Update app.py

app.py

@@ -2,7 +2,7 @@
 🚀 ARF Ultimate Investor Demo v3.8.0 - ENTERPRISE EDITION
 MODULAR VERSION - Properly integrated with all components
 ULTIMATE FIXED VERSION with all critical issues resolved
-NOW WITH REAL ARF v3.3.7 INTEGRATION
+NOW WITH REAL ARF v3.3.7 INTEGRATION AND DYNAMIC SCENARIO METRICS
 """
 
 import logging
@@ -12,6 +12,7 @@ import json
 import datetime
 import asyncio
 import time
+import random
 from pathlib import Path
 from typing import Dict, List, Any, Optional, Tuple
 
@@ -72,13 +73,78 @@ class Settings:
     """Simple settings class"""
     def __init__(self):
         self.arf_mode = "demo"
-        self.use_mock_arf = False  # Changed to False to use real ARF by default
+        self.use_mock_arf = True  # Start with mock to prevent auto-analysis
         self.default_scenario = "Cache Miss Storm"
         self.max_history_items = 100
         self.auto_refresh_seconds = 30
 
 settings = Settings()
 
+# ===========================================
+# HELPER FUNCTIONS FOR EMPTY STATES
+# ===========================================
+def create_empty_plot(title: str):
+    """Create an empty placeholder plot"""
+    import plotly.graph_objects as go
+    fig = go.Figure()
+    fig.add_annotation(
+        text="👆 Select a scenario<br>to view data",
+        xref="paper", yref="paper",
+        x=0.5, y=0.5, showarrow=False,
+        font=dict(size=14, color="#64748b")
+    )
+    fig.update_layout(
+        height=300,
+        title=title,
+        paper_bgcolor="rgba(0,0,0,0)",
+        plot_bgcolor="rgba(0,0,0,0)",
+        xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
+        yaxis=dict(showgrid=False, zeroline=False, showticklabels=False)
+    )
+    return fig
+
+def create_empty_dashboard():
+    """Create empty dashboard"""
+    import plotly.graph_objects as go
+    fig = go.Figure()
+    fig.add_annotation(
+        text="📊 Dashboard will populate<br>after ROI calculation",
+        xref="paper", yref="paper",
+        x=0.5, y=0.5, showarrow=False,
+        font=dict(size=16, color="#64748b")
+    )
+    fig.update_layout(
+        height=700,
+        paper_bgcolor="rgba(0,0,0,0)",
+        plot_bgcolor="rgba(0,0,0,0)",
+        xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
+        yaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
+        title=""
+    )
+    return fig
+
+def get_inactive_agent_html(agent_name: str, description: str):
+    """Get HTML for inactive agent state"""
+    icons = {
+        "Detection": "🕵️‍♂️",
+        "Recall": "🧠", 
+        "Decision": "🎯"
+    }
+    
+    return f"""
+    <div style="border: 2px solid #e2e8f0; border-radius: 14px; padding: 18px; background: #f8fafc; text-align: center; min-height: 180px; display: flex; flex-direction: column; align-items: center; justify-content: center; opacity: 0.7;">
+        <div style="font-size: 32px; margin-bottom: 10px; opacity: 0.5;">{icons.get(agent_name, '⏳')}</div>
+        <div style="width: 100%;">
+            <h4 style="margin: 0 0 8px 0; font-size: 16px; color: #94a3b8;">{agent_name} Agent</h4>
+            <p style="font-size: 13px; color: #cbd5e1; margin-bottom: 12px; line-height: 1.4;">{description}</p>
+            <div style="display: flex; justify-content: space-around; margin-bottom: 12px;">
+                <span style="font-size: 11px; padding: 3px 8px; background: rgba(255, 255, 255, 0.5); border-radius: 6px; color: #cbd5e1; font-weight: 500;">Status: Inactive</span>
+            </div>
+            <div style="display: inline-block; padding: 5px 14px; background: #e2e8f0; border-radius: 20px; font-size: 12px; font-weight: bold; color: #64748b; text-transform: uppercase; letter-spacing: 0.5px;">WAITING</div>
+        </div>
+    </div>
+    """
+
 # ===========================================
 # REAL ARF ORCHESTRATOR (Replaces FixedDemoOrchestrator)
 # ===========================================
@@ -113,17 +179,255 @@ class RealARFOrchestrator:
             self._init_mock_fallback()
     
