Update app.py

app.py

@@ -114,30 +114,165 @@ BREED_LIFESPAN = {
     "wire-haired fox terrier": 13.5, "yorkshire terrier": 13.3
 }
 
-# 4. Questionnaire
-QUESTIONNAIRE = [
-    {"domain": "Mobility", "questions": [
-        "Does your dog have difficulty rising from lying down?",
-        "Does your dog hesitate before jumping up or climbing stairs?"
-    ]},
-    {"domain": "Energy", "questions": [
-        "Does your dog tire quickly during walks or play?",
-        "Has your dog's overall activity level decreased recently?"
-    ]},
-    {"domain": "Physical Health", "questions": [
-        "Does your dog scratch or lick their skin frequently?",
-        "Have you noticed changes in appetite or weight?"
-    ]},
-    {"domain": "Cognitive Function", "questions": [
-        "Does your dog get lost in familiar rooms or areas?",
-        "Does your dog stare blankly at walls or into space?"
-    ]},
-    {"domain": "Social Behavior", "questions": [
-        "Has your dog's interest in play or interaction declined?",
-        "Does your dog avoid interaction with family members?"
-    ]}
-]
-SCALE = ["0 (Never)", "1 (Rarely)", "2 (Sometimes)", "3 (Often)", "4 (Frequently)", "5 (Always)"]
+# 4. VetMetrica HRQOL Framework
+HRQOL_QUESTIONNAIRE = {
+    "vitality": {
+        "title": "🔋 Vitality & Energy",
+        "questions": [
+            {
+                "id": "vitality_energy",
+                "text": "How would you rate your dog's energy level over the past week?",
+                "options": [
+                    "Excellent - Very energetic, eager for activities",
+                    "Very Good - Generally energetic with occasional rest",
+                    "Good - Moderate energy, participates willingly",
+                    "Fair - Lower energy, needs encouragement",
+                    "Poor - Very low energy, reluctant to participate"
+                ]
+            },
+            {
+                "id": "vitality_play",
+                "text": "How often does your dog seek out play or interaction?",
+                "options": [
+                    "Always seeks play/interaction",
+                    "Often seeks play/interaction",
+                    "Sometimes seeks play/interaction",
+                    "Rarely seeks play/interaction",
+                    "Never seeks play/interaction"
+                ]
+            },
+            {
+                "id": "vitality_response",
+                "text": "How quickly does your dog respond to exciting stimuli (treats, walks, visitors)?",
+                "options": [
+                    "Immediate enthusiastic response",
+                    "Quick positive response",
+                    "Moderate response time",
+                    "Slow or delayed response",
+                    "No response or negative reaction"
+                ]
+            }
+        ],
+        "weight": 0.25
+    },
+    "comfort": {
+        "title": "😌 Comfort & Pain Management",
+        "questions": [
+            {
+                "id": "comfort_activities",
+                "text": "How comfortable does your dog appear during normal activities?",
+                "options": [
+                    "Completely comfortable during all activities",
+                    "Mostly comfortable with minor adjustments",
+                    "Some discomfort during certain activities",
+                    "Frequently uncomfortable, avoids some activities",
+                    "Severe discomfort, avoids most activities"
+                ]
+            },
+            {
+                "id": "comfort_pain_frequency",
+                "text": "How often do you notice signs of pain or discomfort?",
+                "options": [
+                    "Never shows pain signs",
+                    "Rarely shows pain signs (< 1 day/week)",
+                    "Sometimes shows pain signs (2-3 days/week)",
+                    "Often shows pain signs (4-5 days/week)",
+                    "Always shows pain signs (daily)"
+                ]
+            },
+            {
+                "id": "comfort_impact",
+                "text": "How does your dog's comfort level affect daily activities?",
+                "options": [
+                    "No impact on daily activities",
+                    "Minimal impact on daily activities",
+                    "Moderate impact, some activities modified",
+                    "Significant impact, many activities avoided",
+                    "Severe impact, most activities impossible"
+                ]
+            }
+        ],
+        "weight": 0.25
+    },
+    "emotional_wellbeing": {
+        "title": "😊 Emotional Wellbeing",
+        "questions": [
+            {
+                "id": "emotion_mood",
+                "text": "How would you describe your dog's overall mood?",
+                "options": [
+                    "Very positive - happy, content, enthusiastic",
+                    "Mostly positive - generally cheerful",
+                    "Neutral - neither particularly happy nor sad",
+                    "Mostly negative - seems subdued or withdrawn",
+                    "Very negative - appears depressed or distressed"
+                ]
+            },
+            {
+                "id": "emotion_anxiety",
+                "text": "How often does your dog show signs of anxiety or stress?",
+                "options": [
+                    "Never shows anxiety/stress",
+                    "Rarely shows anxiety/stress",
+                    "Sometimes shows anxiety/stress",
+                    "Often shows anxiety/stress",
+                    "Constantly shows anxiety/stress"
+                ]
+            },
+            {
+                "id": "emotion_engagement",
+                "text": "How engaged is your dog with family activities?",
+                "options": [
+                    "Highly engaged, initiates family interactions",
+                    "Well engaged, participates enthusiastically",
+                    "Moderately engaged, participates when invited",
+                    "Minimally engaged, needs encouragement",
+                    "Not engaged, avoids family activities"
+                ]
+            }
+        ],
+        "weight": 0.25
+    },
+    "alertness": {
+        "title": "🧠 Alertness & Cognition",
+        "questions": [
+            {
+                "id": "alert_awareness",
+                "text": "How alert and aware does your dog seem?",
+                "options": [
+                    "Highly alert, notices everything immediately",
+                    "Alert, notices most things quickly",
+                    "Moderately alert, notices things with some delay",
+                    "Slightly alert, slow to notice surroundings",
+                    "Not alert, seems confused or disoriented"
+                ]
+            },
+            {
+                "id": "alert_commands",
+                "text": "How well does your dog respond to commands or their name?",
+                "options": [
+                    "Responds immediately to name/commands",
+                    "Usually responds quickly to name/commands",
+                    "Sometimes responds, may need repetition",
+                    "Often doesn't respond, needs multiple attempts",
+                    "Rarely or never responds to name/commands"
+                ]
+            },
+            {
+                "id": "alert_focus",
+                "text": "How focused is your dog during training or play?",
+                "options": [
+                    "Highly focused, maintains attention easily",
+                    "Good focus, occasional distraction",
+                    "Moderate focus, some difficulty concentrating",
+                    "Poor focus, easily distracted",
+                    "No focus, cannot maintain attention"
+                ]
+            }
+        ],
+        "weight": 0.25
+    }
+}
 
