feat(podcast): add pre-estimate endpoint, enhance cost estimator with multi-model support, cleanup alpha pricing seeding

- Add POST /podcast/pre-estimate endpoint for cost estimation before analysis
- Enhance cost_estimator.py with multi-model support (gemini, audio, voice clone, image, video)
- Add detailed cost breakdown (llm, audio, media costs + per-phase breakdown)
- Remove redundant pricing seeding from init_alpha_subscription_tiers.py
- Add SSOT pricing via PricingService.initialize_default_pricing()
- Update TopicUrlInput tooltip to show estimate details
- Add debug logging for pricing seeding and pre-estimate
- Clean up verbose podcast mode debug logs in app.py

backend/services/user_data_service.py

@@ -4,6 +4,7 @@ Handles fetching user data from the onboarding database.
 """
 
 from typing import Optional, List, Dict, Any
+from datetime import datetime
 from sqlalchemy.orm import Session
 from loguru import logger
 
@@ -92,5 +93,88 @@ class UserDataService:
             return integrated_data.get('website_analysis')
             
         except Exception as e:
-            logger.error(f"Error getting user website analysis: {str(e)}")
+            logger.error(f"Error getting user website analysis: {e}")
+            return None 
+    
+    def save_website_extraction(self, user_id: str, extraction_data: Dict[str, Any]) -> bool:
+        """
+        Save website extraction data for future use.
+        
+        Args:
+            user_id: The user ID
+            extraction_data: Website extraction data (title, summary, highlights, url, subpages)
+            
+        Returns:
+            True if saved successfully
+        """
+        try:
+            # Clean data - remove images/favicon
+            clean_data = {
+                k: v for k, v in extraction_data.items()
+                if k not in ('image', 'favicon')
+            }
+            clean_data['saved_at'] = datetime.now().isoformat()
+            
+            # Find or create user session for storing
+            onboarding = self.db.query(OnboardingSession).filter(
+                OnboardingSession.user_id == user_id
+            ).first()
+            
+            if not onboarding:
+                # Create new session if not exists
+                onboarding = OnboardingSession(user_id=user_id)
+                self.db.add(onboarding)
+            
+            # Try to update website_analysis field
+            # The field might be JSON in the model
+            try:
+                existing = onboarding.website_analysis
+                if isinstance(existing, dict):
+                    existing.update(clean_data)
+                    onboarding.website_analysis = existing
+                else:
+                    onboarding.website_analysis = clean_data
+            except Exception as ex:
+                logger.warning(f"Could not update website_analysis: {ex}")
+                onboarding.website_analysis = clean_data
+            
+            self.db.commit()
+            logger.info(f"Saved website extraction for user {user_id}")
+            return True
+            
+        except Exception as e:
+            logger.error(f"Error saving website extraction: {str(e)}")
+            self.db.rollback()
+            return False
+    
+    def get_website_extraction(self, user_id: str) -> Optional[Dict[str, Any]]:
+        """
+        Get saved website extraction data.
+        
+        Args:
+            user_id: The user ID
+            
+        Returns:
+            Website extraction data or None
+        """
+        try:
+            onboarding = self.db.query(OnboardingSession).filter(
+                OnboardingSession.user_id == user_id
+            ).first()
+            
+            if not onboarding:
+                return None
+            
+            extraction = onboarding.website_analysis
+            if isinstance(extraction, dict):
+                # Return clean data without internal fields
+                return {
+                    k: v for k, v in extraction.items()
+                    if k not in ('saved_at', 'full_analysis', 'analysis_status')
+                }
+            
+            return None
+            
+        except Exception as e:
+            logger.error(f"Error getting website extraction: {str(e)}")
             return None