     def _init_mock_fallback(self):
-        """Initialize mock fallback functions"""
-        from demo.mock_arf import (
-            simulate_arf_analysis,
-            run_rag_similarity_search,
-            create_mock_healing_intent,
-            calculate_pattern_confidence
-        )
+        """Initialize mock fallback functions with scenario-aware metrics"""
+        # We'll use the enhanced mock ARF functions
+        # These will be loaded lazily when needed
+        self._mock_functions_loaded = False
+        self._simulate_arf_analysis = None
+        self._run_rag_similarity_search = None
+        self._create_mock_healing_intent = None
+        self._calculate_pattern_confidence = None
+    
+    def _load_mock_functions(self):
+        """Lazy load enhanced mock ARF functions with scenario-aware metrics"""
+        if not self._mock_functions_loaded:
+            try:
+                # Try to import enhanced mock ARF functions
+                from demo.mock_arf import (
+                    simulate_arf_analysis,
+                    run_rag_similarity_search,
+                    create_mock_healing_intent,
+                    calculate_pattern_confidence
+                )
+                self._simulate_arf_analysis = simulate_arf_analysis
+                self._run_rag_similarity_search = run_rag_similarity_search
+                self._create_mock_healing_intent = create_mock_healing_intent
+                self._calculate_pattern_confidence = calculate_pattern_confidence
+                self._mock_functions_loaded = True
+                logger.info("✅ Enhanced scenario-aware mock ARF functions loaded")
+            except ImportError as e:
+                logger.error(f"Failed to load enhanced mock ARF functions: {e}")
+                # Create fallback functions with scenario-aware metrics
+                self._create_scenario_aware_fallback_functions()
+    
+    def _create_scenario_aware_fallback_functions(self):
+        """Create scenario-aware fallback mock functions"""
+        import random
+        import time as ttime
+        
+        # Scenario-specific configurations
+        scenario_configs = {
+            "Cache Miss Storm": {
+                "detection_confidence_range": (0.97, 0.995),
+                "detection_time_range": (35, 55),
+                "accuracy_range": (0.97, 0.995),
+                "similar_incidents_range": (2, 5),
+                "similarity_score_range": (0.88, 0.96),
+                "pattern_confidence_range": (0.91, 0.97),
+                "success_rate_range": (0.82, 0.93),
+                "cost_savings_range": (5000, 9000)
+            },
+            "Database Connection Pool Exhaustion": {
+                "detection_confidence_range": (0.92, 0.98),
+                "detection_time_range": (40, 65),
+                "accuracy_range": (0.95, 0.985),
+                "similar_incidents_range": (1, 4),
+                "similarity_score_range": (0.85, 0.94),
+                "pattern_confidence_range": (0.88, 0.95),
+                "success_rate_range": (0.78, 0.88),
+                "cost_savings_range": (3500, 5500)
+            },
+            "Kubernetes Memory Leak": {
+                "detection_confidence_range": (0.94, 0.99),
+                "detection_time_range": (30, 50),
+                "accuracy_range": (0.96, 0.99),
+                "similar_incidents_range": (3, 6),
+                "similarity_score_range": (0.89, 0.95),
+                "pattern_confidence_range": (0.90, 0.96),
+                "success_rate_range": (0.85, 0.92),
+                "cost_savings_range": (4500, 7500)
+            },
+            "API Rate Limit Storm": {
+                "detection_confidence_range": (0.96, 0.99),
+                "detection_time_range": (25, 45),
+                "accuracy_range": (0.97, 0.99),
+                "similar_incidents_range": (2, 4),
+                "similarity_score_range": (0.87, 0.93),
+                "pattern_confidence_range": (0.89, 0.94),
+                "success_rate_range": (0.80, 0.90),
+                "cost_savings_range": (3000, 5000)
+            },
+            "Network Partition": {
+                "detection_confidence_range": (0.98, 0.999),
+                "detection_time_range": (20, 40),
+                "accuracy_range": (0.98, 0.995),
+                "similar_incidents_range": (1, 3),
+                "similarity_score_range": (0.90, 0.97),
+                "pattern_confidence_range": (0.93, 0.98),
+                "success_rate_range": (0.75, 0.85),
+                "cost_savings_range": (8000, 15000)
+            },
+            "Storage I/O Saturation": {
+                "detection_confidence_range": (0.93, 0.98),
+                "detection_time_range": (45, 70),
+                "accuracy_range": (0.94, 0.98),
+                "similar_incidents_range": (2, 5),
+                "similarity_score_range": (0.86, 0.92),
+                "pattern_confidence_range": (0.87, 0.93),
+                "success_rate_range": (0.79, 0.87),
+                "cost_savings_range": (5500, 8500)
+            }
+        }
+        
+        def get_scenario_config(scenario_name):
+            """Get configuration for a specific scenario"""
+            return scenario_configs.get(scenario_name, {
+                "detection_confidence_range": (0.90, 0.98),
+                "detection_time_range": (30, 60),
+                "accuracy_range": (0.92, 0.98),
+                "similar_incidents_range": (1, 3),
+                "similarity_score_range": (0.85, 0.95),
+                "pattern_confidence_range": (0.85, 0.95),
+                "success_rate_range": (0.75, 0.90),
+                "cost_savings_range": (4000, 8000)
+            })
+        
+        def simulate_arf_analysis(scenario):
+            """Scenario-aware mock analysis"""
+            scenario_name = scenario.get("name", "Unknown Scenario")
+            config = get_scenario_config(scenario_name)
+            
+            # Generate scenario-specific values
+            detection_confidence = random.uniform(*config["detection_confidence_range"])
+            detection_time = random.randint(*config["detection_time_range"])
+            accuracy = random.uniform(*config["accuracy_range"])
+            
+            return {
+                "analysis_complete": True,
+                "anomaly_detected": True,
+                "severity": scenario.get("severity", "HIGH"),
+                "confidence": round(detection_confidence, 3),
+                "detection_time_ms": detection_time * 1000,
+                "detection_time_seconds": detection_time,
+                "accuracy": round(accuracy, 3),
+                "component": scenario.get("component", "unknown"),
+                "scenario_specific": True,
+                "scenario_name": scenario_name
+            }
+        
+        def run_rag_similarity_search(scenario):
+            """Scenario-aware RAG search"""
+            scenario_name = scenario.get("name", "Unknown Scenario")
+            config = get_scenario_config(scenario_name)
+            
+            similar_count = random.randint(*config["similar_incidents_range"])
+            similar_incidents = []
+            
+            base_time = int(ttime.time())
+            
+            for i in range(similar_count):
+                similarity_score = random.uniform(*config["similarity_score_range"])
+                cost_savings = random.randint(*config["cost_savings_range"])
+                
+                similar_incidents.append({
+                    "incident_id": f"inc_{base_time - random.randint(1, 90)}_00{i}",
+                    "similarity_score": round(similarity_score, 3),
+                    "success": random.random() > 0.15,
+                    "resolution": "scale_out",
+                    "cost_savings": cost_savings,
+                    "detection_time": f"{random.randint(30, 60)}s",
+                    "resolution_time": f"{random.randint(10, 25)}m",
+                    "pattern": f"{scenario_name.lower().replace(' ', '_')}_v{random.randint(1, 3)}",
+                    "affected_users": random.randint(20000, 60000),
+                    "component_match": scenario.get("component", "unknown"),
+                    "rag_source": "production_memory_v3"
+                })
+            
+            return similar_incidents
+        
+        def calculate_pattern_confidence(scenario, similar_incidents):
+            """Calculate pattern confidence based on similar incidents"""
+            scenario_name = scenario.get("name", "Unknown Scenario")
+            config = get_scenario_config(scenario_name)
+            
+            if not similar_incidents:
+                return random.uniform(*config["pattern_confidence_range"])
+            
+            # Calculate average similarity and success rate
+            similarity_scores = [inc["similarity_score"] for inc in similar_incidents]
+            success_rates = [1.0 if inc["success"] else 0.0 for inc in similar_incidents]
+            
+            avg_similarity = sum(similarity_scores) / len(similarity_scores)
+            avg_success = sum(success_rates) / len(success_rates)
+            
+            # Weighted average: 60% similarity, 40% success rate
+            confidence = (avg_similarity * 0.6) + (avg_success * 0.4)
+            
+            # Keep within scenario range
+            min_conf, max_conf = config["pattern_confidence_range"]
+            confidence = max(min_conf, min(max_conf, confidence))
+            
+            return round(confidence, 3)
+        
+        def create_mock_healing_intent(scenario, similar_incidents, confidence):
+            """Create mock healing intent based on scenario"""
+            scenario_name = scenario.get("name", "Unknown Scenario")
+            config = get_scenario_config(scenario_name)
+            
+            component = scenario.get("component", "unknown")
+            
+            # Determine action based on component
+            if "cache" in component.lower():
+                action = "scale_out"
+                parameters = {"nodes": "3→5", "memory": "16GB→32GB"}
+            elif "database" in component.lower():
+                action = "restart"
+                parameters = {"connections": "reset_pool", "timeout": "30s"}
+            elif "kubernetes" in component.lower():
+                action = "memory_limit_increase"
+                parameters = {"memory": "1Gi→2Gi", "strategy": "pod_restart"}
+            elif "api" in component.lower():
+                action = "circuit_breaker"
+                parameters = {"threshold": "80%", "window": "5m"}
+            else:
+                action = "investigate"
+                parameters = {"priority": "high"}
+            
+            # Calculate success rate
+            if similar_incidents:
+                success_count = sum(1 for inc in similar_incidents if inc["success"])
+                success_rate = success_count / len(similar_incidents)
+            else:
+                success_rate = random.uniform(*config["success_rate_range"])
+            
+            # Calculate estimated savings
+            if similar_incidents:
+                avg_savings = sum(inc["cost_savings"] for inc in similar_incidents) / len(similar_incidents)
+            else:
+                avg_savings = sum(config["cost_savings_range"]) / 2
+            
+            return {
+                "action": action,
+                "component": component,
+                "confidence": confidence,
+                "parameters": parameters,
+                "success_rate": round(success_rate, 3),
+                "estimated_savings": int(avg_savings),
+                "safety_checks": {
+                    "blast_radius": f"{random.randint(1, 3)} services",
+                    "business_hours": "compliant",
+                    "rollback_plan": "available"
+                },
+                "scenario_specific": True,
+                "scenario_name": scenario_name
+            }
+        
         self._simulate_arf_analysis = simulate_arf_analysis
         self._run_rag_similarity_search = run_rag_similarity_search
-        self._create_mock_healing_intent = create_mock_healing_intent
         self._calculate_pattern_confidence = calculate_pattern_confidence
+        self._create_mock_healing_intent = create_mock_healing_intent
+        self._mock_functions_loaded = True
+        logger.info("Scenario-aware fallback mock functions created")
     
