🧠 Ultimate Brain v3.0: Multi-AI + 100+ Reasoning Protocols + Supertonic

app.py

@@ -16,6 +16,10 @@ import requests
 # Import Unified Brain
 from unified_brain import UnifiedBrain, ReasoningContext
 
+# Import Performance & Analytics
+from performance_optimizer import performance_cache, performance_monitor, with_caching
+from analytics_seo import analytics_tracker, SEOOptimizer
+
 class UltimateLegalBrain:
     """
     Ultimate Legal AI Brain combining:
@@ -103,6 +107,19 @@ async def respond_with_ultimate_brain(
 ):
     """Generate response using Ultimate Brain"""
     
+    import time
+    start_time = time.time()
+    
+    # Track analytics
+    analytics_tracker.track_query(
+        query=message,
+        mode=mode,
+        ai_provider=ai_provider,
+        reasoning_enabled=use_reasoning,
+        response_time=0,  # Will update later
+        success=True
+    )
+    
     # Process with Brain
     brain_result = await ultimate_brain.process_legal_query(
         query=message,
@@ -198,7 +215,15 @@ custom_css = """
 # Create Gradio Interface
 demo = gr.Blocks(title="ProVerBs Ultimate Legal AI Brain", css=custom_css)
 
+# Add SEO meta tags
+seo_meta = SEOOptimizer.get_meta_tags()
+seo_structured = SEOOptimizer.get_structured_data()
+
 with demo:
+    # Add SEO tags
+    gr.HTML(seo_meta + seo_structured)
+    
+    # Header
     gr.HTML("""
     <div class="header-section">
         <h1>⚖️ ProVerBs Ultimate Legal AI Brain</h1>
@@ -417,6 +442,76 @@ with demo:
             - Regulatory updates with RAG
             """)
         
+        # Analytics Dashboard Tab
+        with gr.Tab("📊 Analytics"):
+            gr.Markdown("""
+            ## Analytics & Performance Dashboard
+            
+            View real-time analytics and performance metrics for the Ultimate Brain.
+            """)
+            
+            with gr.Row():
+                analytics_btn = gr.Button("📊 Refresh Analytics", variant="primary")
+                clear_cache_btn = gr.Button("🗑️ Clear Cache", variant="secondary")
+            
+            analytics_output = gr.JSON(label="Analytics Data")
+            performance_output = gr.JSON(label="Performance Metrics")
+            cache_stats_output = gr.JSON(label="Cache Statistics")
+            
+            def get_analytics():
+                return analytics_tracker.get_analytics()
+            
+            def get_performance():
+                return performance_monitor.get_metrics()
+            
+            def get_cache_stats():
+                return performance_cache.get_stats()
+            
+            def clear_cache_action():
+                performance_cache.clear()
+                return {"status": "Cache cleared successfully"}
+            
+            analytics_btn.click(
+                fn=lambda: (get_analytics(), get_performance(), get_cache_stats()),
+                outputs=[analytics_output, performance_output, cache_stats_output]
+            )
+            
+            clear_cache_btn.click(
+                fn=clear_cache_action,
+                outputs=[cache_stats_output]
+            )
+            
+            gr.Markdown("""
+            ### 📈 What's Tracked:
+            
+            **Analytics:**
+            - Total queries processed
+            - Success rate
+            - Average response time
+            - Most popular legal modes
+            - Most popular AI models
+            - Reasoning protocol usage
+            - Recent queries
+            
+            **Performance:**
+            - Cache hit rate
+            - Total requests
+            - Average response time
+            - Error rate
+            
+            **Cache:**
+            - Current cache size
+            - Maximum capacity
+            - TTL (Time To Live)
+            - Oldest cached entry
+            
+            ### 💡 Optimization Tips:
+            - High cache hit rate = faster responses
+            - Monitor popular modes to optimize
+            - Clear cache if experiencing issues
+            - Analytics help identify usage patterns
+            """)
+        
         # About Tab
         with gr.Tab("ℹ️ About"):
             gr.Markdown("""