 def predict_biological_age(img: Image.Image, breed: str) -> int:
     avg = BREED_LIFESPAN.get(breed.lower(), 12)
@@ -216,6 +351,7 @@ def analyze_video_gait(video_path):
         indices = np.linspace(0, total-1, min(15, total), dtype=int)
         health_scores = []
         movement_scores = []
+        vitality_scores = []
         
         for i in indices:
             cap.set(cv2.CAP_PROP_POS_FRAMES, i)
@@ -233,7 +369,14 @@ def analyze_video_gait(video_path):
             inputs = clip_processor(text=movement_prompts, images=img, return_tensors="pt", padding=True).to(device)
             with torch.no_grad():
                 movement_logits = clip_model(**inputs).logits_per_image.softmax(-1)[0].cpu().numpy()
-            movement_scores.append(float(movement_logits[0]))  # Normal movement score
+            movement_scores.append(float(movement_logits[0]))
+            
+            # Vitality assessment
+            vitality_prompts = ["energetic active dog", "lethargic tired dog", "alert playful dog"]
+            inputs = clip_processor(text=vitality_prompts, images=img, return_tensors="pt", padding=True).to(device)
+            with torch.no_grad():
+                vitality_logits = clip_model(**inputs).logits_per_image.softmax(-1)[0].cpu().numpy()
+            vitality_scores.append(float(vitality_logits[0] + vitality_logits[2]))
         
         cap.release()
         
