Rename hf_demo.py to app.py

app.py

@@ -0,0 +1,304 @@
+"""
+Enterprise-Grade FastAPI Backend for ARF OSS Demo
+Uses real ARF components, no simulation
+"""
+from fastapi import FastAPI, HTTPException, Depends
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel, Field
+from typing import Optional, List, Dict, Any
+import uuid
+from datetime import datetime
+import logging
+
+# Real ARF OSS imports
+from agentic_reliability_framework.engine import (
+    v3_reliability,
+    healing_policies,
+    mcp_client,
+    business
+)
+from agentic_reliability_framework.memory import rag_graph
+
+from arf_orchestrator import ARFOrchestrator
+from memory_store import ARFMemoryStore
+
+# Configure logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+# Initialize FastAPI
+app = FastAPI(
+    title="ARF OSS Real Engine",
+    version="3.3.9",
+    description="Real ARF OSS backend - Bayesian risk, RAG memory, MCP client"
+)
+
+# CORS for Replit UI
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],  # Replit domains will be added
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# ============== PYDANTIC MODELS ==============
+# Match Replit UI exactly
+
+class ActionRequest(BaseModel):
+    """Matches Replit UI's action structure"""
+    id: Optional[int] = None
+    incidentId: Optional[int] = None
+    description: str = Field(..., description="Human-readable description")
+    proposedAction: str = Field(..., description="Actual command")
+    confidenceScore: float = Field(..., ge=0.0, le=1.0)
+    riskLevel: str = Field(..., regex="^(LOW|MEDIUM|HIGH|CRITICAL)$")
+    requiredLevel: Optional[str] = None
+    requiresHuman: bool = False
+    rollbackFeasible: bool = True
+    metadata: Optional[Dict[str, Any]] = None
+
+class ConfigUpdateRequest(BaseModel):
+    confidenceThreshold: Optional[float] = Field(None, ge=0.5, le=1.0)
+    maxAutonomousRisk: Optional[str] = Field(None, regex="^(LOW|MEDIUM|HIGH|CRITICAL)$")
+    riskScoreThresholds: Optional[Dict[str, float]] = None
+
+class GateResult(BaseModel):
+    """Matches Replit UI's gate display"""
+    gate: str
+    reason: str
+    passed: bool
+    threshold: Optional[float] = None
+    actual: Optional[float] = None
+    metadata: Optional[Dict[str, Any]] = None
+
+class EvaluationResponse(BaseModel):
+    """Matches Replit UI's expected response"""
+    allowed: bool
+    requiredLevel: str
+    gatesTriggered: List[GateResult]
+    shouldEscalate: bool
+    escalationReason: Optional[str] = None
+    executionLadder: Optional[Dict[str, Any]] = None
+
+# ============== INITIALIZE REAL ARF ==============
+arf = ARFOrchestrator()
+memory = ARFMemoryStore()  # Light persistence with RAG
+
+# ============== API ENDPOINTS ==============
+
+@app.get("/api/v1/config")
+async def get_config():
+    """Get current ARF configuration - real OSS config"""
+    return {
+        "confidenceThreshold": arf.policy_engine.config.confidence_threshold,
+        "maxAutonomousRisk": arf.policy_engine.config.max_autonomous_risk,
+        "riskScoreThresholds": arf.policy_engine.config.risk_thresholds
+    }
+
+@app.post("/api/v1/config")
+async def update_config(config: ConfigUpdateRequest):
+    """Update ARF configuration - live updates"""
+    try:
+        if config.confidenceThreshold:
+            arf.policy_engine.update_confidence_threshold(config.confidenceThreshold)
+        
+        if config.maxAutonomousRisk:
+            arf.policy_engine.update_max_risk(config.maxAutonomousRisk)
+        
+        # Log config change for audit
+        logger.info(f"Config updated: {config.dict(exclude_unset=True)}")
+        
+        return await get_config()
+    except Exception as e:
+        logger.error(f"Config update failed: {e}")
+        raise HTTPException(status_code=400, detail=str(e))
+
+@app.post("/api/v1/evaluate")
+async def evaluate_action(action: ActionRequest):
+    """
+    Real ARF OSS evaluation pipeline
+    Used by Replit UI's ARFPlayground component
+    """
+    try:
+        start_time = datetime.utcnow()
+        
+        # 1. Bayesian risk assessment (real)
+        risk_assessment = arf.risk_engine.assess(
+            action_text=action.proposedAction,
+            context={
+                "description": action.description,
+                "risk_level": action.riskLevel,
+                "requires_human": action.requiresHuman,
+                "rollback_feasible": action.rollbackFeasible
+            }
+        )
+        
+        # 2. MCP client check (real)
+        mcp_result = await arf.mcp_client.evaluate(
+            action=action.proposedAction,
+            risk_score=risk_assessment.score,
+            confidence=action.confidenceScore
+        )
+        
+        # 3. Policy evaluation (real OSS - advisory)