     async def analyze_incident(self, scenario_name: str, scenario_data: Dict[str, Any]) -> Dict[str, Any]:
         """
@@ -175,19 +479,26 @@ class RealARFOrchestrator:
             return await self._analyze_with_mock(scenario_name, scenario_data)
     
     async def _analyze_with_mock(self, scenario_name: str, scenario_data: Dict[str, Any]) -> Dict[str, Any]:
-        """Fallback mock analysis"""
-        logger.info(f"Using mock analysis for: {scenario_name}")
+        """Fallback mock analysis with scenario-aware metrics"""
+        logger.info(f"Using scenario-aware mock analysis for: {scenario_name}")
+        
+        # Load mock functions if not loaded
+        self._load_mock_functions()
         
         try:
+            # Add scenario name to data
+            scenario_data_with_name = scenario_data.copy()
+            scenario_data_with_name["name"] = scenario_name
+            
             # Step 1: Detection Agent
-            detection_result = self._simulate_arf_analysis(scenario_data)
+            detection_result = self._simulate_arf_analysis(scenario_data_with_name)
             
             # Step 2: Recall Agent  
-            similar_incidents = self._run_rag_similarity_search(scenario_data)
+            similar_incidents = self._run_rag_similarity_search(scenario_data_with_name)
             
             # Step 3: Decision Agent
-            confidence = self._calculate_pattern_confidence(scenario_data, similar_incidents)
-            healing_intent = self._create_mock_healing_intent(scenario_data, similar_incidents, confidence)
+            confidence = self._calculate_pattern_confidence(scenario_data_with_name, similar_incidents)
+            healing_intent = self._create_mock_healing_intent(scenario_data_with_name, similar_incidents, confidence)
             
             # Simulate processing time
             await asyncio.sleep(0.5)
@@ -209,7 +520,7 @@ class RealARFOrchestrator:
                 }
             }
             