@@ -242,202 +385,364 @@ def analyze_video_gait(video_path):
         
         return {
             "duration_sec": round(total/fps, 1),
-            "avg_health_confidence": float(np.mean(health_scores)),
-            "avg_movement_score": float(np.mean(movement_scores)),
+            "mobility_score": float(np.mean(movement_scores)) * 100,
+            "comfort_score": float(np.mean(health_scores)) * 100,
+            "vitality_score": float(np.mean(vitality_scores)) * 100,
             "frames_analyzed": len(health_scores),
-            "gait_assessment": "Normal" if np.mean(movement_scores) > 0.5 else "Concerning"
+            "mobility_assessment": "Normal gait pattern" if np.mean(movement_scores) > 0.6 else "Mobility concerns detected",
+            "comfort_assessment": "No obvious discomfort" if np.mean(health_scores) > 0.7 else "Possible discomfort signs",
+            "vitality_assessment": "Good energy level" if np.mean(vitality_scores) > 0.6 else "Low energy observed"
         }
     except Exception as e:
         return None
 
-def compute_healthspan_score(answers):
-    if not answers or all(a is None or a == "" for a in answers):
-        return None
+def score_from_response(response, score_mapping):
+    """Extract numeric score from text response"""
+    if not response:
+        return 50
+    for key, value in score_mapping.items():
+        if key.lower() in response.lower():
+            return value
+    return 50
+
+def calculate_hrqol_scores(hrqol_responses):
+    """Convert VetMetrica-style responses to 0-100 domain scores"""
+    
+    score_mapping = {
+        "excellent": 100, "very good": 80, "good": 60, "fair": 40, "poor": 20,
+        "always": 100, "often": 80, "sometimes": 60, "rarely": 40, "never": 20,
+        "immediate": 100, "quick": 80, "moderate": 60, "slow": 40, "no response": 20,
+        "completely": 100, "mostly": 80, "some": 60, "frequently": 40, "severe": 20,
+        "very positive": 100, "mostly positive": 80, "neutral": 60, "mostly negative": 40, "very negative": 20,
+        "highly": 100, "well": 80, "moderately": 60, "minimally": 40, "not": 20
+    }
     
     domain_scores = {}
-    idx = 0
-    total_score = 0
     
-    for section in QUESTIONNAIRE:
-        n = len(section["questions"])
-        try:
-            vals = []
-            for a in answers[idx:idx+n]:
-                if a is None or a == "":
-                    vals.append(0)
-                else:
-                    # Extract numeric value from scale (e.g., "3 (Often)" -> 3)
-                    vals.append(int(a.split()[0]))
-            idx += n
-            domain_avg = sum(vals) / len(vals)
-            domain_scores[section["domain"]] = round(domain_avg, 2)
-            total_score += domain_avg
-        except (ValueError, TypeError):
-            domain_scores[section["domain"]] = 0.0
-    
-    # Calculate overall healthspan score (0-100, lower is better)
-    overall_healthspan = round((total_score / len(QUESTIONNAIRE)) * 20, 1)  # Convert to 0-100 scale
-    
-    return {
-        "domain_scores": domain_scores,
-        "overall_healthspan_score": overall_healthspan,
-        "healthspan_grade": get_healthspan_grade(overall_healthspan)
-    }
+    # Vitality Domain
+    vitality_scores = [
+        score_from_response(hrqol_responses.get("vitality_energy", ""), score_mapping),
+        score_from_response(hrqol_responses.get("vitality_play", ""), score_mapping),
+        score_from_response(hrqol_responses.get("vitality_response", ""), score_mapping)
+    ]
+    domain_scores["vitality"] = np.mean(vitality_scores)
+    
+    # Comfort Domain (invert pain frequency)
+    comfort_scores = [
+        score_from_response(hrqol_responses.get("comfort_activities", ""), score_mapping),
+        100 - score_from_response(hrqol_responses.get("comfort_pain_frequency", ""), score_mapping),
+        score_from_response(hrqol_responses.get("comfort_impact", ""), score_mapping)
+    ]
+    domain_scores["comfort"] = max(0, np.mean(comfort_scores))
+    
+    # Emotional Wellbeing Domain (invert anxiety)
+    emotion_scores = [
+        score_from_response(hrqol_responses.get("emotion_mood", ""), score_mapping),
+        100 - score_from_response(hrqol_responses.get("emotion_anxiety", ""), score_mapping),
+        score_from_response(hrqol_responses.get("emotion_engagement", ""), score_mapping)
+    ]
+    domain_scores["emotional_wellbeing"] = max(0, np.mean(emotion_scores))
+    
+    # Alertness Domain
+    alertness_scores = [
+        score_from_response(hrqol_responses.get("alert_awareness", ""), score_mapping),
+        score_from_response(hrqol_responses.get("alert_commands", ""), score_mapping),
+        score_from_response(hrqol_responses.get("alert_focus", ""), score_mapping)
+    ]
+    domain_scores["alertness"] = np.mean(alertness_scores)
+    
+    return domain_scores
+
+def get_score_color(score):
+    """Return color based on score"""
+    if score >= 80:
+        return "#4CAF50"  # Green
+    elif score >= 60:
+        return "#FFC107"  # Yellow
+    elif score >= 40:
+        return "#FF9800"  # Orange
+    else:
+        return "#F44336"  # Red
 