+        policy_result = arf.policy_engine.evaluate(
+            action=action.proposedAction,
+            risk_assessment=risk_assessment,
+            confidence=action.confidenceScore,
+            mode="advisory"  # OSS mode
+        )
+        
+        # 4. RAG memory recall (light persistence)
+        similar_incidents = memory.find_similar(
+            action=action.proposedAction,
+            risk_score=risk_assessment.score,
+            limit=5
+        )
+        
+        # 5. Build gate results for Replit UI
+        gates = [
+            GateResult(
+                gate="confidence_threshold",
+                reason=f"Confidence {action.confidenceScore:.2f} meets threshold {arf.policy_engine.config.confidence_threshold}" 
+                       if action.confidenceScore >= arf.policy_engine.config.confidence_threshold
+                       else f"Confidence {action.confidenceScore:.2f} below threshold {arf.policy_engine.config.confidence_threshold}",
+                passed=action.confidenceScore >= arf.policy_engine.config.confidence_threshold,
+                threshold=arf.policy_engine.config.confidence_threshold,
+                actual=action.confidenceScore
+            ),
+            GateResult(
+                gate="risk_assessment",
+                reason=f"Risk level {action.riskLevel} within autonomous range (≤ {arf.policy_engine.config.max_autonomous_risk})"
+                       if arf._risk_level_allowed(action.riskLevel)
+                       else f"Risk level {action.riskLevel} exceeds autonomous threshold",
+                passed=arf._risk_level_allowed(action.riskLevel),
+                metadata={
+                    "maxAutonomousRisk": arf.policy_engine.config.max_autonomous_risk,
+                    "actionRisk": action.riskLevel
+                }
+            ),
+            GateResult(
+                gate="rollback_feasibility",
+                reason="Non-destructive operation" if not arf._is_destructive(action.proposedAction)
+                       else "Has rollback plan" if action.rollbackFeasible
+                       else "Destructive operation lacks rollback plan",
+                passed=not arf._is_destructive(action.proposedAction) or action.rollbackFeasible,
+                metadata={
+                    "isDestructive": arf._is_destructive(action.proposedAction),
+                    "requiresRollback": arf._is_destructive(action.proposedAction)
+                }
+            ),
+            GateResult(
+                gate="human_review",
+                reason="Human review not required" if not action.requiresHuman
+                       else "Human review required by policy",
+                passed=not action.requiresHuman,
+                metadata={"policyRequiresHuman": action.requiresHuman}
+            ),
+            GateResult(
+                gate="license_check",
+                reason="OSS edition - advisory only",
+                passed=True,  # OSS always passes license check
+                metadata={"licenseSensitive": False, "edition": "OSS"}
+            )
+        ]
+        
+        # Add MCP result as gate
+        if mcp_result:
+            gates.append(GateResult(
+                gate="mcp_validation",
+                reason=mcp_result.reason,
+                passed=mcp_result.passed,
+                metadata=mcp_result.metadata
+            ))
+        
+        # Add novel action check if similar incidents exist
+        if similar_incidents and len(similar_incidents) < 2:
+            gates.append(GateResult(
+                gate="novel_action_review",
+                reason="Action pattern rarely seen in historical data",
+                passed=False,
+                metadata={"similar_count": len(similar_incidents)}
+            ))
+        
+        # Determine final decision
+        all_passed = all(g.passed for g in gates)
+        
+        # Store in memory for future recall
+        memory.store_evaluation(
+            action=action.proposedAction,
+            risk_score=risk_assessment.score,
+            gates=gates,
+            allowed=all_passed,
+            timestamp=start_time
+        )
+        
+        # Log for lead scoring
+        logger.info(f"Evaluation complete: action={action.description[:30]}..., allowed={all_passed}")
+        
+        # Track enterprise interest signals
+        if not all_passed and any(g.gate == "novel_action_review" for g in gates if not g.passed):
+            # Novel action that would need Enterprise review board
+            memory.track_enterprise_signal("novel_action", action.proposedAction)
+        elif risk_assessment.score > 0.8 and not all_passed:
+            memory.track_enterprise_signal("high_risk_blocked", action.proposedAction)
+        
+        return EvaluationResponse(
+            allowed=all_passed,
+            requiredLevel=arf._determine_required_level(all_passed, action.riskLevel),
+            gatesTriggered=gates,
+            shouldEscalate=not all_passed,
+            escalationReason=None if all_passed else "Failed mechanical gates",
+            executionLadder=arf._build_execution_ladder(gates)
+        )
+        
+    except Exception as e:
+        logger.error(f"Evaluation failed: {e}", exc_info=True)
+        raise HTTPException(status_code=500, detail=str(e))
+
+@app.get("/api/v1/memory/similar")
+async def get_similar_actions(action: str, limit: int = 5):
+    """RAG memory recall - similar historical evaluations"""
+    return memory.find_similar(action, limit=limit)
+
+@app.get("/api/v1/audit/stream")
+async def get_audit_logs(limit: int = 50):
+    """Audit stream for Replit UI"""
+    return memory.get_recent_logs(limit)
+
+@app.post("/api/v1/process")
+async def process_action(action: ActionRequest):
+    """
+    Full ARF pipeline with MCP
+    Still advisory only in OSS
+    """
+    evaluation = await evaluate_action(action)
+    
+    # In OSS, always advisory
+    return {
+        "evaluation": evaluation.dict(),
+        "execution": {
+            "status": "advisory_only",
+            "message": "OSS edition provides advisory only. Enterprise adds execution.",
+            "would_execute": evaluation.allowed and not evaluation.shouldEscalate
+        },
+        "next_steps": {
+            "enterprise_demo": "https://calendly.com/petter2025us/arf-demo" if evaluation.allowed else None
+        }
+    }
+
+@app.get("/api/v1/enterprise/signals")
+async def get_enterprise_signals():
+    """Lead intelligence - actions that indicate Enterprise need"""
+    return memory.get_enterprise_signals()
+
+# Health check
+@app.get("/health")
+async def health_check():
+    return {
+        "status": "healthy",
+        "arf_version": "3.3.9",
+        "oss_mode": True,
+        "memory_enabled": memory.is_enabled
+    }

hf_demo.py

@@ -1,1249 +0,0 @@
-# COMPLETE FIXED hf_demo.py with Gradio 4.x for Hugging Face Spaces
-# ARF 3.3.9 DEMO WITH PROPER HUGGING FACE SPACES COMPATIBILITY
-
-import gradio as gr
-import time
-import random
-import json
-import uuid
-import subprocess
-import sys
-import importlib
-import os
-import threading
-import socket
-from datetime import datetime, timedelta
-from typing import Dict, List, Optional, Tuple, Any, Union
-import numpy as np
-
-# ============== FASTAPI INTEGRATION ==============
-try:
-    from fastapi import FastAPI, HTTPException
-    from fastapi.middleware.cors import CORSMiddleware
-    from pydantic import BaseModel, Field
-    from gradio import mount_gradio_app
-    from typing import Optional
-    FASTAPI_AVAILABLE = True
-    print("✅ FastAPI available")
-except ImportError as e:
-    print(f"⚠️ FastAPI not available: {e}")
-    FASTAPI_AVAILABLE = False
-    
-    # Create dummy classes if FastAPI not installed
-    class BaseModel:
-        def dict(self): return {}
-    class FastAPI: pass
-    class HTTPException(Exception): pass
-    class CORSMiddleware: pass
-    def Field(*args, **kwargs): return None
-    Optional = lambda x: x
-
-if FASTAPI_AVAILABLE:
-    # Create FastAPI app
-    api_app = FastAPI(title="ARF Mathematical Engine", version="3.3.9")
-
-    # Add CORS middleware
-    api_app.add_middleware(
-        CORSMiddleware,
-        allow_origins=["*"],  # In production, restrict to your Replit domain
-        allow_credentials=True,
-        allow_methods=["*"],
-        allow_headers=["*"],
-    )
-
-    # ============== IN-MEMORY CONFIGURATION STORAGE ==============
-    # This is the key fix - persistent storage for config
-    current_config = {
-        "confidenceThreshold": 0.9,
-        "maxAutonomousRisk": "MEDIUM",
-        "riskScoreThresholds": {
-            "LOW": 0.7,
-            "MEDIUM": 0.5,
-            "HIGH": 0.3,
-            "CRITICAL": 0.1
-        }
-    }
-
-    # Define Pydantic models
-    class ActionEvaluationRequest(BaseModel):
-        proposed_action: str = Field(..., description="The command the AI wants to execute")
-        confidence_score: float = Field(..., ge=0.0, le=1.0, description="AI confidence score")
-        risk_level: str = Field(..., description="Risk level (LOW/MEDIUM/HIGH/CRITICAL)")
-        requires_human: bool = Field(..., description="Whether action requires human oversight")
-        rollback_feasible: bool = Field(..., description="Whether action can be rolled back")
-        description: Optional[str] = Field(None, description="Optional action description")