-            logger.info(f"Mock analysis complete for {scenario_name}")
+            logger.info(f"Scenario-aware mock analysis complete for {scenario_name}")
             return result
             
         except Exception as e:
@@ -334,37 +645,16 @@ def import_components() -> Dict[str, Any]:
             logger.warning(f"EnhancedVisualizationEngine not available: {e}")
             class MockVisualizationEngine:
                 def create_executive_dashboard(self, data=None):
-                    import plotly.graph_objects as go
-                    fig = go.Figure()
-                    fig.update_layout(height=400, title="Executive Dashboard")
-                    return fig
+                    return create_empty_dashboard()
                 
                 def create_telemetry_plot(self, scenario_name, anomaly_detected=True):
-                    import plotly.graph_objects as go
-                    import numpy as np
-                    fig = go.Figure()
-                    fig.add_trace(go.Scatter(x=[0, 1, 2], y=[0, 1, 0]))
-                    fig.update_layout(height=300, title=f"Telemetry: {scenario_name}")
-                    return fig
+                    return create_empty_plot(f"Telemetry: {scenario_name}")
                 
                 def create_impact_gauge(self, scenario_name):
-                    import plotly.graph_objects as go
-                    fig = go.Figure(go.Indicator(
-                        mode="gauge+number",
-                        value=8500,
-                        title={'text': "💰 Hourly Revenue Risk"},
-                        gauge={'axis': {'range': [0, 15000]}}
-                    ))
-                    fig.update_layout(height=300)
-                    return fig
+                    return create_empty_plot(f"Impact: {scenario_name}")
                 
                 def create_timeline_comparison(self):
-                    import plotly.graph_objects as go
-                    fig = go.Figure()
-                    fig.add_trace(go.Bar(name='Manual', x=['Detection', 'Resolution'], y=[300, 2700]))
-                    fig.add_trace(go.Bar(name='ARF', x=['Detection', 'Resolution'], y=[45, 720]))
-                    fig.update_layout(height=400, title="Timeline Comparison")
-                    return fig
+                    return create_empty_plot("Timeline Comparison")
             components["EnhancedVisualizationEngine"] = MockVisualizationEngine()
         
         # Import UI components
@@ -549,12 +839,7 @@ def create_telemetry_plot(scenario_name: str):
         return viz_engine.create_telemetry_plot(scenario_name, anomaly_detected=True)
     except Exception as e:
         logger.error(f"Failed to create telemetry plot: {e}")
-        # Fallback
-        import plotly.graph_objects as go
-        fig = go.Figure()
-        fig.add_trace(go.Scatter(x=[0, 1, 2], y=[0, 1, 0]))
-        fig.update_layout(height=300, title=f"Telemetry: {scenario_name}")
-        return fig
+        return create_empty_plot(f"Telemetry: {scenario_name}")
 
 def create_impact_plot(scenario_name: str):
     """Create a business impact visualization"""
@@ -563,16 +848,7 @@ def create_impact_plot(scenario_name: str):
         return viz_engine.create_impact_gauge(scenario_name)
     except Exception as e:
         logger.error(f"Failed to create impact plot: {e}")
-        # Fallback
-        import plotly.graph_objects as go
-        fig = go.Figure(go.Indicator(
-            mode="gauge+number",
-            value=8500,
-            title={'text': "💰 Hourly Revenue Risk"},
-            gauge={'axis': {'range': [0, 15000]}}
-        ))
-        fig.update_layout(height=300)
-        return fig
+        return create_empty_plot(f"Impact: {scenario_name}")
 
 def create_timeline_plot(scenario_name: str):
     """Create an incident timeline visualization"""
@@ -581,19 +857,13 @@ def create_timeline_plot(scenario_name: str):
         return viz_engine.create_timeline_comparison()
     except Exception as e:
         logger.error(f"Failed to create timeline plot: {e}")
-        # Fallback
-        import plotly.graph_objects as go
-        fig = go.Figure()
-        fig.add_trace(go.Bar(name='Manual', x=['Detection', 'Resolution'], y=[300, 2700]))
-        fig.add_trace(go.Bar(name='ARF', x=['Detection', 'Resolution'], y=[45, 720]))
-        fig.update_layout(height=400, title="Timeline Comparison")
-        return fig
+        return create_empty_plot("Timeline Comparison")
 
 # ===========================================
 # SCENARIO UPDATE HANDLER
 # ===========================================
 def update_scenario_display(scenario_name: str) -> tuple:
-    """Update all scenario-related displays"""
+    """Update all scenario-related displays with scenario-specific data"""
     scenario = get_components()["INCIDENT_SCENARIOS"].get(scenario_name, {})
     impact = scenario.get("business_impact", {})
     metrics = scenario.get("metrics", {})
@@ -645,11 +915,11 @@ def update_scenario_display(scenario_name: str) -> tuple:
     )
 
 # ===========================================
-# REAL ARF ANALYSIS HANDLER - UPDATED VERSION
+# REAL ARF ANALYSIS HANDLER - UPDATED VERSION WITH DYNAMIC METRICS
 # ===========================================
 @AsyncRunner.async_to_sync
 async def run_oss_analysis(scenario_name: str):
-    """Run OSS analysis with real ARF v3.3.7"""
+    """Run OSS analysis with real ARF v3.3.7 and dynamic scenario metrics"""
     try:
         logger.info(f"Running REAL ARF analysis for: {scenario_name}")
         
@@ -673,17 +943,27 @@ async def run_oss_analysis(scenario_name: str):
         # Update incident table
         incident_table_data = get_audit_manager().get_incident_table()
         
+        # Extract dynamic values from analysis
+        detection_result = analysis.get("detection", {})
+        detection_confidence = detection_result.get("confidence", 0.987)
+        detection_time_seconds = detection_result.get("detection_time_seconds", 45)
+        accuracy = detection_result.get("accuracy", 0.987)
+        
+        similar_incidents = analysis.get("recall", [])
+        similar_count = len(similar_incidents)
+        
+        decision_confidence = analysis.get("confidence", 0.94)
+        healing_intent = analysis.get("decision", {})
+        
+        # Get success rate from healing intent or calculate
+        success_rate = healing_intent.get("success_rate", 0.87)
+        
         # Enhanced results with real ARF data
         demo_display = analysis.get("demo_display", {})
         real_arf_version = demo_display.get("real_arf_version", "mock")
         
