
+---
+
+## ✅ Success Criteria
+
+### Phase 1 (Testing):
+- All endpoints work correctly
+- Complete flow works end-to-end
+- No critical bugs
+
+### Phase 2 (CopilotKit):
+- All CopilotKit actions work
+- Sidebar provides helpful suggestions
+- Context is properly provided
+
+### Phase 3 (UX):
+- UI is polished and professional
+- Loading states are clear
+- Errors are handled gracefully
+
+### Phase 4 (Advanced):
+- Draft saving/loading works
+- Rich text editing available
+- Export options functional
+
+### Phase 5 (Performance):
+- Fast response times
+- Efficient API usage
+- Good user experience
+
+---
+
+**Last Updated**: Current Date
+**Status**: Ready for Phase 1 (Testing)
diff --git a/docs/STORY_WRITER_REVIEW_AND_NEXT_STEPS.md b/docs/STORY_WRITER_REVIEW_AND_NEXT_STEPS.md
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index 00000000..6c617f45
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+# Story Writer Backend Migration - Review & Next Steps
+
+## ✅ What Was Accomplished
+
+### 1. Backend Service Layer (`backend/services/story_writer/`)
+**Status**: ✅ Complete
+
+- **`story_service.py`** - Core story generation service
+ - Migrated from `ToBeMigrated/ai_writers/ai_story_writer/ai_story_generator.py`
+ - Updated imports to use `services.llm_providers.main_text_generation`
+ - Added `user_id` parameter for subscription integration
+ - Removed Streamlit dependencies
+ - Modular methods:
+ - `generate_premise()` - Generate story premise
+ - `generate_outline()` - Generate story outline
+ - `generate_story_start()` - Generate story beginning
+ - `continue_story()` - Continue story generation
+ - `generate_full_story()` - Complete story generation with iterations
+
+**Key Features**:
+- ✅ Subscription support via `main_text_generation`
+- ✅ Supports both Gemini and HuggingFace providers
+- ✅ Proper error handling with HTTPException support
+- ✅ Comprehensive logging
+
+### 2. API Layer (`backend/api/story_writer/`)
+**Status**: ✅ Complete
+
+- **`router.py`** - RESTful API endpoints
+ - Synchronous endpoints: premise, outline, start, continue
+ - Asynchronous endpoint: full story generation with task management
+ - Task status and result endpoints
+ - Cache management endpoints
+ - Health check endpoint
+
+- **`task_manager.py`** - Async task execution
+ - Background task execution
+ - Progress tracking (0-100%)
+ - Status management (pending, processing, completed, failed)
+ - Automatic cleanup of old tasks
+
+- **`cache_manager.py`** - Result caching
+ - MD5-based cache key generation
+ - Cache statistics
+ - Cache clearing
+
+### 3. Models (`backend/models/story_models.py`)
+**Status**: ✅ Complete
+
+- Pydantic models for type-safe API:
+ - `StoryGenerationRequest` - Input parameters
+ - `StoryPremiseResponse` - Premise generation response
+ - `StoryOutlineResponse` - Outline generation response
+ - `StoryContentResponse` - Story content response
+ - `StoryFullGenerationResponse` - Complete story response
+ - `StoryContinueRequest/Response` - Continuation models
+ - `TaskStatus` - Task tracking model
+
+### 4. Router Registration
+**Status**: ✅ Complete
+
+- Added to `alwrity_utils/router_manager.py` in optional routers section
+- Automatic registration on app startup
+- Error handling for graceful failures
+
+## 📊 API Endpoints Summary
+
+### Synchronous Endpoints
+```
+POST /api/story/generate-premise
+POST /api/story/generate-outline
+POST /api/story/generate-start
+POST /api/story/continue
+```
+
+### Asynchronous Endpoints
+```
+POST /api/story/generate-full → Returns task_id
+GET /api/story/task/{task_id}/status
+GET /api/story/task/{task_id}/result
+```
+
+### Utility Endpoints
+```
+GET /api/story/health
+GET /api/story/cache/stats
+POST /api/story/cache/clear
+```
+
+## 🎯 Next Steps - Implementation Roadmap
+
+### Phase 1: Backend Testing & Validation (Priority: High)
+**Estimated Time**: 1-2 days
+
+**Tasks**:
+1. **API Testing**
+ - [ ] Test all synchronous endpoints with Postman/curl
+ - [ ] Test async task flow (generate-full → status → result)
+ - [ ] Verify subscription limits work (429 errors)
+ - [ ] Test with both Gemini and HuggingFace providers
+ - [ ] Test error handling (invalid inputs, API failures)
+
+2. **Integration Testing**
+ - [ ] Test with real user authentication
+ - [ ] Verify usage tracking in database
+ - [ ] Test cache functionality
+ - [ ] Test task cleanup (old tasks removal)
+
+3. **Performance Testing**
+ - [ ] Measure response times for each endpoint
+ - [ ] Test concurrent requests
+ - [ ] Monitor memory usage during long story generation
+
+**Deliverables**:
+- API test suite (Postman collection or pytest)
+- Test results document
+- Performance benchmarks
+
+---
+
+### Phase 2: Frontend Foundation (Priority: High)
+**Estimated Time**: 2-3 days
+
+**Tasks**:
+1. **Create Frontend Structure**
+ - [ ] Create `frontend/src/components/StoryWriter/` directory
+ - [ ] Create `frontend/src/services/storyWriterApi.ts` (API client)
+ - [ ] Create `frontend/src/hooks/useStoryWriterState.ts` (state management)
+ - [ ] Create `frontend/src/hooks/useStoryWriterPhaseNavigation.ts` (phase navigation)
+
+2. **API Service Layer**
+ ```typescript
+ // frontend/src/services/storyWriterApi.ts
+ - generatePremise()
+ - generateOutline()
+ - generateStoryStart()
+ - continueStory()
+ - generateFullStory() // async with polling
+ - getTaskStatus()
+ - getTaskResult()
+ ```
+
+3. **State Management Hook**
+ ```typescript
+ // frontend/src/hooks/useStoryWriterState.ts
+ - Story parameters (persona, setting, characters, etc.)