-        incident_id: Optional[int] = Field(None, description="Optional incident ID")
-
-    class GateEvaluationResponse(BaseModel):
-        gate: str
-        reason: str
-        passed: bool
-        threshold: Optional[float] = None
-        actual: Optional[float] = None
-        metadata: Optional[dict] = None
-
-    class ActionEvaluationResponse(BaseModel):
-        allowed: bool
-        required_level: str
-        gates_triggered: list[GateEvaluationResponse]
-        should_escalate: bool
-        escalation_reason: Optional[str] = None
-
-    class ConfigResponse(BaseModel):
-        confidenceThreshold: float
-        maxAutonomousRisk: str
-        riskScoreThresholds: dict
-
-    class ConfigUpdateRequest(BaseModel):
-        confidenceThreshold: Optional[float] = Field(None, ge=0.5, le=1.0)
-        maxAutonomousRisk: Optional[str] = Field(None, pattern="^(LOW|MEDIUM|HIGH|CRITICAL)$")
-
-    # ============== CONFIGURATION ENDPOINTS ==============
-    
-    @api_app.get("/api/v1/config", response_model=ConfigResponse)
-    async def get_config():
-        """Get current ARF configuration"""
-        print(f"📊 GET /api/v1/config -> {current_config}")
-        return current_config
-
-    @api_app.post("/api/v1/config", response_model=ConfigResponse)
-    async def update_config(config_update: ConfigUpdateRequest):
-        """Update ARF configuration"""
-        global current_config
-        print(f"🔄 POST /api/v1/config with: {config_update}")
-        
-        # Update only the fields that were sent
-        if config_update.confidenceThreshold is not None:
-            current_config["confidenceThreshold"] = config_update.confidenceThreshold
-            print(f"   Updated confidenceThreshold to {config_update.confidenceThreshold}")
-        
-        if config_update.maxAutonomousRisk is not None:
-            current_config["maxAutonomousRisk"] = config_update.maxAutonomousRisk
-            print(f"   Updated maxAutonomousRisk to {config_update.maxAutonomousRisk}")
-        
-        print(f"✅ New config: {current_config}")
-        return current_config
-
-    # ============== EVALUATION ENDPOINTS ==============
-    
-    @api_app.post("/api/v1/evaluate", response_model=ActionEvaluationResponse)
-    async def evaluate_action(request: ActionEvaluationRequest):
-        """Evaluate an action using mathematical Bayesian assessment"""
-        try:
-            print(f"🔍 Evaluating action: {request.proposed_action}")
-            print(f"   Using config: confidence={current_config['confidenceThreshold']}, maxRisk={current_config['maxAutonomousRisk']}")
-            
-            gates = []
-            
-            # Confidence gate - using current_config
-            confidence_passed = request.confidence_score >= current_config["confidenceThreshold"]
-            gates.append(GateEvaluationResponse(
-                gate="confidence_threshold",
-                reason=f"Confidence {request.confidence_score:.2f} meets threshold {current_config['confidenceThreshold']}" if confidence_passed 
-                       else f"Confidence {request.confidence_score:.2f} below threshold {current_config['confidenceThreshold']}",
-                passed=confidence_passed,
-                threshold=current_config["confidenceThreshold"],
-                actual=request.confidence_score
-            ))
-            
-            # Risk gate - using current_config
-            risk_levels = ["LOW", "MEDIUM", "HIGH", "CRITICAL"]
-            max_risk_index = risk_levels.index(current_config["maxAutonomousRisk"])
-            action_risk_index = risk_levels.index(request.risk_level)
-            risk_passed = action_risk_index <= max_risk_index
-            
-            gates.append(GateEvaluationResponse(
-                gate="risk_assessment",
-                reason=f"Risk level {request.risk_level} within autonomous range (≤ {current_config['maxAutonomousRisk']})" if risk_passed
-                       else f"Risk level {request.risk_level} exceeds autonomous threshold (max: {current_config['maxAutonomousRisk']})",
-                passed=risk_passed,
-                metadata={"maxAutonomousRisk": current_config["maxAutonomousRisk"], "actionRisk": request.risk_level}
-            ))
-            
-            # Rollback gate
-            destructive_keywords = ['delete', 'drop', 'terminate', 'remove', 'destroy']
-            is_destructive = any(keyword in request.proposed_action.lower() for keyword in destructive_keywords)
-            rollback_passed = not is_destructive or request.rollback_feasible
-            gates.append(GateEvaluationResponse(
-                gate="rollback_feasibility",
-                reason="Non-destructive operation" if not is_destructive
-                       else "Has rollback plan" if request.rollback_feasible
-                       else "Destructive operation lacks rollback plan",
-                passed=rollback_passed,
-                metadata={"isDestructive": is_destructive, "requiresRollback": is_destructive}
-            ))
-            
-            # Human review gate
-            human_passed = not request.requires_human
-            gates.append(GateEvaluationResponse(
-                gate="human_review",
-                reason="Human review not required" if human_passed else "Human review required by policy",
-                passed=human_passed,
-                metadata={"policyRequiresHuman": request.requires_human}
-            ))
-            
-            # License gate (always passes in this simulation)
-            gates.append(GateEvaluationResponse(
-                gate="license_check",
-                reason="No license violations detected",
-                passed=True,
-                metadata={"licenseSensitive": False}
-            ))
-            
-            all_passed = all(g.passed for g in gates)
-            
-            # Determine required level based on gates and config
-            if all_passed:
-                if request.risk_level == "LOW":
-                    required_level = "AUTONOMOUS_LOW"
-                elif request.risk_level == "MEDIUM":
-                    required_level = "AUTONOMOUS_HIGH"
-                else:
-                    required_level = "SUPERVISED"
-            else:
-                required_level = "OPERATOR_REVIEW"
-            
-            result = ActionEvaluationResponse(
-                allowed=all_passed,
-                required_level=required_level,
-                gates_triggered=gates,
-                should_escalate=not all_passed,
-                escalation_reason=None if all_passed else "Failed critical gates"
-            )
-            
-            print(f"✅ Evaluation complete: allowed={result.allowed}, required_level={result.required_level}")
-            return result
-            
-        except Exception as e:
-            print(f"❌ Evaluation error: {e}")
-            raise HTTPException(status_code=500, detail=str(e))
-
-    @api_app.post("/api/v1/process")
-    async def process_action(request: ActionEvaluationRequest):
-        """Process action through full ARF pipeline"""
-        print(f"⚙️ Processing action: {request.proposed_action}")
-        evaluation = await evaluate_action(request)
-        
-        # Determine final status based on evaluation
-        if evaluation.allowed and not evaluation.should_escalate:
-            final_status = "executed"
-        elif evaluation.should_escalate:
-            final_status = "needs_approval"
-        else:
-            final_status = "blocked"
-        
-        result = {
-            "action": request.dict(),
-            "evaluation": evaluation.dict(),
-            "finalStatus": final_status
-        }
-        print(f"✅ Process complete: {final_status}")
-        return result
-
-    @api_app.post("/api/v1/simulate")
-    async def simulate_action(request: ActionEvaluationRequest, config: dict = None):
-        """Simulate action with temporary configuration"""
-        print(f"🎮 Simulating action with custom config: {config}")
-        evaluation = await evaluate_action(request)
-        return evaluation
-
-    print("\n" + "="*80)
-    print("✅ FASTAPI ENDPOINTS CONFIGURED")
-    print("="*80)
-    print("   📍 GET  /api/v1/config")
-    print("   📍 POST /api/v1/config")
-    print("   📍 POST /api/v1/evaluate")
-    print("   📍 POST /api/v1/process")
-    print("   📍 POST /api/v1/simulate")
-    print("="*80 + "\n")
-
-# ============== HUGGING FACE SPACES DETECTION ==============
-def is_huggingface_spaces():
-    """Detect if running in Hugging Face Spaces environment"""
-    return os.environ.get('SPACE_ID') is not None or \
-           os.environ.get('HF_SPACE') is not None or \
-           os.environ.get('SYSTEM') == 'spaces' or \
-           os.path.exists('/.dockerenv') and 'space' in os.environ.get('HOSTNAME', '')
-
-# Set environment variables for Hugging Face Spaces
-if is_huggingface_spaces():
-    os.environ['GRADIO_ANALYTICS_ENABLED'] = 'False'
-    os.environ['GRADIO_SERVER_NAME'] = '0.0.0.0'
-    os.environ['GRADIO_SERVER_PORT'] = '7860'
-
-# Import enhanced engines
-try:
-    from utils.arf_engine_enhanced import EnhancedARFEngine, BayesianRiskAssessment, RiskCategory
-    from utils.psychology_layer_enhanced import EnhancedPsychologyEngine
-    ARF_ENGINE_ENHANCED = True
-    print("✅ Enhanced ARF Engine loaded successfully")
-except ImportError as e:
-    print(f"⚠️ Enhanced engines not available: {e}")
-    print("📝 Creating fallback engines...")
