Update app.py

app.py

@@ -284,164 +284,166 @@ class UltraSupremeAnalyzer:
         ultra_result["intelligence_metrics"]["cultural_awareness_score"] = len(ultra_result["demographic"]["cultural_religious"]) * 20
         
         return ultra_result
+    
         def build_ultra_supreme_prompt(self, ultra_analysis, clip_results):
-        """BUILD ULTRA SUPREME FLUX PROMPT - ABSOLUTE MAXIMUM QUALITY"""
-        
-        components = []
-        
-        # 1. ULTRA INTELLIGENT ARTICLE SELECTION
-        subject_desc = []
-        if ultra_analysis["demographic"]["cultural_religious"]:
-            subject_desc.extend(ultra_analysis["demographic"]["cultural_religious"][:1])
-        if ultra_analysis["demographic"]["age_category"] and ultra_analysis["demographic"]["age_category"] != "middle_aged":
-            subject_desc.append(ultra_analysis["demographic"]["age_category"].replace("_", " "))
-        if ultra_analysis["demographic"]["gender"]:
-            subject_desc.append(ultra_analysis["demographic"]["gender"])
-        
-        if subject_desc:
-            full_subject = " ".join(subject_desc)
-            article = "An" if full_subject[0].lower() in 'aeiou' else "A"
-        else:
-            article = "A"
-        components.append(article)
-        
-        # 2. ULTRA CONTEXTUAL ADJECTIVES (max 2-3 per Flux rules)
-        adjectives = []
-        
-        # Age-based adjectives
-        age_cat = ultra_analysis["demographic"]["age_category"]
-        if age_cat and age_cat in self.quality_descriptors_ultra["based_on_age"]:
-            adjectives.extend(self.quality_descriptors_ultra["based_on_age"][age_cat][:2])
-        
-        # Emotion-based adjectives
-        emotion = ultra_analysis["emotional_state"]["primary_emotion"]
-        if emotion and emotion in self.quality_descriptors_ultra["based_on_emotion"]:
-            adjectives.extend(self.quality_descriptors_ultra["based_on_emotion"][emotion][:1])
-        
-        # Default if none found
-        if not adjectives:
-            adjectives = ["distinguished", "professional"]
-        
-        components.extend(adjectives[:2])  # Flux rule: max 2-3 adjectives
-        
-        # 3. ULTRA ENHANCED SUBJECT
-        if subject_desc:
-            components.append(" ".join(subject_desc))
-        else:
-            components.append("person")
-        
-        # 4. ULTRA DETAILED FACIAL FEATURES
-        facial_details = []
-        
-        # Eyes
-        if ultra_analysis["facial_ultra"]["eyes"]:
-            eye_desc = ultra_analysis["facial_ultra"]["eyes"][0]
-            facial_details.append(f"with {eye_desc}")
-        
-        # Facial hair with ultra detail
-        if ultra_analysis["facial_ultra"]["facial_hair"]:
-            beard_details = ultra_analysis["facial_ultra"]["facial_hair"]
-            if any("silver" in detail or "gray" in detail or "grey" in detail for detail in beard_details):
-                facial_details.append("with a distinguished silver beard")
-            elif any("beard" in detail for detail in beard_details):
-                facial_details.append("with a full well-groomed beard")
-        
-        if facial_details:
-            components.extend(facial_details)
-        
-        # 5. CLOTHING AND ACCESSORIES ULTRA
-        clothing_details = []
-        
-        # Eyewear
-        if ultra_analysis["clothing_accessories"]["eyewear"]:
-            eyewear = ultra_analysis["clothing_accessories"]["eyewear"][0]
-            clothing_details.append(f"wearing {eyewear}")
-        
-        # Headwear
-        if ultra_analysis["clothing_accessories"]["headwear"]:
-            headwear = ultra_analysis["clothing_accessories"]["headwear"][0]
+            """BUILD ULTRA SUPREME FLUX PROMPT - ABSOLUTE MAXIMUM QUALITY"""
+            
+            components = []
+            
+            # 1. ULTRA INTELLIGENT ARTICLE SELECTION
+            subject_desc = []
             if ultra_analysis["demographic"]["cultural_religious"]:
-                clothing_details.append("wearing a traditional black hat")
+                subject_desc.extend(ultra_analysis["demographic"]["cultural_religious"][:1])
+            if ultra_analysis["demographic"]["age_category"] and ultra_analysis["demographic"]["age_category"] != "middle_aged":
+                subject_desc.append(ultra_analysis["demographic"]["age_category"].replace("_", " "))
+            if ultra_analysis["demographic"]["gender"]:
+                subject_desc.append(ultra_analysis["demographic"]["gender"])
+            
+            if subject_desc:
+                full_subject = " ".join(subject_desc)
+                article = "An" if full_subject[0].lower() in 'aeiou' else "A"
             else:
-                clothing_details.append(f"wearing a {headwear}")
-        
-        if clothing_details:
-            components.extend(clothing_details)
-        
-        # 6. ULTRA POSE AND BODY LANGUAGE
-        pose_description = "positioned with natural dignity"
-        
-        if ultra_analysis["pose_composition"]["posture"]:
-            posture = ultra_analysis["pose_composition"]["posture"][0]
-            pose_description = f"maintaining {posture}"
-        elif ultra_analysis["technical_analysis"]["shot_type"] == "portrait":