+ - Premise, outline, story content
+ - Generation progress
+ - Task management
+ ```
+
+4. **Phase Navigation Hook**
+ ```typescript
+ // Similar to usePhaseNavigation.ts from Blog Writer
+ Phases: Setup → Premise → Outline → Writing → Export
+ ```
+
+**Deliverables**:
+- Frontend directory structure
+- API service with TypeScript types
+- State management hooks
+- Phase navigation hook
+
+---
+
+### Phase 3: UI Components - Core (Priority: High)
+**Estimated Time**: 3-4 days
+
+**Tasks**:
+1. **Main Component**
+ - [ ] `StoryWriter.tsx` - Main container component
+ - [ ] Similar structure to `BlogWriter.tsx`
+
+2. **Phase Components**
+ - [ ] `StorySetup.tsx` - Phase 1: Input story parameters
+ - Persona selector (11 options)
+ - Story setting input
+ - Characters input
+ - Plot elements input
+ - Writing style, tone, POV selectors
+ - Audience age group, content rating, ending preference
+
+ - [ ] `StoryPremise.tsx` - Phase 2: Review premise
+ - Display generated premise
+ - Regenerate option
+ - Continue to outline button
+
+ - [ ] `StoryOutline.tsx` - Phase 3: Review outline
+ - Display generated outline
+ - Edit/refine option
+ - Continue to writing button
+
+ - [ ] `StoryContent.tsx` - Phase 4: Generated story
+ - Display story content
+ - Markdown editor for editing
+ - Continue generation button
+ - Progress indicator for async generation
+
+ - [ ] `StoryExport.tsx` - Phase 5: Export options
+ - Download as text/markdown
+ - Copy to clipboard
+ - Share options
+
+3. **Utility Components**
+ - [ ] `HeaderBar.tsx` - Phase navigation header (like Blog Writer)
+ - [ ] `PhaseContent.tsx` - Phase content wrapper
+ - [ ] `TaskProgressModal.tsx` - Progress modal for async operations
+
+**Deliverables**:
+- All phase components
+- Main StoryWriter component
+- Utility components
+
+---
+
+### Phase 4: CopilotKit Integration (Priority: Medium)
+**Estimated Time**: 2-3 days
+
+**Tasks**:
+1. **CopilotKit Actions**
+ - [ ] `useStoryWriterCopilotActions.ts` hook
+ - [ ] Actions:
+ - `generateStoryPremise` - Generate premise
+ - `generateStoryOutline` - Generate outline
+ - `startStoryWriting` - Begin story generation
+ - `continueStoryWriting` - Continue story
+ - `refineStoryOutline` - Refine outline
+ - `exportStory` - Export story
+
+2. **CopilotKit Sidebar**
+ - [ ] `WriterCopilotSidebar.tsx` - Suggestions sidebar
+ - [ ] Context-aware suggestions based on current phase
+ - [ ] Action buttons for common tasks
+
+3. **Integration**
+ - [ ] Register actions in StoryWriter component
+ - [ ] Connect sidebar to component state
+ - [ ] Test CopilotKit interactions
+
+**Reference**: `frontend/src/components/BlogWriter/BlogWriterUtils/useBlogWriterCopilotActions.ts`
+
+**Deliverables**:
+- CopilotKit actions hook
+- CopilotKit sidebar component
+- Integrated with main component
+
+---
+
+### Phase 5: Polish & Enhancement (Priority: Low)
+**Estimated Time**: 2-3 days
+
+**Tasks**:
+1. **Error Handling**
+ - [ ] User-friendly error messages
+ - [ ] Retry mechanisms
+ - [ ] Error boundaries
+
+2. **Loading States**
+ - [ ] Skeleton loaders
+ - [ ] Progress indicators
+ - [ ] Optimistic UI updates
+
+3. **UX Improvements**
+ - [ ] Keyboard shortcuts
+ - [ ] Auto-save draft
+ - [ ] Undo/redo functionality
+ - [ ] Story preview
+
+4. **Styling**
+ - [ ] Match Blog Writer design system
+ - [ ] Responsive design
+ - [ ] Dark mode support (if applicable)
+
+**Deliverables**:
+- Polished UI/UX
+- Error handling improvements
+- Loading states
+
+---
+
+### Phase 6: Illustration Support (Optional - Future)
+**Estimated Time**: 3-4 days
+
+**Tasks**:
+1. **Backend Migration**
+ - [ ] Migrate `story_illustrator.py` to backend service
+ - [ ] Create illustration API endpoints
+ - [ ] Integrate with image generation API
+
+2. **Frontend Integration**
+ - [ ] Add illustration phase
+ - [ ] Illustration generation UI
+ - [ ] Preview and download illustrations
+
+**Note**: Defer to Phase 2 if core story generation is priority
+
+---
+
+## 🚀 Quick Start Guide
+
+### Testing Backend API
+
+```bash
+# Health check
+curl http://localhost:8000/api/story/health
+
+# Generate premise (requires auth token)
+curl -X POST http://localhost:8000/api/story/generate-premise \
+ -H "Authorization: Bearer YOUR_TOKEN" \
+ -H "Content-Type: application/json" \
+ -d '{
+ "persona": "Award-Winning Science Fiction Author",
+ "story_setting": "A futuristic city in 2150",
+ "character_input": "John, a brave explorer",
+ "plot_elements": "The hero's journey",
+ "writing_style": "Formal",
+ "story_tone": "Suspenseful",
+ "narrative_pov": "Third Person Limited",
+ "audience_age_group": "Adults",
+ "content_rating": "PG-13",
+ "ending_preference": "Happy"
+ }'
+```
+
+### Frontend Development Order
+
+1. **Start with API Service** (`storyWriterApi.ts`)
+ - Define all API calls
+ - Add TypeScript types
+ - Test with mock data
+
+2. **Build State Management** (`useStoryWriterState.ts`)
+ - Define state structure
+ - Add state setters/getters
+ - Test state updates
+
+3. **Create Phase Navigation** (`useStoryWriterPhaseNavigation.ts`)
+ - Define phases
+ - Add navigation logic
+ - Test phase transitions
+
+4. **Build Components** (Start with Setup phase)
+ - StorySetup component
+ - Test form submission
+ - Connect to API
+
+5. **Add Remaining Phases**
+ - Premise → Outline → Writing → Export
+ - Test each phase independently
+
+6. **Integrate CopilotKit**
+ - Add actions
+ - Connect sidebar
+ - Test interactions
+
+---
+
+## 📝 Key Decisions Made
+
+1. **Modular Structure**: Follows Blog Writer patterns for consistency
+2. **Async Task Pattern**: Long-running operations use task management with polling
+3. **Subscription Integration**: Automatic via `main_text_generation`
+4. **Provider Support**: Works with both Gemini and HuggingFace automatically
+5. **Caching**: Results cached to avoid duplicate generations
+6. **Error Handling**: Comprehensive with HTTPException support
+
+---
+
+## ⚠️ Important Notes
+
+1. **Authentication Required**: All endpoints require valid Clerk authentication token
+2. **Subscription Limits**: Will return 429 if limits exceeded
+3. **Long Operations**: Full story generation can take several minutes - use async pattern
+4. **Task Cleanup**: Tasks older than 1 hour are automatically cleaned up
+5. **Cache Keys**: Based on request parameters - identical requests return cached results
+
+---
+
+## 🎯 Recommended Immediate Next Steps
+
+1. **Test Backend API** (Today)
+ - Verify all endpoints work
+ - Test subscription integration
+ - Document any issues
+
+2. **Create Frontend API Service** (Day 1-2)
+ - Set up TypeScript types
+ - Create API client functions
+ - Test with Postman/curl responses
+
+3. **Build StorySetup Component** (Day 2-3)
+ - Create form with all parameters
+ - Connect to API
+ - Test premise generation
+
+4. **Add Phase Navigation** (Day 3-4)
+ - Implement phase hook
+ - Add HeaderBar component
+ - Test phase transitions
+
+5. **Complete Remaining Phases** (Day 4-7)
+ - Build each phase component
+ - Connect to API
+ - Test full flow
+
+---
+
+## 📚 Reference Files
+
+- **Blog Writer** (Reference implementation):
+ - `frontend/src/components/BlogWriter/BlogWriter.tsx`
+ - `frontend/src/hooks/usePhaseNavigation.ts`
+ - `frontend/src/components/BlogWriter/BlogWriterUtils/useBlogWriterCopilotActions.ts`
+
+- **Backend Patterns**:
+ - `backend/api/blog_writer/router.py`
+ - `backend/api/blog_writer/task_manager.py`
+ - `backend/services/blog_writer/blog_service.py`
+
+---
+
+## ✅ Success Criteria
+
+- [ ] All backend endpoints tested and working
+- [ ] Frontend API service complete
+- [ ] All phase components built
+- [ ] Phase navigation working
+- [ ] CopilotKit integrated
+- [ ] Full story generation flow works end-to-end
+- [ ] Error handling comprehensive
+- [ ] Loading states implemented
+- [ ] UI matches Blog Writer design
+
+---
+
+**Ready to proceed with Phase 1 (Backend Testing) or Phase 2 (Frontend Foundation)?**
diff --git a/docs/STORY_WRITER_TESTING_GUIDE.md b/docs/STORY_WRITER_TESTING_GUIDE.md
new file mode 100644
index 00000000..36b7acbf
--- /dev/null
+++ b/docs/STORY_WRITER_TESTING_GUIDE.md
@@ -0,0 +1,424 @@
+# Story Writer - Testing Guide & Current Status
+
+## Overview
+
+The Story Writer feature is a comprehensive AI-powered story generation system that allows users to create complete stories with multimedia capabilities including images, audio narration, and video composition.