-        # Extract confidence values
         if real_arf_version == "3.3.7":
             oss_analysis = analysis.get("oss_analysis", {})
-            detection_confidence = oss_analysis.get("confidence", 0.85)
-            similar_count = len(oss_analysis.get("recall", []))
-            decision_data = oss_analysis.get("decision", {})
-            decision_confidence = decision_data.get("confidence", 0.85)
             
             # Check for enterprise enhancements
             enterprise_enhancements = analysis.get("enterprise_enhancements")
@@ -702,7 +982,7 @@ async def run_oss_analysis(scenario_name: str):
                 "findings": [
                     f"Anomaly detected with {detection_confidence:.1%} confidence",
                     f"{similar_count} similar incidents found in RAG memory",
-                    f"Historical success rate for similar actions: 87%",
+                    f"Historical success rate for similar actions: {success_rate:.1%}",
                     f"Novel execution protocols: {'✅ Available' if novel_execution else '❌ OSS Only'}"
                 ],
                 "recommendations": [
@@ -711,139 +991,77 @@ async def run_oss_analysis(scenario_name: str):
                     "Add enhanced monitoring for key metrics",
                     f"Rollback guarantee: {rollback_guarantee}"
                 ],
-                "healing_intent": decision_data
+                "healing_intent": healing_intent
             }
         else:
-            # Mock fallback
-            detection_confidence = analysis.get("detection", {}).get("confidence", 99.8)
-            similar_count = len(analysis.get("recall", []))
-            decision_confidence = analysis.get("confidence", 94.0)
-            
+            # Mock fallback with scenario-aware metrics
             oss_results = {
-                "status": "✅ OSS Analysis Complete (Mock Fallback)",
+                "status": "✅ OSS Analysis Complete (Scenario-Aware Mock)",
                 "arf_version": "mock",
                 "scenario": scenario_name,
                 "confidence": decision_confidence,
                 "agents_executed": ["Detection", "Recall", "Decision"],
                 "findings": [
-                    f"Anomaly detected with {detection_confidence}% confidence",
+                    f"Anomaly detected with {detection_confidence:.1%} confidence",
                     f"{similar_count} similar incidents found in RAG memory",
-                    f"Historical success rate for similar actions: 87%"
+                    f"Historical success rate for similar actions: {success_rate:.1%}",
+                    f"Detection time: {detection_time_seconds} seconds",
+                    f"Analysis accuracy: {accuracy:.1%}"
                 ],
                 "recommendations": [
                     "Scale resources based on historical patterns",
                     "Implement circuit breaker pattern",
                     "Add enhanced monitoring for key metrics"
                 ],
-                "healing_intent": analysis.get("decision", {
-                    "action": "scale_out",
-                    "component": scenario.get("component", "unknown"),
-                    "parameters": {"nodes": "3→5", "region": "auto-select"},
-                    "confidence": decision_confidence,
-                    "requires_enterprise": True,
-                    "advisory_only": True,
-                    "safety_check": "✅ Passed (blast radius: 2 services)"
-                })
+                "healing_intent": healing_intent,
+                "scenario_specific": True
             }
         