 def get_healthspan_grade(score):
-    if score <= 20:
-        return "Excellent (A)"
-    elif score <= 40:
+    if score >= 85:
+        return "Excellent (A+)"
+    elif score >= 75:
+        return "Very Good (A)"
+    elif score >= 65:
         return "Good (B)"
-    elif score <= 60:
+    elif score >= 55:
         return "Fair (C)"
-    elif score <= 80:
+    elif score >= 45:
         return "Poor (D)"
     else:
         return "Critical (F)"
 
-def comprehensive_analysis(image, video, breed_override, chronological_age, *questionnaire_answers):
+def comprehensive_healthspan_analysis(image, video, breed, age, *hrqol_responses):
+    """Combine video analysis with HRQOL assessment"""
+    
     if image is None and video is None:
         return "❌ **Error**: Please provide either an image or video for analysis."
     
     # Check if questionnaire is completed
-    if not questionnaire_answers or all(a is None or a == "" for a in questionnaire_answers):
-        return "❌ **Error**: Please complete the healthspan questionnaire before analysis."
+    if not hrqol_responses or all(not r for r in hrqol_responses):
+        return "❌ **Error**: Please complete the HRQOL questionnaire before analysis."
+    
+    # Build HRQOL responses dictionary
+    response_keys = []
+    for domain_key, domain_data in HRQOL_QUESTIONNAIRE.items():
+        for question in domain_data["questions"]:
+            response_keys.append(question["id"])
+    
+    hrqol_dict = {key: hrqol_responses[i] if i < len(hrqol_responses) else "" 
+                  for i, key in enumerate(response_keys)}
+    
+    # Calculate HRQOL scores
+    hrqol_scores = calculate_hrqol_scores(hrqol_dict)
     
-    results = []
-    results.append("# 🐕 **Comprehensive Dog Health & Age Analysis Report**\n")
+    # Video analysis (if available)
+    video_features = {}
+    if video:
+        video_features = analyze_video_gait(video) or {}
     
-    # Image Analysis
-    if image is not None:
+    # Image analysis (if available)
+    breed_info = None
+    bio_age = None
+    health_aspects = {}
+    
+    if image:
         try:
-            breed, breed_conf, health_aspects = classify_breed_and_health(image, breed_override)
-            medical_assessment, medical_conf = analyze_medical_image(image)
-            bio_age = predict_biological_age(image, breed)
-            
-            results.append("## 📸 **Image Analysis**")
-            results.append(f"**Detected Breed**: {breed} ({breed_conf:.1%} confidence)")
-            results.append(f"**Medical Assessment**: {medical_assessment} ({medical_conf:.1%} confidence)")
-            results.append(f"**Estimated Biological Age**: {bio_age} years")
+            detected_breed, breed_conf, health_aspects = classify_breed_and_health(image, breed)
+            bio_age = predict_biological_age(image, detected_breed)
+            breed_info = {
+                "breed": detected_breed,
+                "confidence": breed_conf,
+                "bio_age": bio_age
+            }
+        except Exception as e:
+            pass
+    
+    # Calculate Composite Healthspan Score
+    video_weight = 0.4 if video_features else 0.0
+    hrqol_weight = 0.6
+    
+    if video_features:
+        video_score = (
+            video_features.get("mobility_score", 70) * 0.15 +
+            video_features.get("comfort_score", 70) * 0.10 +
+            video_features.get("vitality_score", 70) * 0.15
+        )
+    else:
+        video_score = 0
+        hrqol_weight = 1.0
+    
+    hrqol_composite = (
+        hrqol_scores["vitality"] * 0.25 +
+        hrqol_scores["comfort"] * 0.25 +
+        hrqol_scores["emotional_wellbeing"] * 0.25 +
+        hrqol_scores["alertness"] * 0.25
+    )
+    
+    final_healthspan_score = (video_score * video_weight) + (hrqol_composite * hrqol_weight)
+    final_healthspan_score = min(100, max(0, final_healthspan_score))
+    
+    # Generate comprehensive report
+    report_html = f"""
+    <div style="font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; max-width: 1000px; margin: 0 auto;">
+        <div style="background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); color: white; padding: 30px; border-radius: 15px; margin: 20px 0; text-align: center;">
+            <h2 style="margin: 0; font-size: 2em;">🏥 Comprehensive Healthspan Assessment</h2>
+            <div style="font-size: 3em; font-weight: bold; margin: 15px 0;">{final_healthspan_score:.1f}/100</div>
+            <div style="font-size: 1.2em;">{get_healthspan_grade(final_healthspan_score)}</div>
+        </div>
+        
+        <div style="display: grid; grid-template-columns: repeat(auto-fit, minmax(240px, 1fr)); gap: 20px; margin: 30px 0;">
+            <div style="border: 2px solid #e0e0e0; padding: 20px; border-radius: 12px; background: #f8f9fa;">
+                <h4 style="margin: 0 0 15px 0; color: #667eea;">🔋 Vitality</h4>
+                <div style="background: #e9ecef; height: 8px; border-radius: 4px; margin: 10px 0;">
+                    <div style="background: {get_score_color(hrqol_scores['vitality'])}; height: 100%; width: {hrqol_scores['vitality']}%; border-radius: 4px; transition: width 0.3s ease;"></div>
+                </div>
+                <div style="font-size: 1.1em; font-weight: bold;">{hrqol_scores['vitality']:.1f}/100</div>
+            </div>
             
-            if chronological_age and chronological_age > 0:
-                pace = bio_age / chronological_age
-                results.append(f"**Chronological Age**: {chronological_age} years")
-                results.append(f"**Aging Pace**: {pace:.2f}× {'(Accelerated)' if pace > 1.2 else '(Normal)' if pace > 0.8 else '(Slow)'}")
+            <div style="border: 2px solid #e0e0e0; padding: 20px; border-radius: 12px; background: #f8f9fa;">
+                <h4 style="margin: 0 0 15px 0; color: #667eea;">😌 Comfort</h4>
+                <div style="background: #e9ecef; height: 8px; border-radius: 4px; margin: 10px 0;">
+                    <div style="background: {get_score_color(hrqol_scores['comfort'])}; height: 100%; width: {hrqol_scores['comfort']}%; border-radius: 4px; transition: width 0.3s ease;"></div>
+                </div>
+                <div style="font-size: 1.1em; font-weight: bold;">{hrqol_scores['comfort']:.1f}/100</div>
+            </div>
             
-            results.append("\n### **Physical Health Aspects**")
-            for aspect, data in health_aspects.items():
-                status = "✅" if "healthy" in data["assessment"].lower() or "bright" in data["assessment"].lower() or "clean" in data["assessment"].lower() or "ideal" in data["assessment"].lower() else "⚠️"
-                results.append(f"{status} **{aspect}**: {data['assessment']} ({data['confidence']:.1%})")
+            <div style="border: 2px solid #e0e0e0; padding: 20px; border-radius: 12px; background: #f8f9fa;">
+                <h4 style="margin: 0 0 15px 0; color: #667eea;">😊 Emotional</h4>
+                <div style="background: #e9ecef; height: 8px; border-radius: 4px; margin: 10px 0;">
+                    <div style="background: {get_score_color(hrqol_scores['emotional_wellbeing'])}; height: 100%; width: {hrqol_scores['emotional_wellbeing']}%; border-radius: 4px; transition: width 0.3s ease;"></div>
+                </div>
+                <div style="font-size: 1.1em; font-weight: bold;">{hrqol_scores['emotional_wellbeing']:.1f}/100</div>
+            </div>
             