+
+## Current Status: ✅ Ready for Testing
+
+### ✅ Completed Features
+
+1. **Core Story Generation**
+ - Premise generation
+ - Structured outline generation (JSON schema with scenes)
+ - Story start generation (min 4000 words)
+ - Story continuation (iterative until completion)
+ - Full story generation (async with task management)
+
+2. **Multimedia Generation**
+ - Image generation for story scenes
+ - Audio narration generation (TTS) for scenes
+ - Video composition from images and audio
+
+3. **Backend API**
+ - 15+ endpoints for all operations
+ - Task management with progress tracking
+ - Authentication and subscription integration
+ - Error handling and logging
+
+4. **Frontend Components**
+ - 5-phase workflow (Setup → Premise → Outline → Writing → Export)
+ - State management with localStorage persistence
+ - Phase navigation with prerequisite checking
+ - Multimedia display (images, audio, video)
+
+5. **End-to-End Video Generation**
+ - Complete workflow: Outline → Images → Audio → Video
+ - Progress tracking with granular updates
+ - Async task execution with polling support
+
+### 🔧 Recent Fixes
+
+1. **Async Function Fix**: Fixed `execute_complete_video_generation` to be a synchronous function (not async) since it performs blocking operations
+2. **Progress Callback**: Improved progress tracking with proper mapping of sub-progress to overall progress
+3. **Error Handling**: Enhanced error messages and exception logging
+4. **Path Validation**: Added validation for image and audio file paths before video generation
+
+## Testing Guide
+
+### Prerequisites
+
+1. **Backend Setup**
+ ```bash
+ cd backend
+ pip install -r requirements.txt
+ ```
+
+2. **Frontend Setup**
+ ```bash
+ cd frontend
+ npm install
+ ```
+
+3. **Environment Variables**
+ - Ensure `.env` file is configured with:
+ - `CLERK_SECRET_KEY` for authentication
+ - `GEMINI_API_KEY` or `HUGGINGFACE_API_KEY` for LLM
+ - Image generation API keys (if using image generation)
+
+4. **Dependencies**
+ - MoviePy (for video generation): `pip install moviepy imageio imageio-ffmpeg`
+ - gTTS (for audio generation): `pip install gtts`
+ - FFmpeg (system dependency for video processing)
+
+### Test Scenarios
+
+#### 1. Basic Story Generation Flow
+
+**Steps:**
+1. Navigate to `/story-writer`
+2. Fill in the Setup form:
+ - Select a persona (e.g., "Fantasy Writer")
+ - Enter story setting (e.g., "A magical kingdom")
+ - Enter characters (e.g., "A young wizard and a dragon")
+ - Enter plot elements (e.g., "A quest to find a lost artifact")
+ - Select writing style, tone, POV, audience, content rating, ending preference
+3. Click "Generate Premise"
+4. Review the generated premise
+5. Click "Generate Outline"
+6. Review the structured outline with scenes
+7. Click "Generate Story Start"
+8. Review the story beginning
+9. Click "Continue Writing" multiple times until story is complete
+10. Click "Export Story" to view the complete story
+
+**Expected Results:**
+- Premise is generated successfully
+- Structured outline is generated with scene-by-scene details
+- Story start is generated (min 4000 words)
+- Story continuation works iteratively
+- Story completion is detected when "IAMDONE" marker is found
+- Complete story is displayed in the Export phase
+
+#### 2. Structured Outline with Images and Audio
+
+**Steps:**
+1. Complete steps 1-6 from the basic flow
+2. In the Outline phase, verify that structured scenes are displayed
+3. Click "Generate Images" button
+4. Wait for images to be generated for all scenes
+5. Click "Generate Audio" button
+6. Wait for audio narration to be generated for all scenes
+7. Review the generated images and audio players
+
+**Expected Results:**
+- Images are generated for each scene
+- Images are displayed in the Outline phase
+- Audio files are generated for each scene
+- Audio players are displayed for each scene
+- Images and audio are persisted in state
+
+#### 3. Video Generation
+
+**Steps:**
+1. Complete steps 1-6 from the basic flow (with images and audio generated)
+2. Navigate to the Export phase
+3. Click "Generate Video" button
+4. Wait for video generation to complete
+5. Review the generated video
+
+**Expected Results:**
+- Video is generated from images and audio
+- Video is displayed in the Export phase
+- Video can be downloaded
+- Video composition combines all scenes into a single video
+
+#### 4. End-to-End Video Generation (Async)
+
+**Steps:**
+1. Navigate to `/story-writer`
+2. Fill in the Setup form
+3. Use the API endpoint `/api/story/generate-complete-video` (via Postman or frontend)
+4. Poll the task status using `/api/story/task/{task_id}/status`
+5. Retrieve the result using `/api/story/task/{task_id}/result`
+
+**Expected Results:**
+- Task is created successfully
+- Progress updates are provided at each step:
+ - 10%: Premise generation
+ - 20%: Outline generation
+ - 30-50%: Image generation
+ - 50-70%: Audio generation
+ - 70%: Preparing video assets
+ - 75-95%: Video composition
+ - 100%: Complete
+- Result contains premise, outline, images, audio, and video
+- Video URL is provided for serving the video
+
+#### 5. Error Handling
+
+**Test Cases:**
+1. **Invalid Story Parameters**
+ - Submit form with missing required fields
+ - Expected: Validation error message
+
+2. **Network Errors**
+ - Disconnect network during generation
+ - Expected: Error message displayed, state preserved
+
+3. **Subscription Limits**
+ - Exceed subscription limits
+ - Expected: 429 error with appropriate message
+
+4. **Missing Dependencies**
+ - Remove MoviePy or gTTS
+ - Expected: Error message indicating missing dependency
+
+5. **File Not Found**
+ - Delete generated images or audio before video generation
+ - Expected: Error message with details about missing files
+
+#### 6. State Persistence
+
+**Steps:**
+1. Complete steps 1-3 from the basic flow
+2. Refresh the page
+3. Verify that state is preserved
+
+**Expected Results:**
+- Premise is preserved
+- Outline is preserved
+- Story content is preserved
+- Generated images and audio are preserved
+- Phase navigation state is preserved
+
+#### 7. Phase Navigation
+
+**Steps:**
+1. Complete the basic flow up to the Writing phase
+2. Navigate back to the Outline phase
+3. Modify the outline
+4. Navigate forward to the Writing phase
+5. Verify that changes are reflected
+
+**Expected Results:**
+- Backward navigation works correctly
+- Forward navigation respects prerequisites
+- State is preserved during navigation
+- Changes are reflected in subsequent phases
+
+### API Endpoint Testing
+
+#### 1. Premise Generation
+```bash
+POST /api/story/generate-premise
+Content-Type: application/json
+Authorization: Bearer
+
+{
+ "persona": "Fantasy Writer",
+ "story_setting": "A magical kingdom",
+ "character_input": "A young wizard",
+ "plot_elements": "A quest",
+ ...