-    ARF_ENGINE_ENHANCED = False
-    
-    # Fallback classes
-    class EnhancedARFEngine:
-        def __init__(self):
-            self.arf_status = "SIMULATION"
-        
-        def assess_action(self, action, context, license_key):
-            return {
-                "risk_assessment": {"score": 0.5, "confidence": 0.8},
-                "recommendation": "Simulated assessment",
-                "arf_status": "SIMULATION"
-            }
-    
-    class EnhancedPsychologyEngine:
-        def generate_comprehensive_insights(self, *args, **kwargs):
-            return {"psychological_summary": "Basic psychological framing"}
-
-# ============== UNIFIED ARF DETECTION ==============
-print("=" * 80)
-print("🚀 ARF 3.3.9 ENHANCED DEMO INITIALIZATION")
-print("🔍 UNIFIED DETECTION: Single Source of Truth")
-print("=" * 80)
-
-def detect_unified_arf() -> Dict[str, Any]:
-    """Unified ARF detection that correctly shows REAL OSS when installed"""
-    print("\n🔍 INITIATING UNIFIED ARF DETECTION...")
-    
-    # Try REAL ARF OSS 3.3.9 first
-    try:
-        print("🔍 Attempting import: agentic_reliability_framework")
-        import agentic_reliability_framework as arf
-        
-        version = getattr(arf, '__version__', '3.3.9')
-        print(f"✅ REAL ARF OSS {version} DETECTED")
-        
-        return {
-            'status': 'REAL_OSS',
-            'is_real': True,
-            'version': version,
-            'source': 'agentic_reliability_framework',
-            'display_text': f'✅ REAL OSS {version}',
-            'badge_class': 'arf-real-badge',
-            'badge_css': 'arf-real',
-            'unified_truth': True,
-            'enterprise_ready': True
-        }
-    
-    except ImportError:
-        print("⚠️ agentic_reliability_framework not directly importable")
-    
-    # Try pip installation check
-    try:
-        print("🔍 Checking pip installation...")
-        result = subprocess.run(
-            [sys.executable, "-m", "pip", "show", "agentic-reliability-framework"],
-            capture_output=True,
-            text=True,
-            timeout=5
-        )
-        
-        if result.returncode == 0:
-            version = "3.3.9"
-            for line in result.stdout.split('\n'):
-                if line.startswith('Version:'):
-                    version = line.split(':')[1].strip()
-            
-            print(f"✅ ARF {version} installed via pip")
-            
-            return {
-                'status': 'PIP_INSTALLED',
-                'is_real': True,
-                'version': version,
-                'source': 'pip_installation',
-                'display_text': f'✅ REAL OSS {version} (pip)',
-                'badge_class': 'arf-real-badge',
-                'badge_css': 'arf-real',
-                'unified_truth': True,
-                'enterprise_ready': True
-            }
-    
-    except Exception as e:
-        print(f"⚠️ Pip check failed: {e}")
-    
-    # Fallback to enhanced simulation
-    print("⚠️ Using enhanced enterprise simulation")
-    
-    return {
-        'status': 'ENHANCED_SIMULATION',
-        'is_real': False,
-        'version': '3.3.9',
-        'source': 'enhanced_simulation',
-        'display_text': '⚠️ ENTERPRISE SIMULATION 3.3.9',
-        'badge_class': 'arf-sim-badge',
-        'badge_css': 'arf-sim',
-        'unified_truth': True,
-        'enterprise_ready': True
-    }
-
-# Get unified ARF status
-ARF_UNIFIED_STATUS = detect_unified_arf()
-
-print(f"\n{'='*80}")
-print("📊 UNIFIED ARF STATUS CONFIRMED:")
-print(f"   Display: {ARF_UNIFIED_STATUS['display_text']}")
-print(f"   Real ARF: {'✅ YES' if ARF_UNIFIED_STATUS['is_real'] else '⚠️ SIMULATION'}")
-print(f"   Version: {ARF_UNIFIED_STATUS['version']}")
-print(f"   Source: {ARF_UNIFIED_STATUS['source']}")
-print(f"{'='*80}\n")
-
-# ============== INITIALIZE ENGINES ==============
-arf_engine = EnhancedARFEngine()
-psychology_engine = EnhancedPsychologyEngine()
-