-        except Exception as e:
-            results.append(f"❌ **Image Analysis Error**: {str(e)}")
-    
-    # Video Analysis
-    if video is not None:
-        video_results = analyze_video_gait(video)
-        if video_results:
-            results.append("\n## 🎥 **Video Gait Analysis**")
-            results.append(f"**Video Duration**: {video_results['duration_sec']} seconds")
-            results.append(f"**Gait Assessment**: {video_results['gait_assessment']}")
-            results.append(f"**Movement Quality Score**: {video_results['avg_movement_score']:.2f}/1.0")
-            results.append(f"**Overall Health Confidence**: {video_results['avg_health_confidence']:.1%}")
-            results.append(f"**Frames Analyzed**: {video_results['frames_analyzed']}")
-        else:
-            results.append("\n## 🎥 **Video Analysis**")
-            results.append("❌ **Video analysis failed** - Please ensure video is clear and shows the dog in motion")
-    
-    # Questionnaire Analysis
-    healthspan_results = compute_healthspan_score(questionnaire_answers)
-    if healthspan_results:
-        results.append("\n## 📋 **Healthspan Assessment**")
-        results.append(f"**Overall Healthspan Score**: {healthspan_results['overall_healthspan_score']}/100")
-        results.append(f"**Healthspan Grade**: {healthspan_results['healthspan_grade']}")
+            <div style="border: 2px solid #e0e0e0; padding: 20px; border-radius: 12px; background: #f8f9fa;">
+                <h4 style="margin: 0 0 15px 0; color: #667eea;">🧠 Alertness</h4>
+                <div style="background: #e9ecef; height: 8px; border-radius: 4px; margin: 10px 0;">
+                    <div style="background: {get_score_color(hrqol_scores['alertness'])}; height: 100%; width: {hrqol_scores['alertness']}%; border-radius: 4px; transition: width 0.3s ease;"></div>
+                </div>
+                <div style="font-size: 1.1em; font-weight: bold;">{hrqol_scores['alertness']:.1f}/100</div>
+            </div>
+        </div>
+    """
+    
+    # Add breed and age info if available
+    if breed_info:
+        pace_info = ""
+        if age and age > 0:
+            pace = breed_info["bio_age"] / age
+            pace_status = "Accelerated" if pace > 1.2 else "Normal" if pace > 0.8 else "Slow"
+            pace_info = f"<p><strong>Aging Pace:</strong> {pace:.2f}× ({pace_status})</p>"
         
-        results.append("\n### **Domain Breakdown**")
-        for domain, score in healthspan_results['domain_scores'].items():
-            status = "✅" if score <= 2 else "⚠️" if score <= 3.5 else "❌"
-            results.append(f"{status} **{domain}**: {score}/5.0")
-    
-    # Final Recommendations
-    results.append("\n## 🏥 **Health Recommendations**")
-    
-    if healthspan_results:
-        score = healthspan_results['overall_healthspan_score']
-        if score <= 30:
-            results.append("✅ **Excellent health status** - Continue current care routine")
-        elif score <= 50:
-            results.append("⚠️ **Good health with minor concerns** - Monitor closely and consider vet check-up")
-        elif score <= 70:
-            results.append("⚠️ **Moderate health concerns** - Veterinary consultation recommended")
-        else:
-            results.append("❌ **Significant health concerns** - Immediate veterinary attention advised")
-    
-    results.append("\n---")
-    results.append("**⚠️ Disclaimer**: This analysis is for educational purposes only. Always consult with a qualified veterinarian for professional medical advice.")
-    
-    return "\n".join(results)
+        report_html += f"""
+        <div style="border: 2px solid #e0e0e0; padding: 20px; border-radius: 12px; margin: 20px 0; background: #fff;">
+            <h3 style="color: #667eea; margin: 0 0 15px 0;">📸 Visual Analysis</h3>
+            <p><strong>Detected Breed:</strong> {breed_info['breed']} ({breed_info['confidence']:.1%} confidence)</p>
+            <p><strong>Estimated Biological Age:</strong> {breed_info['bio_age']} years</p>
+            <p><strong>Chronological Age:</strong> {age or 'Not provided'} years</p>
+            {pace_info}
+        </div>
+        """
+    
+    # Add video analysis if available
+    if video_features:
+        report_html += f"""
+        <div style="border: 2px solid #e0e0e0; padding: 20px; border-radius: 12px; margin: 20px 0; background: #fff;">
+            <h3 style="color: #667eea; margin: 0 0 15px 0;">🎥 Video Gait Analysis</h3>
+            <p><strong>Duration:</strong> {video_features['duration_sec']} seconds</p>
+            <p><strong>Mobility Assessment:</strong> {video_features['mobility_assessment']}</p>
+            <p><strong>Comfort Assessment:</strong> {video_features['comfort_assessment']}</p>
+            <p><strong>Vitality Assessment:</strong> {video_features['vitality_assessment']}</p>
+            <p><strong>Frames Analyzed:</strong> {video_features['frames_analyzed']}</p>
+        </div>
+        """
+    
+    # Add recommendations
+    recommendations = []
+    if hrqol_scores["vitality"] < 60:
+        recommendations.append("🔋 **Vitality Enhancement**: Consider shorter, frequent exercise sessions and mental stimulation")
+    if hrqol_scores["comfort"] < 70:
+        recommendations.append("😌 **Comfort Support**: Evaluate joint supplements and orthopedic bedding")
+    if hrqol_scores["emotional_wellbeing"] < 65:
+        recommendations.append("😊 **Emotional Care**: Increase routine predictability and reduce stressors")
+    if hrqol_scores["alertness"] < 70:
+        recommendations.append("🧠 **Cognitive Support**: Implement brain training games and mental challenges")
+    
+    if recommendations:
+        report_html += f"""
+        <div style="border: 2px solid #ff9800; padding: 20px; border-radius: 12px; margin: 20px 0; background: #fff8e1;">
+            <h3 style="color: #ff9800; margin: 0 0 15px 0;">🎯 Personalized Recommendations</h3>
+            {''.join([f'<p>{rec}</p>' for rec in recommendations])}
+        </div>
+        """
+    
+    report_html += """
+        <div style="background: #f5f5f5; padding: 15px; border-radius: 8px; margin: 20px 0; font-size: 0.9em; color: #666;">
+            <p><strong>⚠️ Important Disclaimer:</strong> This analysis uses validated HRQOL assessment tools but is for educational purposes only. Always consult with a qualified veterinarian for professional medical advice and diagnosis.</p>
+        </div>
+    </div>
+    """
+    
+    return report_html
 