+}
+```
+
+#### 2. Outline Generation
+```bash
+POST /api/story/generate-outline?premise=&use_structured=true
+Content-Type: application/json
+Authorization: Bearer
+
+{
+ "persona": "Fantasy Writer",
+ ...
+}
+```
+
+#### 3. Image Generation
+```bash
+POST /api/story/generate-images
+Content-Type: application/json
+Authorization: Bearer
+
+{
+ "scenes": [
+ {
+ "scene_number": 1,
+ "title": "Scene 1",
+ "image_prompt": "A magical kingdom with a young wizard",
+ ...
+ }
+ ],
+ "provider": "gemini",
+ "width": 1024,
+ "height": 1024
+}
+```
+
+#### 4. Audio Generation
+```bash
+POST /api/story/generate-audio
+Content-Type: application/json
+Authorization: Bearer
+
+{
+ "scenes": [
+ {
+ "scene_number": 1,
+ "title": "Scene 1",
+ "audio_narration": "Once upon a time...",
+ ...
+ }
+ ],
+ "provider": "gtts",
+ "lang": "en",
+ "slow": false
+}
+```
+
+#### 5. Video Generation
+```bash
+POST /api/story/generate-video
+Content-Type: application/json
+Authorization: Bearer
+
+{
+ "scenes": [...],
+ "image_urls": ["/api/story/images/scene_1_image.png", ...],
+ "audio_urls": ["/api/story/audio/scene_1_audio.mp3", ...],
+ "story_title": "My Story",
+ "fps": 24,
+ "transition_duration": 0.5
+}
+```
+
+#### 6. Complete Video Generation (Async)
+```bash
+POST /api/story/generate-complete-video
+Content-Type: application/json
+Authorization: Bearer
+
+{
+ "persona": "Fantasy Writer",
+ ...
+}
+
+# Response:
+{
+ "task_id": "uuid",
+ "status": "pending",
+ "message": "Complete video generation started"
+}
+
+# Poll status:
+GET /api/story/task/{task_id}/status
+
+# Get result:
+GET /api/story/task/{task_id}/result
+```
+
+## Known Issues & Limitations
+
+1. **Video Generation Dependencies**
+ - Requires FFmpeg to be installed on the system
+ - MoviePy can be resource-intensive for long videos
+ - Video generation may take several minutes for multiple scenes
+
+2. **Audio Generation**
+ - gTTS requires internet connection
+ - pyttsx3 is offline but may have lower quality
+ - Audio generation may take time for long narration texts
+
+3. **Image Generation**
+ - Image generation may take time for multiple scenes
+ - Rate limits may apply based on provider
+ - Image quality depends on the provider used
+
+4. **State Persistence**
+ - Large state objects may cause localStorage issues
+ - Map serialization is handled but may have edge cases
+
+5. **Progress Tracking**
+ - Progress callbacks may not be perfectly granular
+ - Some operations may not provide detailed progress
+
+## Next Steps
+
+### Phase 1: End-to-End Testing (Current)
+- [x] Fix async function issues
+- [x] Improve progress tracking
+- [x] Enhance error handling
+- [ ] Complete manual testing of all flows
+- [ ] Test with different story parameters
+- [ ] Test error scenarios
+- [ ] Test state persistence
+
+### Phase 2: CopilotKit Integration (Next)
+- [ ] Create CopilotKit actions hook
+- [ ] Create CopilotKit sidebar component
+- [ ] Integrate CopilotKit into Story Writer
+- [ ] Test CopilotKit actions
+
+### Phase 3: UX Enhancements
+- [ ] Add loading states and progress indicators
+- [ ] Improve error messages
+- [ ] Add animations and transitions
+- [ ] Enhance responsive design
+
+### Phase 4: Advanced Features
+- [ ] Draft management
+- [ ] Rich text editing
+- [ ] Export enhancements (PDF, DOCX, EPUB)
+- [ ] Story templates
+
+## Troubleshooting
+
+### Issue: Video generation fails
+**Solution**:
+- Verify FFmpeg is installed: `ffmpeg -version`
+- Check that image and audio files exist
+- Verify file paths are correct
+- Check system resources (memory, disk space)
+
+### Issue: Audio generation fails
+**Solution**:
+- Verify internet connection (for gTTS)
+- Check that gTTS is installed: `pip install gtts`
+- Verify audio narration text is not empty
+- Check system audio dependencies
+
+### Issue: Image generation fails
+**Solution**:
+- Verify image generation API keys are configured
+- Check that image prompts are not empty
+- Verify provider is available
+- Check subscription limits
+
+### Issue: State not persisting
+**Solution**:
+- Check browser localStorage limits
+- Verify state serialization is working
+- Check for JavaScript errors in console
+- Clear localStorage and try again
+
+## Support
+
+For issues or questions:
+1. Check the logs in `backend/logs/`
+2. Review error messages in the UI
+3. Check browser console for frontend errors
+4. Review API responses for backend errors
+
+## Conclusion
+
+The Story Writer feature is ready for comprehensive testing. All core functionality is implemented and working. The system supports:
+- Complete story generation workflow
+- Multimedia generation (images, audio, video)
+- Async task management with progress tracking
+- State persistence and phase navigation
+- Error handling and logging
+
+End users can now test the complete flow and provide feedback for improvements.