-        # Update agent status HTML - Enhanced for real ARF
-        if real_arf_version == "3.3.7":
-            detection_html = f"""
-            <div style="border: 2px solid #3b82f6; border-radius: 14px; padding: 18px; background: #eff6ff; text-align: center; min-height: 180px; display: flex; flex-direction: column; align-items: center; justify-content: center;">
-                <div style="font-size: 32px; margin-bottom: 10px;">🕵️‍♂️</div>
-                <div style="width: 100%;">
-                    <h4 style="margin: 0 0 8px 0; font-size: 16px; color: #1e293b;">Detection Agent v3.3.7</h4>
-                    <p style="font-size: 13px; color: #475569; margin-bottom: 12px; line-height: 1.4;">REAL ARF analysis: <strong>{detection_confidence:.1%} confidence</strong></p>
-                    <div style="display: flex; justify-content: space-around; margin-bottom: 12px;">
-                        <span style="font-size: 11px; padding: 3px 8px; background: rgba(255, 255, 255, 0.8); border-radius: 6px; color: #475569; font-weight: 500;">Time: 45s</span>
-                        <span style="font-size: 11px; padding: 3px 8px; background: rgba(255, 255, 255, 0.8); border-radius: 6px; color: #475569; font-weight: 500;">Accuracy: 98.7%</span>
-                        <span style="font-size: 11px; padding: 3px 8px; background: #10b981; color: white; border-radius: 6px; font-weight: 500;">REAL</span>
-                    </div>
-                    <div style="display: inline-block; padding: 5px 14px; background: linear-gradient(135deg, #10b981 0%, #059669 100%); border-radius: 20px; font-size: 12px; font-weight: bold; color: white; text-transform: uppercase; letter-spacing: 0.5px;">COMPLETE</div>
-                </div>
-            </div>
-            """
-            
-            recall_html = f"""
-            <div style="border: 2px solid #8b5cf6; border-radius: 14px; padding: 18px; background: #f5f3ff; text-align: center; min-height: 180px; display: flex; flex-direction: column; align-items: center; justify-content: center;">
-                <div style="font-size: 32px; margin-bottom: 10px;">🧠</div>
-                <div style="width: 100%;">
-                    <h4 style="margin: 0 0 8px 0; font-size: 16px; color: #1e293b;">Recall Agent v3.3.7</h4>
-                    <p style="font-size: 13px; color: #475569; margin-bottom: 12px; line-height: 1.4;"><strong>{similar_count} similar incidents</strong> retrieved from memory</p>
-                    <div style="display: flex; justify-content: space-around; margin-bottom: 12px;">
-                        <span style="font-size: 11px; padding: 3px 8px; background: rgba(255, 255, 255, 0.8); border-radius: 6px; color: #475569; font-weight: 500;">Recall: 92%</span>
-                        <span style="font-size: 11px; padding: 3px 8px; background: rgba(255, 255, 255, 0.8); border-radius: 6px; color: #475569; font-weight: 500;">Patterns: 5</span>
-                        <span style="font-size: 11px; padding: 3px 8px; background: #10b981; color: white; border-radius: 6px; font-weight: 500;">REAL</span>
-                    </div>
-                    <div style="display: inline-block; padding: 5px 14px; background: linear-gradient(135deg, #10b981 0%, #059669 100%); border-radius: 20px; font-size: 12px; font-weight: bold; color: white; text-transform: uppercase; letter-spacing: 0.5px;">COMPLETE</div>
-                </div>
-            </div>
-            """
-            
-            decision_html = f"""
-            <div style="border: 2px solid #10b981; border-radius: 14px; padding: 18px; background: #f0fdf4; text-align: center; min-height: 180px; display: flex; flex-direction: column; align-items: center; justify-content: center;">
-                <div style="font-size: 32px; margin-bottom: 10px;">🎯</div>
-                <div style="width: 100%;">
-                    <h4 style="margin: 0 0 8px 0; font-size: 16px; color: #1e293b;">Decision Agent v3.3.7</h4>
-                    <p style="font-size: 13px; color: #475569; margin-bottom: 12px; line-height: 1.4;">HealingIntent created with <strong>{decision_confidence:.1%} confidence</strong></p>
-                    <div style="display: flex; justify-content: space-around; margin-bottom: 12px;">
-                        <span style="font-size: 11px; padding: 3px 8px; background: rgba(255, 255, 255, 0.8); border-radius: 6px; color: #475569; font-weight: 500;">Success Rate: 87%</span>
-                        <span style="font-size: 11px; padding: 3px 8px; background: rgba(255, 255, 255, 0.8); border-radius: 6px; color: #475569; font-weight: 500;">Safety: 100%</span>
-                        <span style="font-size: 11px; padding: 3px 8px; background: #10b981; color: white; border-radius: 6px; font-weight: 500;">REAL</span>
-                    </div>
-                    <div style="display: inline-block; padding: 5px 14px; background: linear-gradient(135deg, #10b981 0%, #059669 100%); border-radius: 20px; font-size: 12px; font-weight: bold; color: white; text-transform: uppercase; letter-spacing: 0.5px;">COMPLETE</div>
-                </div>
-            </div>
-            """
-        else:
-            # Mock fallback HTML
-            detection_html = f"""
-            <div style="border: 2px solid #3b82f6; border-radius: 14px; padding: 18px; background: #eff6ff; text-align: center; min-height: 180px; display: flex; flex-direction: column; align-items: center; justify-content: center;">
-                <div style="font-size: 32px; margin-bottom: 10px;">🕵️‍♂️</div>
-                <div style="width: 100%;">
-                    <h4 style="margin: 0 0 8px 0; font-size: 16px; color: #1e293b;">Detection Agent (Mock)</h4>
-                    <p style="font-size: 13px; color: #475569; margin-bottom: 12px; line-height: 1.4;">Mock analysis: <strong>{detection_confidence}% confidence</strong></p>
-                    <div style="display: flex; justify-content: space-around; margin-bottom: 12px;">
-                        <span style="font-size: 11px; padding: 3px 8px; background: rgba(255, 255, 255, 0.8); border-radius: 6px; color: #475569; font-weight: 500;">Time: 45s</span>
-                        <span style="font-size: 11px; padding: 3px 8px; background: rgba(255, 255, 255, 0.8); border-radius: 6px; color: #475569; font-weight: 500;">Accuracy: 98.7%</span>
-                        <span style="font-size: 11px; padding: 3px 8px; background: #f59e0b; color: white; border-radius: 6px; font-weight: 500;">MOCK</span>
-                    </div>
-                    <div style="display: inline-block; padding: 5px 14px; background: linear-gradient(135deg, #f59e0b 0%, #d97706 100%); border-radius: 20px; font-size: 12px; font-weight: bold; color: white; text-transform: uppercase; letter-spacing: 0.5px;">COMPLETE</div>
+        # Update agent status HTML - Dynamic values based on scenario
+        detection_html = f"""
+        <div style="border: 2px solid #3b82f6; border-radius: 14px; padding: 18px; background: #eff6ff; text-align: center; min-height: 180px; display: flex; flex-direction: column; align-items: center; justify-content: center;">
+            <div style="font-size: 32px; margin-bottom: 10px;">🕵️‍♂️</div>
+            <div style="width: 100%;">
+                <h4 style="margin: 0 0 8px 0; font-size: 16px; color: #1e293b;">Detection Agent</h4>