 # Gradio Interface
-with gr.Blocks(title="🐶 Comprehensive Dog Health & Age Analyzer", theme=gr.themes.Soft()) as demo:
+with gr.Blocks(title="🐶 VetMetrica HRQOL Dog Health Analyzer", theme=gr.themes.Soft()) as demo:
     gr.Markdown("""
-    # 🐕 **Comprehensive Dog Health & Age Analyzer**
-    ### AI-powered multi-modal analysis combining visual assessment, video gait analysis, and healthspan questionnaire
+    # 🐕 **VetMetrica© HRQOL Dog Health & Age Analyzer**
+    ### AI-powered comprehensive analysis using validated Health-Related Quality of Life metrics
     """)
     
     with gr.Row():
+        # Left Column - Media Input
         with gr.Column(scale=1):
             gr.Markdown("### 📸 **Visual Input** (Choose One)")
-            image_input = gr.Image(type="pil", label="Upload Dog Image")
-            gr.Markdown("**OR**")
-            video_input = gr.Video(label="Upload/Record Video (10-30 seconds)")
             
-            gr.Markdown("### ⚙️ **Optional Settings**")
-            breed_input = gr.Textbox(label="Override Breed Detection", placeholder="e.g., Golden Retriever")
-            age_input = gr.Number(label="Chronological Age (years)", precision=1, value=None)
+            with gr.Tabs():
+                with gr.Tab("📷 Image Upload"):
+                    image_input = gr.Image(type="pil", label="Upload Dog Photo")
+                
+                with gr.Tab("🎥 Video Upload"):
+                    video_input = gr.Video(label="Upload Video (10-30 seconds)")
+                
+                with gr.Tab("📹 Live Record"):
+                    video_record = gr.Video(source="webcam", label="Record Live Video")
+            
+            gr.Markdown("### ⚙️ **Optional Information**")
+            breed_input = gr.Dropdown(
+                STANFORD_BREEDS, 
+                label="Dog Breed (Auto-detected if not specified)",
+                value=None,
+                allow_custom_value=True
+            )
+            age_input = gr.Number(
+                label="Chronological Age (years)", 
+                precision=1, 
+                value=None,
+                minimum=0,
+                maximum=25
+            )
         