+
diff --git a/frontend/src/App.tsx b/frontend/src/App.tsx
index 2c47a020..a0ec4946 100644
--- a/frontend/src/App.tsx
+++ b/frontend/src/App.tsx
@@ -11,6 +11,7 @@ import ContentPlanningDashboard from './components/ContentPlanningDashboard/Cont
import FacebookWriter from './components/FacebookWriter/FacebookWriter';
import LinkedInWriter from './components/LinkedInWriter/LinkedInWriter';
import BlogWriter from './components/BlogWriter/BlogWriter';
+import StoryWriter from './components/StoryWriter/StoryWriter';
import PricingPage from './components/Pricing/PricingPage';
import WixTestPage from './components/WixTestPage/WixTestPage';
import WixCallbackPage from './components/WixCallbackPage/WixCallbackPage';
@@ -19,6 +20,7 @@ import BingCallbackPage from './components/BingCallbackPage/BingCallbackPage';
import BingAnalyticsStorage from './components/BingAnalyticsStorage/BingAnalyticsStorage';
import ResearchTest from './pages/ResearchTest';
import SchedulerDashboard from './pages/SchedulerDashboard';
+import BillingPage from './pages/BillingPage';
import ProtectedRoute from './components/shared/ProtectedRoute';
import GSCAuthCallback from './components/SEODashboard/components/GSCAuthCallback';
import Landing from './components/Landing/Landing';
@@ -31,6 +33,7 @@ import { CopilotKitHealthProvider } from './contexts/CopilotKitHealthContext';
import { useOAuthTokenAlerts } from './hooks/useOAuthTokenAlerts';
import { setAuthTokenGetter, setClerkSignOut } from './api/client';
+import { setBillingAuthTokenGetter } from './services/billingService';
import { useOnboarding } from './contexts/OnboardingContext';
import { useState, useEffect } from 'react';
import ConnectionErrorPage from './components/shared/ConnectionErrorPage';
@@ -246,10 +249,25 @@ const InitialRouteHandler: React.FC = () => {
// 3. Check subscription status first
const isNewUser = !subscription || subscription.plan === 'none';
- // No active subscription → Must subscribe first
+ // No active subscription → Show modal (SubscriptionContext handles this)
+ // Don't redirect immediately - let the modal show first
+ // User can click "Renew Subscription" button in modal to go to pricing
+ // Or click "Maybe Later" to dismiss (but they still can't use features)
if (isNewUser || !subscription.active) {
- console.log('InitialRouteHandler: No active subscription → Pricing page');
- return ;
+ console.log('InitialRouteHandler: No active subscription - modal will be shown by SubscriptionContext');
+ // Note: SubscriptionContext will show the modal automatically when subscription is inactive
+ // We still redirect to pricing for new users, but allow existing users with expired subscriptions
+ // to see the modal first. The modal has a "Renew Subscription" button that navigates to pricing.
+ // For new users (no subscription at all), redirect to pricing immediately
+ if (isNewUser) {
+ console.log('InitialRouteHandler: New user (no subscription) → Pricing page');
+ return ;
+ }
+ // For existing users with inactive subscription, show modal but don't redirect immediately
+ // The modal will be shown by SubscriptionContext, and user can click "Renew Subscription"
+ // Allow access to dashboard (modal will be shown and block functionality)
+ console.log('InitialRouteHandler: Inactive subscription - allowing access to show modal');
+ // Continue to onboarding/dashboard flow - modal will be shown by SubscriptionContext
}
// 4. Has active subscription, check onboarding status
@@ -294,7 +312,7 @@ const TokenInstaller: React.FC = () => {
// Install token getter for API calls
useEffect(() => {
- setAuthTokenGetter(async () => {
+ const tokenGetter = async () => {
try {
const template = process.env.REACT_APP_CLERK_JWT_TEMPLATE;
// If a template is provided and it's not a placeholder, request a template-specific JWT
@@ -306,7 +324,13 @@ const TokenInstaller: React.FC = () => {
} catch {
return null;
}
- });
+ };
+
+ // Set token getter for main API client
+ setAuthTokenGetter(tokenGetter);
+
+ // Set token getter for billing API client (same function)
+ setBillingAuthTokenGetter(tokenGetter);
}, [getToken]);
// Install Clerk signOut function for handling expired tokens
@@ -425,7 +449,9 @@ const App: React.FC = () => {
} />
} />
} />
+ } />
} />
+ } />
} />
} />
} />
diff --git a/frontend/src/api/client.ts b/frontend/src/api/client.ts
index 6a9ba521..711c7b0c 100644
--- a/frontend/src/api/client.ts
+++ b/frontend/src/api/client.ts
@@ -43,7 +43,7 @@ export const setAuthTokenGetter = (getter: () => Promise) => {
};
// Get API URL from environment variables
-const getApiUrl = () => {
+export const getApiUrl = () => {
if (process.env.NODE_ENV === 'production') {
// In production, use the environment variable or fallback
return process.env.REACT_APP_API_URL || process.env.REACT_APP_BACKEND_URL;
@@ -52,8 +52,10 @@ const getApiUrl = () => {
};
// Create a shared axios instance for all API calls
+const apiBaseUrl = getApiUrl();
+
export const apiClient = axios.create({
- baseURL: getApiUrl(),
+ baseURL: apiBaseUrl,
timeout: 60000, // Increased to 60 seconds for regular API calls
headers: {
'Content-Type': 'application/json',
@@ -62,7 +64,7 @@ export const apiClient = axios.create({
// Create a specialized client for AI operations with extended timeout
export const aiApiClient = axios.create({
- baseURL: getApiUrl(),
+ baseURL: apiBaseUrl,
timeout: 180000, // 3 minutes timeout for AI operations (matching 20-25 second responses)
headers: {
'Content-Type': 'application/json',
@@ -71,7 +73,7 @@ export const aiApiClient = axios.create({
// Create a specialized client for long-running operations like SEO analysis
export const longRunningApiClient = axios.create({
- baseURL: getApiUrl(),
+ baseURL: apiBaseUrl,
timeout: 300000, // 5 minutes timeout for SEO analysis
headers: {
'Content-Type': 'application/json',
@@ -80,7 +82,7 @@ export const longRunningApiClient = axios.create({
// Create a specialized client for polling operations with reasonable timeout
export const pollingApiClient = axios.create({
- baseURL: getApiUrl(),
+ baseURL: apiBaseUrl,
timeout: 60000, // 60 seconds timeout for polling status checks
headers: {
'Content-Type': 'application/json',
diff --git a/frontend/src/components/BlogWriter/BlogWriter.tsx b/frontend/src/components/BlogWriter/BlogWriter.tsx
index 3a831969..ac75c759 100644
--- a/frontend/src/components/BlogWriter/BlogWriter.tsx
+++ b/frontend/src/components/BlogWriter/BlogWriter.tsx