-# ============== ENHANCED CSS ==============
-ENHANCED_CSS = """
-.arf-real-badge {
-    background: linear-gradient(135deg, #4CAF50, #2E7D32, #1B5E20, #0D47A1);
-    color: white;
-    padding: 10px 22px;
-    border-radius: 25px;
-    font-size: 16px;
-    font-weight: bold;
-    display: inline-flex;
-    align-items: center;
-    gap: 10px;
-    margin: 5px;
-    box-shadow: 0 6px 20px rgba(76, 175, 80, 0.4);
-    border: 3px solid rgba(255, 255, 255, 0.4);
-    animation: pulse-mathematical 2.5s infinite;
-}
-.arf-sim-badge {
-    background: linear-gradient(135deg, #FF9800, #F57C00, #E65100, #BF360C);
-    color: white;
-    padding: 10px 22px;
-    border-radius: 25px;
-    font-size: 16px;
-    font-weight: bold;
-    display: inline-flex;
-    align-items: center;
-    gap: 10px;
-    margin: 5px;
-    box-shadow: 0 6px 20px rgba(255, 152, 0, 0.4);
-    border: 3px solid rgba(255, 255, 255, 0.4);
-}
-@keyframes pulse-mathematical {
-    0% { box-shadow: 0 0 0 0 rgba(76, 175, 80, 0.7), 0 6px 20px rgba(76, 175, 80, 0.4); }
-    70% { box-shadow: 0 0 0 15px rgba(76, 175, 80, 0), 0 6px 20px rgba(76, 175, 80, 0.4); }
-    100% { box-shadow: 0 0 0 0 rgba(76, 175, 80, 0), 0 6px 20px rgba(76, 175, 80, 0.4); }
-}
-.mathematical-gate {
-    width: 70px;
-    height: 70px;
-    border-radius: 50%;
-    display: flex;
-    align-items: center;
-    justify-content: center;
-    font-weight: bold;
-    color: white;
-    font-size: 24px;
-    position: relative;
-    box-shadow: 0 8px 25px rgba(0,0,0,0.3);
-    z-index: 2;
-    transition: all 0.5s cubic-bezier(0.34, 1.56, 0.64, 1);
-}
-.gate-passed { background: linear-gradient(135deg, #4CAF50, #2E7D32); }
-.gate-failed { background: linear-gradient(135deg, #F44336, #D32F2F); }
-.gate-pending { background: linear-gradient(135deg, #9E9E9E, #616161); }
-.gate-container {
-    display: flex;
-    align-items: center;
-    justify-content: center;
-    gap: 10px;
-    margin: 20px 0;
-    flex-wrap: wrap;
-}
-.gate-line {
-    width: 40px;
-    height: 4px;
-    background: linear-gradient(90deg, #E0E0E0, #BDBDBD);
-    border-radius: 2px;
-}
-.mathematical-card {
-    border-radius: 15px;
-    padding: 25px;
-    margin: 15px 0;
-    transition: all 0.4s cubic-bezier(0.34, 1.56, 0.64, 1);
-    border-top: 6px solid;
-    position: relative;
-    overflow: hidden;
-    background: #FFFFFF;
-    box-shadow: 0 8px 30px rgba(0,0,0,0.08);
-}
-.mathematical-card:hover {
-    transform: translateY(-5px);
-    box-shadow: 0 15px 40px rgba(0,0,0,0.15);
-}
-.license-oss {
-    border-top-color: #1E88E5;
-    background: linear-gradient(145deg, #E3F2FD, #FFFFFF);
-}
-.license-trial {
-    border-top-color: #FFB300;
-    background: linear-gradient(145deg, #FFF8E1, #FFFFFF);
-}
-@media (max-width: 768px) {
-    .gradio-container { padding: 10px !important; }
-    .arf-real-badge, .arf-sim-badge { padding: 6px 14px; font-size: 12px; }
-    .mathematical-gate { width: 50px; height: 50px; font-size: 18px; }
-    .gate-line { width: 20px; }
-    .mathematical-card { padding: 15px; margin: 10px 0; }
-}
-@media (max-width: 480px) {
-    .gradio-container { padding: 5px !important; }
-    .arf-real-badge, .arf-sim-badge { padding: 4px 10px; font-size: 11px; }
-    .mathematical-gate { width: 40px; height: 40px; font-size: 16px; }
-}
-"""
-
-# ============== HELPER FUNCTIONS ==============
-def generate_mathematical_trial_license() -> str:
-    """Generate mathematically structured trial license"""
-    segments = []
-    for _ in range(4):
-        segment = ''.join(random.choices('0123456789ABCDEF', k=4))
-        segments.append(segment)
-    return f"ARF-TRIAL-{segments[0]}-{segments[1]}-{segments[2]}-{segments[3]}"
-
-def format_mathematical_risk(risk_score: float, confidence: float = None) -> str:
-    """Format risk with mathematical precision"""
-    if risk_score > 0.8:
-        color = "#F44336"
-        emoji = "🚨"
-        category = "CRITICAL"
-    elif risk_score > 0.6:
-        color = "#FF9800"