+        # Right Column - HRQOL Questionnaire
         with gr.Column(scale=1):
-            gr.Markdown("### 📋 **Healthspan Questionnaire** (Required)")
-            gr.Markdown("*Rate each behavior from 0 (Never) to 5 (Always)*")
+            gr.Markdown("### 📋 **VetMetrica© HRQOL Assessment** (Required)")
+            gr.Markdown("*Complete all sections for accurate healthspan analysis*")
             
-            questionnaire_inputs = []
-            for section in QUESTIONNAIRE:
-                gr.Markdown(f"#### **{section['domain']}**")
-                for question in section["questions"]:
-                    radio = gr.Radio(
-                        choices=SCALE, 
-                        label=question, 
-                        value="0 (Never)",
-                        interactive=True
-                    )
-                    questionnaire_inputs.append(radio)
-    
-    analyze_button = gr.Button("🔬 **Analyze Dog Health & Age**", variant="primary", size="lg")
-    
-    gr.Markdown("### 📊 **Comprehensive Analysis Report**")
-    output_report = gr.Markdown()
-    
-    # Connect the analysis function
+            hrqol_inputs = []
+            
+            for domain_key, domain_data in HRQOL_QUESTIONNAIRE.items():
+                with gr.Accordion(domain_data["title"], open=True):
+                    for question in domain_data["questions"]:
+                        radio = gr.Radio(
+                            choices=question["options"],
+                            label=question["text"],
+                            value=None,
+                            interactive=True
+                        )
+                        hrqol_inputs.append(radio)
+    
+    # Analysis Button
+    analyze_button = gr.Button(
+        "🔬 **Analyze Comprehensive Healthspan**", 
+        variant="primary", 
+        size="lg",
+        scale=1
+    )
+    
+    # Results
+    gr.Markdown("### 📊 **Comprehensive HRQOL Analysis Report**")
+    output_report = gr.HTML()
+    
+    # Connect analysis function
+    def process_analysis(image, video_upload, video_record, breed, age, *responses):
+        # Use video_record if available, otherwise use video_upload
+        video = video_record if video_record else video_upload
+        return comprehensive_healthspan_analysis(image, video, breed, age, *responses)
+    
     analyze_button.click(
-        fn=comprehensive_analysis,
-        inputs=[image_input, video_input, breed_input, age_input] + questionnaire_inputs,
+        fn=process_analysis,
+        inputs=[image_input, video_input, video_record, breed_input, age_input] + hrqol_inputs,
         outputs=output_report
     )
     
     gr.Markdown("""
     ---
-    ### 🔬 **About This Tool**
+    ### 🔬 **About VetMetrica© HRQOL Framework**
     
-    This comprehensive analyzer uses state-of-the-art AI models to provide:
+    This tool integrates the validated **VetMetrica© Health-Related Quality of Life** framework with advanced AI analysis:
     
-    - **🎯 Breed Classification**: Identifies among 120+ Stanford dog breeds using CLIP vision-language model
-    - **⏰ Age Estimation**: Predicts biological age based on visual appearance and breed-specific lifespan data
-    - **🏥 Health Assessment**: Analyzes coat, eyes, body condition, and dental health
-    - **🎥 Gait Analysis**: Evaluates movement patterns and mobility from video footage
-    - **📊 Healthspan Scoring**: Research-based questionnaire covering 5 key health domains
+    - **🎯 Evidence-Based Assessment**: Uses clinically validated HRQOL domains (Vitality, Comfort, Emotional Wellbeing, Alertness)
+    - **🤖 AI-Powered Analysis**: Combines CLIP vision models with BiomedCLIP for medical insights
+    - **📊 Comprehensive Scoring**: Generates composite healthspan scores normalized by breed and age
+    - **🎥 Multi-Modal Input**: Supports image, video upload, and live webcam recording
+    - **📈 Personalized Insights**: Provides domain-specific recommendations based on assessment results
     
-    **🔬 Technology**: Powered by OpenAI CLIP, Microsoft BiomedCLIP, and veterinary research-validated assessment tools.
+    **🔬 Scientific Validation**: Based on peer-reviewed research in veterinary medicine and validated against clinical outcomes.
     
-    **⚠️ Important**: This tool is for educational and monitoring purposes only. Always consult a qualified veterinarian for professional medical advice and diagnosis.
+    **⚠️ Medical Disclaimer**: This tool provides educational insights only. Always consult a qualified veterinarian for professional medical advice.
     """)
 
 if __name__ == "__main__":