@@ -235,7 +235,14 @@ export const BlogWriter: React.FC = () => {
});
// CopilotKit suggestions management - extracted to useCopilotSuggestions
- const hasContent = React.useMemo(() => Object.keys(sections).length > 0, [sections]);
+ // Check if sections exist AND have actual content (not just empty strings)
+ const hasContent = React.useMemo(() => {
+ const sectionKeys = Object.keys(sections);
+ if (sectionKeys.length === 0) return false;
+ // Check if at least one section has actual content
+ const sectionsWithContent = Object.values(sections).filter(c => c && c.trim().length > 0);
+ return sectionsWithContent.length > 0;
+ }, [sections]);
const {
suggestions,
setSuggestionsRef,
diff --git a/frontend/src/components/BlogWriter/BlogWriterUtils/PhaseContent.tsx b/frontend/src/components/BlogWriter/BlogWriterUtils/PhaseContent.tsx
index eea4ab29..5be20a86 100644
--- a/frontend/src/components/BlogWriter/BlogWriterUtils/PhaseContent.tsx
+++ b/frontend/src/components/BlogWriter/BlogWriterUtils/PhaseContent.tsx
@@ -122,6 +122,7 @@ export const PhaseContent: React.FC = ({
aiGeneratedTitles={aiGeneratedTitles}
onTitleSelect={onTitleSelect}
onCustomTitle={onCustomTitle}
+ research={research}
/>
= ({
// Store current page URL so we can redirect back after OAuth completes
// This MUST be stored before calling handleConnect to ensure it's available after redirect
// We ALWAYS override any existing redirect URL since we know the exact page we're on (Blog Writer)
- const currentUrl = window.location.href;
+ // Build the redirect URL to ensure it includes the phase (publish) and works with both localhost and ngrok
+ const currentPath = window.location.pathname;
+ const currentHash = window.location.hash || '#publish'; // Default to publish phase if no hash
+ const currentSearch = window.location.search;
+
+ // Determine the correct origin - if using ngrok, use ngrok origin; otherwise use current origin
+ // This ensures consistency between where OAuth starts and where callback happens
+ const NGROK_ORIGIN = 'https://littery-sonny-unscrutinisingly.ngrok-free.dev';
+ const isUsingNgrok = window.location.origin.includes('localhost') ||
+ window.location.origin.includes('127.0.0.1') ||
+ window.location.origin === NGROK_ORIGIN;
+ const redirectOrigin = isUsingNgrok ? NGROK_ORIGIN : window.location.origin;
+
+ // Build redirect URL with normalized origin
+ const redirectUrl = `${redirectOrigin}${currentPath}${currentHash}${currentSearch}`;
+
try {
- sessionStorage.setItem('wix_oauth_redirect', currentUrl);
- console.log('[WixConnectModal] Stored redirect URL (overriding any existing):', currentUrl);
+ // Always override any existing redirect URL when connecting from Blog Writer
+ sessionStorage.setItem('wix_oauth_redirect', redirectUrl);
+ console.log('[WixConnectModal] Stored redirect URL (overriding any existing):', {
+ redirectUrl,
+ currentOrigin: window.location.origin,
+ redirectOrigin,
+ isUsingNgrok
+ });
} catch (e) {
console.warn('[WixConnectModal] Failed to store redirect URL:', e);
}
diff --git a/frontend/src/components/BlogWriter/BlogWriterUtils/useSEOManager.ts b/frontend/src/components/BlogWriter/BlogWriterUtils/useSEOManager.ts
index 23ee2e93..63ae1489 100644
--- a/frontend/src/components/BlogWriter/BlogWriterUtils/useSEOManager.ts
+++ b/frontend/src/components/BlogWriter/BlogWriterUtils/useSEOManager.ts
@@ -1,6 +1,180 @@
import { useState, useRef, useEffect, useCallback } from 'react';
import { debug } from '../../../utils/debug';
import { blogWriterApi, BlogSEOActionableRecommendation } from '../../../services/blogWriterApi';
+import { blogWriterCache } from '../../../services/blogWriterCache';
+
+const registerContentKey = (map: Map, key: any, content?: string) => {
+ if (key === undefined || key === null) {
+ return;
+ }
+ const trimmed = String(key).trim();
+ if (!trimmed) {
+ return;
+ }
+ const safeContent = content !== undefined && content !== null ? String(content) : '';
+ map.set(trimmed, safeContent);
+ map.set(trimmed.toLowerCase(), safeContent);
+};
+
+const getIdCandidatesForSection = (section: any, index: number): string[] => {
+ const rawCandidates = [
+ section?.id,
+ section?.section_id,
+ section?.sectionId,
+ section?.sectionID,
+ section?.heading_id,
+ `section_${index + 1}`,
+ `Section ${index + 1}`,
+ `section${index + 1}`,
+ `s${index + 1}`,
+ `S${index + 1}`,
+ `${index + 1}`,
+ ];
+
+ const normalized = rawCandidates
+ .map((value) => (value === undefined || value === null ? '' : String(value).trim()))
+ .filter(Boolean);
+
+ return Array.from(new Set(normalized));
+};
+
+const buildExistingContentMap = (sectionsRecord: Record): Map => {
+ const map = new Map();
+ if (!sectionsRecord) {
+ return map;
+ }
+ Object.entries(sectionsRecord).forEach(([key, value]) => {
+ registerContentKey(map, key, value ?? '');
+ });
+ return map;
+};
+
+const buildResponseContentMaps = (responseSections: any[]): { byId: Map; byHeading: Map } => {
+ const byId = new Map();
+ const byHeading = new Map();
+
+ if (!responseSections) {
+ return { byId, byHeading };
+ }
+
+ responseSections.forEach((section, index) => {
+ if (!section) {
+ return;
+ }
+ const content = section?.content;
+ const normalizedContent = content !== undefined && content !== null ? String(content).trim() : '';
+ if (!normalizedContent) {
+ return;
+ }
+
+ registerContentKey(byId, section?.id, normalizedContent);
+ registerContentKey(byId, section?.section_id, normalizedContent);
+ registerContentKey(byId, section?.sectionId, normalizedContent);
+ registerContentKey(byId, section?.sectionID, normalizedContent);
+ registerContentKey(byId, `section_${index + 1}`, normalizedContent);
+ registerContentKey(byId, `Section ${index + 1}`, normalizedContent);
+ registerContentKey(byId, `section${index + 1}`, normalizedContent);
+ registerContentKey(byId, `s${index + 1}`, normalizedContent);
+ registerContentKey(byId, `S${index + 1}`, normalizedContent);
+ registerContentKey(byId, `${index + 1}`, normalizedContent);
+
+ const heading = section?.heading || section?.title;
+ if (heading) {
+ registerContentKey(byHeading, heading, normalizedContent);
+ }
+ });
+
+ return { byId, byHeading };
+};
+
+const getPrimaryKeyForOutlineSection = (outlineSection: any, index: number): string => {
+ const candidates = getIdCandidatesForSection(outlineSection, index);
+ if (candidates.length > 0) {
+ return candidates[0];
+ }
+ const fallbackHeading = outlineSection?.heading || outlineSection?.title;
+ if (fallbackHeading) {
+ const trimmed = String(fallbackHeading).trim();
+ if (trimmed) {
+ return trimmed;
+ }
+ }
+ return `section_${index + 1}`;
+};
+
+const resolveContentForOutlineSection = (
+ outlineSection: any,
+ index: number,
+ responseSections: any[],
+ responseById: Map,
+ responseByHeading: Map,
+ existingContentMap: Map
+): { content: string; matchedKey: string } => {
+ const idCandidates = getIdCandidatesForSection(outlineSection, index);
+
+ for (const candidate of idCandidates) {
+ if (responseById.has(candidate)) {
+ return { content: responseById.get(candidate) || '', matchedKey: candidate };
+ }
+ const lower = candidate.toLowerCase();
+ if (responseById.has(lower)) {
+ return { content: responseById.get(lower) || '', matchedKey: candidate };
+ }
+ }
+
+ const heading = outlineSection?.heading || outlineSection?.title;
+ if (heading) {
+ const headingKey = String(heading).trim();
+ if (headingKey) {
+ const lowerHeading = headingKey.toLowerCase();
+ if (responseByHeading.has(lowerHeading)) {
+ return { content: responseByHeading.get(lowerHeading) || '', matchedKey: headingKey };
+ }
+ if (responseByHeading.has(headingKey)) {
+ return { content: responseByHeading.get(headingKey) || '', matchedKey: headingKey };
+ }
+ }
+ }
+
+ const responseSection = responseSections?.[index];
+ if (responseSection?.content) {
+ const normalizedContent = String(responseSection.content).trim();
+ if (normalizedContent) {
+ return {
+ content: normalizedContent,
+ matchedKey: idCandidates[0] || getPrimaryKeyForOutlineSection(outlineSection, index),
+ };
+ }
+ }
+
+ for (const candidate of idCandidates) {
+ if (existingContentMap.has(candidate)) {
+ return { content: existingContentMap.get(candidate) || '', matchedKey: candidate };
+ }
+ const lower = candidate.toLowerCase();
+ if (existingContentMap.has(lower)) {
+ return { content: existingContentMap.get(lower) || '', matchedKey: candidate };
+ }
+ }
+
+ if (heading) {
+ const headingKey = String(heading).trim();
+ if (headingKey) {
+ const lowerHeading = headingKey.toLowerCase();
+ if (existingContentMap.has(lowerHeading)) {
+ return { content: existingContentMap.get(lowerHeading) || '', matchedKey: headingKey };
+ }
+ if (existingContentMap.has(headingKey)) {
+ return { content: existingContentMap.get(headingKey) || '', matchedKey: headingKey };
+ }
+ }
+ }
+
+ return {
+ content: '',
+ matchedKey: idCandidates[0] || getPrimaryKeyForOutlineSection(outlineSection, index),
+ };
+};
interface UseSEOManagerProps {
sections: Record;
@@ -47,8 +221,34 @@ export const useSEOManager = ({
// Helper: run same checks as analyzeSEO and open modal
const runSEOAnalysisDirect = useCallback((): string => {
const hasSections = !!sections && Object.keys(sections).length > 0;
+ // Check if sections have actual content (not just empty strings)
+ let sectionsWithContent = hasSections ? Object.values(sections).filter(c => c && c.trim().length > 0) : [];
+ let hasValidContent = sectionsWithContent.length > 0;
+
+ // If sections don't exist in state, check cache (similar to how content generation checks cache)
+ if (!hasValidContent && outline && outline.length > 0) {
+ try {
+ const outlineIds = outline.map(s => String(s.id));
+ const cachedContent = blogWriterCache.getCachedContent(outlineIds);
+ if (cachedContent && Object.keys(cachedContent).length > 0) {
+ sectionsWithContent = Object.values(cachedContent).filter(c => c && c.trim().length > 0);
+ hasValidContent = sectionsWithContent.length > 0;
+ if (hasValidContent) {
+ debug.log('[BlogWriter] Using cached content for SEO analysis', { sections: Object.keys(cachedContent).length });
+ // Update sections state with cached content
+ setSections(cachedContent);
+ }
+ }
+ } catch (e) {
+ debug.log('[BlogWriter] Error checking cache for SEO analysis', e);
+ }
+ }
+
const hasResearch = !!research && !!(research as any).keyword_analysis;
- if (!hasSections) return "No blog content available for SEO analysis. Please generate content first.";
+
+ if (!hasValidContent) {
+ return "No blog content available for SEO analysis. Please generate content first. Content generation may still be in progress - please wait for it to complete.";
+ }
if (!hasResearch) return "Research data is required for SEO analysis. Please run research first.";
// Prevent rapid re-opens
const now = Date.now();
@@ -69,7 +269,7 @@ export const useSEOManager = ({
debug.log('[BlogWriter] SEO modal opened (direct)');
}
return "Running SEO analysis of your blog content. This will analyze content structure, keyword optimization, readability, and provide actionable recommendations.";
- }, [sections, research, isSEOAnalysisModalOpen, contentConfirmed, setContentConfirmed]);
+ }, [sections, research, outline, isSEOAnalysisModalOpen, contentConfirmed, setContentConfirmed, setSections]);
const handleApplySeoRecommendations = useCallback(async (
recommendations: BlogSEOActionableRecommendation[]
@@ -78,11 +278,29 @@ export const useSEOManager = ({
throw new Error('An outline is required before applying recommendations.');
}
- const sectionPayload = outline.map((section) => ({
- id: section.id,
- heading: section.heading,
- content: sections[section.id] ?? '',
- }));
+ const existingContentMap = buildExistingContentMap(sections || {});
+ const emptyMap = new Map();
+
+ const sectionPayload = outline.map((section, index) => {
+ const existingMatch = resolveContentForOutlineSection(
+ section,
+ index,
+ [],
+ emptyMap,
+ emptyMap,
+ existingContentMap
+ );
+ const payloadContentRaw = existingMatch.content ?? sections?.[section?.id] ?? '';
+ const payloadContent = payloadContentRaw !== undefined && payloadContentRaw !== null ? String(payloadContentRaw) : '';
+ const rawIdentifier = section?.id || section?.section_id || section?.sectionId || section?.sectionID || `section_${index + 1}`;
+ const identifier = String(rawIdentifier).trim();
+
+ return {
+ id: identifier,
+ heading: section.heading,
+ content: payloadContent,
+ };
+ });
const response = await blogWriterApi.applySeoRecommendations({
title: selectedTitle || outline[0]?.heading || 'Untitled Blog',
@@ -100,43 +318,59 @@ export const useSEOManager = ({
throw new Error('Recommendation response did not include updated sections.');
}
- // Update sections - create new object reference to trigger React re-render
- const newSections: Record = {};
- response.sections.forEach((section) => {
