Update app.py

app.py

@@ -500,8 +500,7 @@ class UltraSupremeAnalyzer:
         breakdown["environmental"] = env_score
         
         return min(score, 100), breakdown
-
-class UltraSupremeOptimizer:
+        class UltraSupremeOptimizer:
     def __init__(self):
         self.interrogator = None
         self.analyzer = UltraSupremeAnalyzer()
@@ -608,11 +607,9 @@ class UltraSupremeOptimizer:
             clothing = ", ".join(ultra_analysis["clothing_accessories"]["eyewear"] + ultra_analysis["clothing_accessories"]["headwear"]) if ultra_analysis["clothing_accessories"]["eyewear"] or ultra_analysis["clothing_accessories"]["headwear"] else "None detected"
             
             analysis_info = f"""**🚀 ULTRA SUPREME ANALYSIS COMPLETE**
-
 **Processing:** {gpu_status} • {duration:.1f}s • Triple CLIP Ultra Intelligence  
 **Ultra Score:** {score}/100 • Breakdown: Structure({breakdown.get('structure',0)}) Features({breakdown.get('features',0)}) Cultural({breakdown.get('cultural',0)}) Emotional({breakdown.get('emotional',0)}) Technical({breakdown.get('technical',0)})  
 **Generation:** #{self.usage_count}  
-
 **🧠 ULTRA DEEP DETECTION:**
 • **Age Category:** {ultra_analysis["demographic"].get("age_category", "Unspecified").replace("_", " ").title()} (Confidence: {ultra_analysis["demographic"].get("age_confidence", 0)})
 • **Cultural Context:** {cultural}  
@@ -621,12 +618,10 @@ class UltraSupremeOptimizer:
 • **Setting:** {ultra_analysis["environmental"].get("setting_type", "Standard").title()}
 • **Emotion:** {ultra_analysis["emotional_state"].get("primary_emotion", "Neutral").title()}
 • **Total Features:** {ultra_analysis["intelligence_metrics"]["total_features_detected"]}
-
 **📊 CLIP ANALYSIS SOURCES:**
 • **Fast:** {clip_fast[:50]}...
 • **Classic:** {clip_classic[:50]}...  
 • **Best:** {clip_best[:50]}...
-
 **⚡ ULTRA OPTIMIZATION:** Applied absolute maximum depth analysis with Pariente AI research rules"""
             
             return optimized_prompt, analysis_info, score, breakdown
@@ -635,6 +630,7 @@ class UltraSupremeOptimizer:
             logger.error(f"Ultra supreme generation error: {e}")
             return f"❌ Error: {str(e)}", "Please try with a different image.", 0, {}
 
+# Initialize the optimizer
 optimizer = UltraSupremeOptimizer()
 
 def process_ultra_supreme_analysis(image):
@@ -825,6 +821,18 @@ def create_interface():
                 
                 clear_btn = gr.Button("🗑️ Clear Ultra Analysis", size="sm")
         
+        # Event handlers
+        analyze_btn.click(
+            fn=process_ultra_supreme_analysis,
+            inputs=[image_input],
+            outputs=[prompt_output, info_output, score_output]
+        )
+        
+        clear_btn.click(
+            fn=clear_outputs,
+            outputs=[prompt_output, info_output, score_output]
+        )
+        
         gr.Markdown("""
         ---
         ### 🏆 Ultra Supreme Research Foundation
@@ -833,4 +841,17 @@ def create_interface():
         ultra-deep feature extraction, cultural context awareness, and emotional intelligence mapping, it achieves maximum possible 
         understanding and applies research-validated Flux rules with supreme intelligence.
         
-        **🔬 Pariente AI Research Laboratory** • **🚀 Ultra Supreme
+        **🔬 Pariente AI Research Laboratory** • **🚀 Ultra Supreme Intelligence Engine**
+        """)
+    
+    return interface
+
+# Launch the application
+if __name__ == "__main__":
+    demo = create_interface()
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        share=True,
+        show_error=True
+    )