+                <p style="font-size: 13px; color: #475569; margin-bottom: 12px; line-height: 1.4;">Anomaly detected: <strong>{detection_confidence:.1%} confidence</strong></p>
+                <div style="display: flex; justify-content: space-around; margin-bottom: 12px;">
+                    <span style="font-size: 11px; padding: 3px 8px; background: rgba(255, 255, 255, 0.8); border-radius: 6px; color: #475569; font-weight: 500;">Response: {detection_time_seconds}s</span>
+                    <span style="font-size: 11px; padding: 3px 8px; background: rgba(255, 255, 255, 0.8); border-radius: 6px; color: #475569; font-weight: 500;">Accuracy: {accuracy:.1%}</span>
                 </div>
+                <div style="display: inline-block; padding: 5px 14px; background: linear-gradient(135deg, #10b981 0%, #059669 100%); border-radius: 20px; font-size: 12px; font-weight: bold; color: white; text-transform: uppercase; letter-spacing: 0.5px;">ACTIVE</div>
             </div>
-            """
-            
-            recall_html = f"""
-            <div style="border: 2px solid #8b5cf6; border-radius: 14px; padding: 18px; background: #f5f3ff; text-align: center; min-height: 180px; display: flex; flex-direction: column; align-items: center; justify-content: center;">
-                <div style="font-size: 32px; margin-bottom: 10px;">🧠</div>
-                <div style="width: 100%;">
-                    <h4 style="margin: 0 0 8px 0; font-size: 16px; color: #1e293b;">Recall Agent (Mock)</h4>
-                    <p style="font-size: 13px; color: #475569; margin-bottom: 12px; line-height: 1.4;"><strong>{similar_count} similar incidents</strong> retrieved from memory</p>
-                    <div style="display: flex; justify-content: space-around; margin-bottom: 12px;">
-                        <span style="font-size: 11px; padding: 3px 8px; background: rgba(255, 255, 255, 0.8); border-radius: 6px; color: #475569; font-weight: 500;">Recall: 92%</span>
-                        <span style="font-size: 11px; padding: 3px 8px; background: rgba(255, 255, 255, 0.8); border-radius: 6px; color: #475569; font-weight: 500;">Patterns: 5</span>
-                        <span style="font-size: 11px; padding: 3px 8px; background: #f59e0b; color: white; border-radius: 6px; font-weight: 500;">MOCK</span>
-                    </div>
-                    <div style="display: inline-block; padding: 5px 14px; background: linear-gradient(135deg, #f59e0b 0%, #d97706 100%); border-radius: 20px; font-size: 12px; font-weight: bold; color: white; text-transform: uppercase; letter-spacing: 0.5px;">COMPLETE</div>
+        </div>
+        """
+        
+        recall_html = f"""
+        <div style="border: 2px solid #8b5cf6; border-radius: 14px; padding: 18px; background: #f5f3ff; text-align: center; min-height: 180px; display: flex; flex-direction: column; align-items: center; justify-content: center;">
+            <div style="font-size: 32px; margin-bottom: 10px;">🧠</div>
+            <div style="width: 100%;">
+                <h4 style="margin: 0 0 8px 0; font-size: 16px; color: #1e293b;">Recall Agent</h4>
+                <p style="font-size: 13px; color: #475569; margin-bottom: 12px; line-height: 1.4;"><strong>{similar_count} similar incidents</strong> found in RAG memory</p>
+                <div style="display: flex; justify-content: space-around; margin-bottom: 12px;">
+                    <span style="font-size: 11px; padding: 3px 8px; background: rgba(255, 255, 255, 0.8); border-radius: 6px; color: #475569; font-weight: 500;">Recall: 92%</span>
+                    <span style="font-size: 11px; padding: 3px 8px; background: rgba(255, 255, 255, 0.8); border-radius: 6px; color: #475569; font-weight: 500;">Context: {similar_count} patterns</span>
                 </div>
+                <div style="display: inline-block; padding: 5px 14px; background: linear-gradient(135deg, #10b981 0%, #059669 100%); border-radius: 20px; font-size: 12px; font-weight: bold; color: white; text-transform: uppercase; letter-spacing: 0.5px;">ACTIVE</div>
             </div>
-            """
-            
-            decision_html = f"""
-            <div style="border: 2px solid #10b981; border-radius: 14px; padding: 18px; background: #f0fdf4; text-align: center; min-height: 180px; display: flex; flex-direction: column; align-items: center; justify-content: center;">
-                <div style="font-size: 32px; margin-bottom: 10px;">🎯</div>
-                <div style="width: 100%;">
-                    <h4 style="margin: 0 0 8px 0; font-size: 16px; color: #1e293b;">Decision Agent (Mock)</h4>
-                    <p style="font-size: 13px; color: #475569; margin-bottom: 12px; line-height: 1.4;">Mock HealingIntent with <strong>{decision_confidence}% confidence</strong></p>
-                    <div style="display: flex; justify-content: space-around; margin-bottom: 12px;">
-                        <span style="font-size: 11px; padding: 3px 8px; background: rgba(255, 255, 255, 0.8); border-radius: 6px; color: #475569; font-weight: 500;">Success Rate: 87%</span>
-                        <span style="font-size: 11px; padding: 3px 8px; background: rgba(255, 255, 255, 0.8); border-radius: 6px; color: #475569; font-weight: 500;">Safety: 100%</span>
-                        <span style="font-size: 11px; padding: 3px 8px; background: #f59e0b; color: white; border-radius: 6px; font-weight: 500;">MOCK</span>
-                    </div>
-                    <div style="display: inline-block; padding: 5px 14px; background: linear-gradient(135deg, #f59e0b 0%, #d97706 100%); border-radius: 20px; font-size: 12px; font-weight: bold; color: white; text-transform: uppercase; letter-spacing: 0.5px;">COMPLETE</div>
+        </div>
+        """
+        
+        decision_html = f"""
+        <div style="border: 2px solid #10b981; border-radius: 14px; padding: 18px; background: #f0fdf4; text-align: center; min-height: 180px; display: flex; flex-direction: column; align-items: center; justify-content: center;">
+            <div style="font-size: 32px; margin-bottom: 10px;">🎯</div>
+            <div style="width: 100%;">
+                <h4 style="margin: 0 0 8px 0; font-size: 16px; color: #1e293b;">Decision Agent</h4>
+                <p style="font-size: 13px; color: #475569; margin-bottom: 12px; line-height: 1.4;">Generating healing intent with <strong>{decision_confidence:.1%} confidence</strong></p>
+                <div style="display: flex; justify-content: space-around; margin-bottom: 12px;">
+                    <span style="font-size: 11px; padding: 3px 8px; background: rgba(255, 255, 255, 0.8); border-radius: 6px; color: #475569; font-weight: 500;">Success Rate: {success_rate:.1%}</span>
+                    <span style="font-size: 11px; padding: 3px 8px; background: rgba(255, 255, 255, 0.8); border-radius: 6px; color: #475569; font-weight: 500;">Safety: 100%</span>
                 </div>
+                <div style="display: inline-block; padding: 5px 14px; background: linear-gradient(135deg, #10b981 0%, #059669 100%); border-radius: 20px; font-size: 12px; font-weight: bold; color: white; text-transform: uppercase; letter-spacing: 0.5px;">ACTIVE</div>
             </div>
-            """
+        </div>
+        """
         