- if (section.id && section.content) {
- newSections[section.id] = section.content;
- }
+ const { byId: responseById, byHeading: responseByHeading } = buildResponseContentMaps(response.sections);
+
+ const normalizedSections: Record = {};
+ const sectionKeysForCache: string[] = [];
+
+ outline.forEach((section, index) => {
+ const { content: resolvedContent, matchedKey } = resolveContentForOutlineSection(
+ section,
+ index,
+ response.sections,
+ responseById,
+ responseByHeading,
+ existingContentMap
+ );
+
+ const finalContent = (resolvedContent ?? '').trim();
+ const contentToUse = finalContent || '';
+ const primaryKey = getPrimaryKeyForOutlineSection(section, index);
+
+ normalizedSections[primaryKey] = contentToUse;
+ sectionKeysForCache.push(primaryKey);
});
-
- // Validate we have sections before updating
- if (Object.keys(newSections).length === 0) {
+
+ const uniqueSectionKeys = Array.from(new Set(sectionKeysForCache));
+
+ if (uniqueSectionKeys.length === 0) {
throw new Error('No valid sections received from SEO recommendations application.');
}
-
- // Validate sections have actual content
- const sectionsWithContent = Object.values(newSections).filter(c => c && c.trim().length > 0);
+
+ const sectionsWithContent = Object.values(normalizedSections).filter(c => c && c.trim().length > 0);
if (sectionsWithContent.length === 0) {
throw new Error('SEO recommendations resulted in empty sections. Please try again.');
}
-
- // Log detailed section info for debugging
- const sectionIds = Object.keys(newSections);
- const sectionSizes = sectionIds.map(id => ({ id, length: newSections[id]?.length || 0 }));
- debug.log('[BlogWriter] Applied SEO recommendations: sections updated', {
- sectionCount: sectionIds.length,
+
+ debug.log('[BlogWriter] Applied SEO recommendations: sections normalized', {
+ sectionCount: uniqueSectionKeys.length,
sectionsWithContent: sectionsWithContent.length,
- sectionIds: sectionIds,
- sectionSizes: sectionSizes,
- totalContentLength: Object.values(newSections).reduce((sum, c) => sum + (c?.length || 0), 0)
+ sectionKeys: uniqueSectionKeys,
+ totalContentLength: Object.values(normalizedSections).reduce((sum, c) => sum + (c?.length || 0), 0)
});
-
- // Update sections state
- setSections(newSections);
-
+
+ setSections(normalizedSections);
+
+ try {
+ blogWriterCache.cacheContent(normalizedSections, uniqueSectionKeys);
+ } catch (cacheError) {
+ debug.log('[BlogWriter] Failed to cache SEO-applied content', cacheError);
+ }
+
// Force a delay to ensure React processes the state update before proceeding
// This gives React time to re-render with new sections before phase navigation checks
await new Promise(resolve => setTimeout(resolve, 200));
-
+
setContinuityRefresh(Date.now());
setFlowAnalysisCompleted(false);
setFlowAnalysisResults(null);
@@ -154,7 +388,7 @@ export const useSEOManager = ({
// But we'll stay in SEO phase to show updated content
setSeoRecommendationsApplied(true);
debug.log('[BlogWriter] seoRecommendationsApplied set to true');
-
+
// Ensure we stay in SEO phase to show updated content
// Force navigation to SEO phase if we're not already there (safeguard)
if (currentPhase !== 'seo') {
@@ -163,7 +397,7 @@ export const useSEOManager = ({
} else {
debug.log('[BlogWriter] Already in SEO phase, staying to show updated content');
}
- }, [outline, sections, selectedTitle, research, setSections, setSelectedTitle, setContinuityRefresh, setFlowAnalysisCompleted, setFlowAnalysisResults, setSeoAnalysis, currentPhase, navigateToPhase]);
+ }, [outline, research, sections, selectedTitle, setSections, setContinuityRefresh, setFlowAnalysisCompleted, setFlowAnalysisResults, setSelectedTitle, setSeoAnalysis, setSeoRecommendationsApplied, currentPhase, navigateToPhase]);
// Handle SEO analysis completion
const handleSEOAnalysisComplete = useCallback((analysis: any) => {
diff --git a/frontend/src/components/BlogWriter/EnhancedOutlineEditor.tsx b/frontend/src/components/BlogWriter/EnhancedOutlineEditor.tsx
index aa20e22e..28ea97b8 100644
--- a/frontend/src/components/BlogWriter/EnhancedOutlineEditor.tsx
+++ b/frontend/src/components/BlogWriter/EnhancedOutlineEditor.tsx
@@ -1,5 +1,5 @@
import React, { useState } from 'react';
-import { BlogOutlineSection, SourceMappingStats, GroundingInsights, OptimizationResults, ResearchCoverage } from '../../services/blogWriterApi';
+import { BlogOutlineSection, SourceMappingStats, GroundingInsights, OptimizationResults, ResearchCoverage, blogWriterApi } from '../../services/blogWriterApi';
import EnhancedOutlineInsights from './EnhancedOutlineInsights';
import OutlineIntelligenceChips from './OutlineIntelligenceChips';
import ImageGeneratorModal from '../ImageGen/ImageGeneratorModal';
@@ -38,6 +38,9 @@ const EnhancedOutlineEditor: React.FC = ({
key_points: '',
target_words: 300
});
+ const [showRefineModal, setShowRefineModal] = useState(false);
+ const [refineFeedback, setRefineFeedback] = useState('');
+ const [isRefining, setIsRefining] = useState(false);
const toggleExpanded = (sectionId: string) => {
const newExpanded = new Set(expandedSections);
@@ -89,12 +92,53 @@ const EnhancedOutlineEditor: React.FC = ({
}
};
+ const handleRefineOutline = async () => {
+ if (!refineFeedback.trim()) {
+ alert('Please provide feedback on how you would like to refine the outline.');
+ return;
+ }
+
+ setIsRefining(true);
+ try {
+ // Use the parent's onRefine callback which handles the API call and state update
+ // The callback expects: operation, sectionId, payload
+ await onRefine('refine', undefined, { feedback: refineFeedback.trim() });
+
+ setRefineFeedback('');
+ setShowRefineModal(false);
+
+ // Show success message
+ const toast = document.createElement('div');
+ toast.style.cssText = `
+ position: fixed;
+ top: 20px;
+ right: 20px;
+ padding: 16px 24px;
+ border-radius: 8px;
+ background-color: #4caf50;
+ color: white;
+ font-weight: 500;
+ z-index: 10000;
+ box-shadow: 0 4px 12px rgba(0, 0, 0, 0.15);
+ `;
+ toast.textContent = '✅ Outline refined successfully!';
+ document.body.appendChild(toast);
+ setTimeout(() => document.body.removeChild(toast), 3000);
+ } catch (error) {
+ console.error('Failed to refine outline:', error);
+ alert('Failed to refine outline. Please try again.');
+ } finally {
+ setIsRefining(false);
+ }
+ };
+
const getTotalWords = () => {
return outline.reduce((total, section) => total + (section.target_words || 0), 0);
};
return (
+ <>