-            pose_description = "captured in contemplative portrait pose"
-        
-        components.append(pose_description)
-        
-        # 7. ULTRA ENVIRONMENTAL CONTEXT
-        environment_desc = "in a thoughtfully composed environment"
-        
-        if ultra_analysis["environmental"]["setting_type"]:
-            setting_map = {
-                "residential": "in an intimate home setting",
-                "office": "in a professional office environment", 
-                "religious": "in a sacred traditional space",
-                "formal": "in a distinguished formal setting"
-            }
-            environment_desc = setting_map.get(ultra_analysis["environmental"]["setting_type"], "in a carefully arranged professional setting")
-        
-        components.append(environment_desc)
-        
-        # 8. ULTRA SOPHISTICATED LIGHTING
-        lighting_desc = "illuminated by sophisticated portrait lighting that emphasizes character and facial texture"
-        
-        if ultra_analysis["environmental"]["lighting_analysis"]:
-            primary_light = ultra_analysis["environmental"]["lighting_analysis"][0]
-            if "dramatic" in primary_light:
-                lighting_desc = "bathed in dramatic chiaroscuro lighting that creates compelling depth and shadow play"
-            elif "natural" in primary_light or "window" in primary_light:
-                lighting_desc = "graced by gentle natural lighting that brings out intricate facial details and warmth"
-            elif "soft" in primary_light:
-                lighting_desc = "softly illuminated to reveal nuanced expressions and character"
-        
-        components.append(lighting_desc)
-        
-        # 9. ULTRA TECHNICAL SPECIFICATIONS
-        if ultra_analysis["technical_analysis"]["shot_type"] in ["portrait", "headshot", "close-up"]:
-            camera_setup = "Shot on Phase One XF IQ4, 85mm f/1.4 lens, f/2.8 aperture"
-        elif ultra_analysis["demographic"]["cultural_religious"]:
-            camera_setup = "Shot on Hasselblad X2D, 90mm lens, f/2.8 aperture" 
-        else:
-            camera_setup = "Shot on Phase One XF, 80mm lens, f/4 aperture"
-        
-        components.append(camera_setup)
-        
-        # 10. ULTRA QUALITY DESIGNATION
-        quality_designation = "professional portrait photography"
-        
-        if ultra_analysis["demographic"]["cultural_religious"]:
-            quality_designation = "fine art documentary photography"
-        elif ultra_analysis["emotional_state"]["primary_emotion"]:
-            quality_designation = "expressive portrait photography"
-        
-        components.append(quality_designation)
-        
-        # ULTRA FINAL ASSEMBLY
-        prompt = ", ".join(components)
-        
-        # Ultra cleaning and optimization
-        prompt = re.sub(r'\s+', ' ', prompt)
-        prompt = re.sub(r',\s*,+', ',', prompt)
-        prompt = re.sub(r'\s*,\s*', ', ', prompt)
-        prompt = prompt.replace(" ,", ",")
-        
-        if prompt:
-            prompt = prompt[0].upper() + prompt[1:]
-        
-        return prompt
+                article = "A"
+            components.append(article)
+            
+            # 2. ULTRA CONTEXTUAL ADJECTIVES (max 2-3 per Flux rules)
+            adjectives = []
+            
+            # Age-based adjectives
+            age_cat = ultra_analysis["demographic"]["age_category"]
+            if age_cat and age_cat in self.quality_descriptors_ultra["based_on_age"]:
+                adjectives.extend(self.quality_descriptors_ultra["based_on_age"][age_cat][:2])
+            
+            # Emotion-based adjectives
+            emotion = ultra_analysis["emotional_state"]["primary_emotion"]
+            if emotion and emotion in self.quality_descriptors_ultra["based_on_emotion"]:
+                adjectives.extend(self.quality_descriptors_ultra["based_on_emotion"][emotion][:1])
+            
+            # Default if none found
+            if not adjectives:
+                adjectives = ["distinguished", "professional"]
+            
+            components.extend(adjectives[:2])  # Flux rule: max 2-3 adjectives
+            
+            # 3. ULTRA ENHANCED SUBJECT
+            if subject_desc:
+                components.append(" ".join(subject_desc))
+            else:
+                components.append("person")
+            
+            # 4. ULTRA DETAILED FACIAL FEATURES
+            facial_details = []
+            
+            # Eyes
+            if ultra_analysis["facial_ultra"]["eyes"]:
+                eye_desc = ultra_analysis["facial_ultra"]["eyes"][0]
+                facial_details.append(f"with {eye_desc}")
+            
+            # Facial hair with ultra detail
+            if ultra_analysis["facial_ultra"]["facial_hair"]:
+                beard_details = ultra_analysis["facial_ultra"]["facial_hair"]
+                if any("silver" in detail or "gray" in detail or "grey" in detail for detail in beard_details):
+                    facial_details.append("with a distinguished silver beard")
+                elif any("beard" in detail for detail in beard_details):
+                    facial_details.append("with a full well-groomed beard")
+            
+            if facial_details:
+                components.extend(facial_details)
+            
+            # 5. CLOTHING AND ACCESSORIES ULTRA
+            clothing_details = []
+            
+            # Eyewear
+            if ultra_analysis["clothing_accessories"]["eyewear"]:
+                eyewear = ultra_analysis["clothing_accessories"]["eyewear"][0]
+                clothing_details.append(f"wearing {eyewear}")
+            
+            # Headwear
+            if ultra_analysis["clothing_accessories"]["headwear"]:
+                headwear = ultra_analysis["clothing_accessories"]["headwear"][0]
+                if ultra_analysis["demographic"]["cultural_religious"]:
+                    clothing_details.append("wearing a traditional black hat")
+                else:
+                    clothing_details.append(f"wearing a {headwear}")
+            
+            if clothing_details:
+                components.extend(clothing_details)
+            
+            # 6. ULTRA POSE AND BODY LANGUAGE
+            pose_description = "positioned with natural dignity"
+            
+            if ultra_analysis["pose_composition"]["posture"]:
+                posture = ultra_analysis["pose_composition"]["posture"][0]
+                pose_description = f"maintaining {posture}"
+            elif ultra_analysis["technical_analysis"]["shot_type"] == "portrait":
+                pose_description = "captured in contemplative portrait pose"
+            
+            components.append(pose_description)
+            
+            # 7. ULTRA ENVIRONMENTAL CONTEXT
+            environment_desc = "in a thoughtfully composed environment"
+            
+            if ultra_analysis["environmental"]["setting_type"]:
+                setting_map = {
+                    "residential": "in an intimate home setting",
+                    "office": "in a professional office environment", 
+                    "religious": "in a sacred traditional space",
+                    "formal": "in a distinguished formal setting"
+                }
+                environment_desc = setting_map.get(ultra_analysis["environmental"]["setting_type"], "in a carefully arranged professional setting")
+            
+            components.append(environment_desc)
+            
+            # 8. ULTRA SOPHISTICATED LIGHTING
+            lighting_desc = "illuminated by sophisticated portrait lighting that emphasizes character and facial texture"
+            
+            if ultra_analysis["environmental"]["lighting_analysis"]:
+                primary_light = ultra_analysis["environmental"]["lighting_analysis"][0]
+                if "dramatic" in primary_light:
+                    lighting_desc = "bathed in dramatic chiaroscuro lighting that creates compelling depth and shadow play"
+                elif "natural" in primary_light or "window" in primary_light:
+                    lighting_desc = "graced by gentle natural lighting that brings out intricate facial details and warmth"
+                elif "soft" in primary_light:
+                    lighting_desc = "softly illuminated to reveal nuanced expressions and character"
+            
+            components.append(lighting_desc)
+            
+            # 9. ULTRA TECHNICAL SPECIFICATIONS
+            if ultra_analysis["technical_analysis"]["shot_type"] in ["portrait", "headshot", "close-up"]:
+                camera_setup = "Shot on Phase One XF IQ4, 85mm f/1.4 lens, f/2.8 aperture"
+            elif ultra_analysis["demographic"]["cultural_religious"]:
+                camera_setup = "Shot on Hasselblad X2D, 90mm lens, f/2.8 aperture" 
+            else:
+                camera_setup = "Shot on Phase One XF, 80mm lens, f/4 aperture"
+            
+            components.append(camera_setup)
+            
+            # 10. ULTRA QUALITY DESIGNATION
+            quality_designation = "professional portrait photography"
+            
+            if ultra_analysis["demographic"]["cultural_religious"]:
+                quality_designation = "fine art documentary photography"
+            elif ultra_analysis["emotional_state"]["primary_emotion"]:
+                quality_designation = "expressive portrait photography"
+            
+            components.append(quality_designation)
+            
+            # ULTRA FINAL ASSEMBLY
+            prompt = ", ".join(components)
+            
+            # Ultra cleaning and optimization
+            prompt = re.sub(r'\s+', ' ', prompt)
+            prompt = re.sub(r',\s*,+', ',', prompt)
+            prompt = re.sub(r'\s*,\s*', ', ', prompt)
+            prompt = prompt.replace(" ,", ",")
+            
+            if prompt:
+                prompt = prompt[0].upper() + prompt[1:]
+            
+            return prompt
+    
         def calculate_ultra_supreme_score(self, prompt, ultra_analysis):
-        """ULTRA SUPREME INTELLIGENCE SCORING"""
+            """ULTRA SUPREME INTELLIGENCE SCORING"""
         
         score = 0
         breakdown = {}
@@ -549,7 +551,8 @@ class UltraSupremeOptimizer:
             image.thumbnail((max_size, max_size), Image.Resampling.LANCZOS)
         
         return image
-        @spaces.GPU
+
+    @spaces.GPU
     def generate_ultra_supreme_prompt(self, image):
         try:
             if not self.is_initialized: