Upload 15 files

ai_recommendation_engine.py

@@ -2289,13 +2289,31 @@ class AIRecommendationEngine:
                 urgency_level, recommendations, email_type
             )
             
-            # Send email
+            # For preview mode, don't actually send the email
+            if recipient_email == '[email protected]':
+                return {
+                    'success': True,
+                    'recipient': recipient_email,
+                    'subject': email_content['subject'],
+                    'html_content': email_content['html_content'],
+                    'text_content': email_content['text_content'],
+                    'recommendations_count': len(recommendations),
+                    'personalization': {
+                        'personality_type': personality_type,
+                        'buying_motivation': buying_motivation,
+                        'urgency_level': urgency_level
+                    }
+                }
+            
+            # Send email for real recipients
             success = self.send_email(recipient_email, email_content)
             
             return {
                 'success': success,
                 'recipient': recipient_email,
                 'subject': email_content['subject'],
+                'html_content': email_content['html_content'],
+                'text_content': email_content['text_content'],
                 'recommendations_count': len(recommendations),
                 'personalization': {
                     'personality_type': personality_type,

api_service_enhanced.py

@@ -1793,19 +1793,25 @@ class EnhancedLeadQualificationAPI:
                 # Generate AI insights
                 ai_insights = ai_engine.analyze_user_behavior_with_ai(analysis_data)
                 
-                # Ensure ChromaDB has properties before generating recommendations
-                if hasattr(ai_engine, 'properties_collection') and ai_engine.properties_collection:
-                    try:
+                # Ensure ChromaDB is properly initialized and has properties
+                if not hasattr(ai_engine, 'properties_collection') or ai_engine.properties_collection is None:
+                    logger.info("🚀 ChromaDB not initialized, initializing...")
+                    ai_engine.initialize_chromadb()
+                
+                # Check if ChromaDB has properties
+                try:
+                    if ai_engine.properties_collection:
                         collection_count = ai_engine.properties_collection.count()
+                        logger.info(f"📊 ChromaDB has {collection_count} properties")
                         if collection_count == 0:
                             logger.info("🚀 ChromaDB is empty, auto-fetching properties...")
                             ai_engine.auto_fetch_and_store_properties()
-                    except Exception as count_error:
-                        logger.warning(f"⚠️ Could not check ChromaDB count: {count_error}")
+                    else:
+                        logger.warning("⚠️ ChromaDB collection is None, auto-fetching properties...")
                         ai_engine.auto_fetch_and_store_properties()
-                else:
-                    logger.warning("⚠️ ChromaDB not initialized, auto-initializing...")
-                    ai_engine.initialize_chromadb()
+                except Exception as count_error:
+                    logger.warning(f"⚠️ Could not check ChromaDB count: {count_error}")
+                    logger.info("🚀 Auto-fetching properties as fallback...")
                     ai_engine.auto_fetch_and_store_properties()
                 
                 # Email types to generate
@@ -1853,18 +1859,24 @@ class EnhancedLeadQualificationAPI:
                         if email_content.get('success'):
                             email_previews.append({
                                 'email_type': email_type,
-                                'subject': self._get_custom_subject(email_type, customer_id, ai_insights),
+                                'subject': email_content.get('subject', self._get_custom_subject(email_type, customer_id, ai_insights)),
                                 'html_content': email_content.get('html_content', ''),
                                 'text_content': email_content.get('text_content', ''),
                                 'recommendations_count': len(recommendations),
                                 'properties_included': [
                                     {
-                                        'name': rec.get('property_name', 'Property'),
-                                        'price': rec.get('price', 0),
-                                        'type': rec.get('property_type', 'N/A'),
-                                        'score': rec.get('ai_score', 0)
+                                        'name': rec.get('property_name', rec.get('name', rec.get('title', 'Property'))),
+                                        'price': rec.get('price', rec.get('marketValue', rec.get('amount', 0))),
+                                        'type': rec.get('property_type', rec.get('type', rec.get('propertyTypeName', 'N/A'))),
+                                        'score': rec.get('ai_score', rec.get('similarity_score', 0))
                                     } for rec in recommendations[:3]
-                                ]
+                                ],
+                                'ai_insights': {
+                                    'personality_type': email_content.get('personalization', {}).get('personality_type', 'N/A'),
+                                    'decision_style': ai_insights.get('recommendation_strategy', 'N/A'),
+                                    'urgency_level': email_content.get('personalization', {}).get('urgency_level', 'N/A'),
+                                    'peak_activity': ai_insights.get('peak_time', 'N/A')
+                                }
                             })
                         else:
                             email_previews.append({

templates/ai_lead_analysis.html

@@ -1560,9 +1560,26 @@
                                     </div>
                                     <div class="mt-3">
                                         <h6>Email Content Preview:</h6>
-                                        <div class="alert alert-light">
-                                            <small>This email would be sent to the customer based on their tracking data and AI analysis. The content is personalized based on their viewing behavior, preferences, and engagement patterns.</small>
-                                        </div>
+                                        ${result.html_content ? `
+                                            <div class="email-preview-container" style="max-height: 400px; overflow-y: auto; border: 1px solid #ddd; border-radius: 8px; padding: 15px; background: white;">
+                                                <div class="email-preview-header mb-3">
+                                                    <strong>Subject:</strong> ${result.subject || 'N/A'}<br>
+                                                    <strong>Properties:</strong> ${result.recommendations_count || 0} recommendations<br>
+                                                    <strong>AI Insights:</strong> ${result.ai_insights ? `
+                                                        Personality: ${result.ai_insights.personality_type || 'N/A'} | 
+                                                        Urgency: ${result.ai_insights.urgency_level || 'N/A'} | 
+                                                        Peak Time: ${result.ai_insights.peak_activity || 'N/A'}
+                                                    ` : 'N/A'}
+                                                </div>
+                                                <div class="email-content-preview">
+                                                    ${result.html_content}
+                                                </div>
+                                            </div>
+                                        ` : `
+                                            <div class="alert alert-light">
+                                                <small>This email would be sent to the customer based on their tracking data and AI analysis. The content is personalized based on their viewing behavior, preferences, and engagement patterns.</small>
+                                            </div>
+                                        `}
                                     </div>
                                 ` : `
                                     <div class="alert alert-danger">

templates/perfect_ai_dashboard.html

@@ -779,9 +779,26 @@
                                     </div>
                                     <div class="mt-3">
                                         <h6>Email Content Preview:</h6>
-                                        <div class="alert alert-light">
-                                            <small>This email would be sent to the customer based on their tracking data and AI analysis. The content is personalized based on their viewing behavior, preferences, and engagement patterns.</small>
-                                        </div>
+                                        ${result.html_content ? `
+                                            <div class="email-preview-container" style="max-height: 400px; overflow-y: auto; border: 1px solid #ddd; border-radius: 8px; padding: 15px; background: white;">
+                                                <div class="email-preview-header mb-3">
+                                                    <strong>Subject:</strong> ${result.subject || 'N/A'}<br>
+                                                    <strong>Properties:</strong> ${result.recommendations_count || 0} recommendations<br>
+                                                    <strong>AI Insights:</strong> ${result.ai_insights ? `
+                                                        Personality: ${result.ai_insights.personality_type || 'N/A'} | 
+                                                        Urgency: ${result.ai_insights.urgency_level || 'N/A'} | 
+                                                        Peak Time: ${result.ai_insights.peak_activity || 'N/A'}
+                                                    ` : 'N/A'}
+                                                </div>
+                                                <div class="email-content-preview">
+                                                    ${result.html_content}
+                                                </div>
+                                            </div>
+                                        ` : `
+                                            <div class="alert alert-light">
+                                                <small>This email would be sent to the customer based on their tracking data and AI analysis. The content is personalized based on their viewing behavior, preferences, and engagement patterns.</small>
+                                            </div>
+                                        `}
                                     </div>
                                 ` : `
                                     <div class="alert alert-danger">

templates/unified_ai_dashboard.html

@@ -778,9 +778,26 @@
                                     </div>
                                     <div class="mt-3">
                                         <h6>Email Content Preview:</h6>
-                                        <div class="alert alert-light">
-                                            <small>This email would be sent to the customer based on their tracking data and AI analysis. The content is personalized based on their viewing behavior, preferences, and engagement patterns.</small>
-                                        </div>
+                                        ${result.html_content ? `
+                                            <div class="email-preview-container" style="max-height: 400px; overflow-y: auto; border: 1px solid #ddd; border-radius: 8px; padding: 15px; background: white;">
+                                                <div class="email-preview-header mb-3">
+                                                    <strong>Subject:</strong> ${result.subject || 'N/A'}<br>
+                                                    <strong>Properties:</strong> ${result.recommendations_count || 0} recommendations<br>
+                                                    <strong>AI Insights:</strong> ${result.ai_insights ? `
+                                                        Personality: ${result.ai_insights.personality_type || 'N/A'} | 
+                                                        Urgency: ${result.ai_insights.urgency_level || 'N/A'} | 
+                                                        Peak Time: ${result.ai_insights.peak_activity || 'N/A'}
+                                                    ` : 'N/A'}
+                                                </div>
+                                                <div class="email-content-preview">
+                                                    ${result.html_content}
+                                                </div>
+                                            </div>
+                                        ` : `
+                                            <div class="alert alert-light">
+                                                <small>This email would be sent to the customer based on their tracking data and AI analysis. The content is personalized based on their viewing behavior, preferences, and engagement patterns.</small>
+                                            </div>
+                                        `}
                                     </div>
                                 ` : `
                                     <div class="alert alert-danger">