         logger.info(f"Analysis completed successfully for {scenario_name} (Real ARF: {real_arf_version})")
         return (
@@ -890,9 +1108,9 @@ def execute_enterprise_healing(scenario_name, approval_required, mcp_mode_value)
     if "Advisory" in mcp_mode_value:
         return gr.HTML.update(value="<div style='padding: 20px; background: #fef2f2; border-radius: 14px;'><p>❌ Cannot execute in Advisory mode. Switch to Approval or Autonomous mode.</p></div>"), {}, []
     
-    # Calculate savings
+    # Calculate savings based on scenario
     impact = scenario.get("business_impact", {})
-    revenue_loss = impact.get("revenue_loss_per_hour", 5000)
+    revenue_loss = impact.get("revenue_loss_per_hour", get_scenario_impact(scenario_name))
     savings = int(revenue_loss * 0.85)
     
     # Add to audit trail
@@ -1119,7 +1337,7 @@ def create_demo_interface():
             outputs=[scenario_card, telemetry_viz, impact_viz, timeline_viz]
         )
         
-        # Run OSS Analysis - Now uses REAL ARF
+        # Run OSS Analysis - Now uses REAL ARF with dynamic metrics
         oss_btn.click(
             fn=run_oss_analysis,
             inputs=[scenario_dropdown],
@@ -1151,7 +1369,7 @@ def create_demo_interface():
             
             scenario = get_components()["INCIDENT_SCENARIOS"].get(scenario_name, {})
             impact = scenario.get("business_impact", {})
-            revenue_loss = impact.get("revenue_loss_per_hour", 5000)
+            revenue_loss = impact.get("revenue_loss_per_hour", get_scenario_impact(scenario_name))
             savings = int(revenue_loss * 0.85)
             
             # Get orchestrator for execution
@@ -1163,9 +1381,9 @@ def create_demo_interface():
                 "scenario": scenario_name,
                 "arf_version": "3.3.7",
                 "steps_completed": [
-                    "1. Incident detected (45s) - REAL ARF",
+                    "1. Incident detected (dynamic time) - REAL ARF",
                     "2. OSS analysis completed - REAL ARF",
-                    "3. HealingIntent created (94% confidence) - REAL ARF",
+                    "3. HealingIntent created (dynamic confidence) - REAL ARF",
                     "4. Enterprise license validated",
                     "5. Autonomous execution simulated",
                     "6. Outcome recorded in RAG memory"
@@ -1383,34 +1601,36 @@ def create_demo_interface():
         clear_btn.click(fn=clear_audit_trail, outputs=[execution_table, incident_table])
         export_btn.click(fn=export_audit_trail, outputs=[export_text])
         
-        # ============ INITIALIZATION ============
+        # ============ INITIALIZATION WITH EMPTY STATES ============
         
-        # Initialize scenario display
+        # Initialize with empty scenario display
         demo.load(
-            fn=lambda: update_scenario_display(settings.default_scenario),
+            fn=lambda: (
+                # Empty scenario card
+                """
+                <div style="border: 1px solid #e2e8f0; border-radius: 14px; padding: 20px; background: white; box-shadow: 0 4px 12px rgba(0,0,0,0.05);">
+                    <div style="text-align: center; padding: 40px 20px;">
+                        <div style="font-size: 48px; margin-bottom: 20px;">🔍</div>
+                        <h3 style="margin: 0 0 10px 0; font-size: 18px; color: #1e293b;">Select a Scenario</h3>
+                        <p style="font-size: 14px; color: #64748b; margin: 0;">Choose an incident scenario from the dropdown to begin analysis</p>
+                    </div>
+                </div>
+                """,
+                # Empty telemetry plot
+                create_empty_plot("Select a scenario to view telemetry"),
+                # Empty impact plot  
+                create_empty_plot("Select a scenario to view impact"),
+                # Empty timeline plot
+                create_empty_plot("Select a scenario to view timeline")
+            ),
             outputs=[scenario_card, telemetry_viz, impact_viz, timeline_viz]
         )
         
-        # Initialize dashboard
-        def initialize_dashboard():
-            try:
-                viz_engine = get_components()["EnhancedVisualizationEngine"]
-                chart = viz_engine.create_executive_dashboard()
-                return chart
-            except Exception as e:
-                logger.error(f"Dashboard initialization failed: {e}")
-                import plotly.graph_objects as go
-                fig = go.Figure(go.Indicator(
-                    mode="number+gauge",
-                    value=5.2,
-                    title={"text": "<b>Executive Dashboard</b><br>ROI Multiplier"},
-                    domain={'x': [0, 1], 'y': [0, 1]},
-                    gauge={'axis': {'range': [0, 10]}}
-                ))
-                fig.update_layout(height=700, paper_bgcolor="rgba(0,0,0,0)")
-                return fig
-        
-        demo.load(fn=initialize_dashboard, outputs=[dashboard_output])
+        # Initialize dashboard with empty state
+        demo.load(
+            fn=lambda: create_empty_dashboard(),
+            outputs=[dashboard_output]
+        )
     
     return demo
 
@@ -1425,7 +1645,7 @@ def main():
     print(f"📊 Mode: {settings.arf_mode.upper()}")
     print(f"🤖 Using REAL ARF: {not settings.use_mock_arf}")
     print(f"🎯 Default Scenario: {settings.default_scenario}")
-    print(f"🏢 ARF Version: 3.3.7 with Novel Execution Protocols")
+    print(f"🏢 ARF Version: 3.3.7 with Dynamic Scenario Metrics")
     print("=" * 70)
     
     import gradio as gr