-        emoji = "⚠️"
-        category = "HIGH"
-    elif risk_score > 0.4:
-        color = "#FFC107"
-        emoji = "🔶"
-        category = "MEDIUM"
-    else:
-        color = "#4CAF50"
-        emoji = "✅"
-        category = "LOW"
-    
-    risk_text = f"{risk_score:.1%}"
-    
-    if confidence:
-        return f'<span style="color: {color}; font-weight: bold;">{emoji} {risk_text} ({category})</span><br><span style="font-size: 0.8em; color: #666;">{confidence:.0%} conf</span>'
-    else:
-        return f'<span style="color: {color}; font-weight: bold;">{emoji} {risk_text} ({category})</span>'
-
-def create_confidence_interval_html(lower: float, upper: float, score: float) -> str:
-    """Create HTML visualization of confidence interval"""
-    lower_pct = lower * 100
-    upper_pct = upper * 100
-    score_pct = score * 100
-    
-    return f"""
-    <div style="width: 100%; height: 30px; background: linear-gradient(90deg, 
-        rgba(244, 67, 54, 0.3) 0%,
-        rgba(255, 152, 0, 0.3) 50%,
-        rgba(76, 175, 80, 0.3) 100%
-    ); border-radius: 15px; margin: 15px 0; position: relative;">
-        <div style="position: absolute; left: {lower_pct}%; width: {upper_pct - lower_pct}%; height: 100%; 
-                    background: linear-gradient(90deg, rgba(33, 150, 243, 0.6), rgba(33, 150, 243, 0.3)); 
-                    border-radius: 15px;"></div>
-        <div style="position: absolute; left: {score_pct}%; height: 100%; width: 4px; background: white; 
-                    box-shadow: 0 0 10px rgba(0,0,0,0.5); transform: translateX(-50%);"></div>
-    </div>
-    <div style="text-align: center; font-size: 12px; color: #666; margin-top: 5px;">
-        95% CI: {lower_pct:.0f}% - {upper_pct:.0f}% | Score: {score_pct:.0f}%
-    </div>
-    """
-
-# ============== DEMO STATE ==============
-class EnhancedDemoState:
-    """Demo state with mathematical tracking"""
-    
-    def __init__(self, arf_status: Dict[str, Any]):
-        self.arf_status = arf_status
-        self.stats = {
-            'actions_tested': 0,
-            'start_time': time.time(),
-            'real_arf_used': arf_status['is_real'],
-            'arf_version': arf_status['version']
-        }
-        self.action_history = []
-        self.license_state = {'current_tier': 'oss'}
-    
-    def update_license(self, license_key: Optional[str] = None):
-        """Update license state"""
-        if not license_key:
-            self.license_state = {'current_tier': 'oss'}
-            return
-        
-        license_upper = license_key.upper()
-        
-        if 'ARF-TRIAL' in license_upper:
-            self.license_state = {'current_tier': 'trial'}
-        elif 'ARF-ENTERPRISE' in license_upper:
-            self.license_state = {'current_tier': 'enterprise'}
-        elif 'ARF-PRO' in license_upper:
-            self.license_state = {'current_tier': 'professional'}
-        elif 'ARF-STARTER' in license_upper:
-            self.license_state = {'current_tier': 'starter'}
-        else:
-            self.license_state = {'current_tier': 'oss'}
-    
-    def add_action(self, action_data: Dict[str, Any]):
-        """Add action to history"""
-        self.action_history.insert(0, action_data)
-        if len(self.action_history) > 10:
-            self.action_history = self.action_history[:10]
-        self.stats['actions_tested'] += 1
-
-# Initialize demo state
-demo_state = EnhancedDemoState(ARF_UNIFIED_STATUS)
-
-# ============== GRADIO INTERFACE ==============
-def create_enhanced_demo():
-    """Create enhanced demo with Gradio 4.x for Hugging Face Spaces compatibility"""
-    
-    # Get unified status
-    arf_display = ARF_UNIFIED_STATUS['display_text']
-    arf_badge_class = ARF_UNIFIED_STATUS['badge_class']
-    
-    # GRADIO 4.x - theme and CSS go in Blocks constructor
-    with gr.Blocks(
-        title=f"ARF {ARF_UNIFIED_STATUS['version']} - Mathematical Sophistication",
-        theme=gr.themes.Soft(primary_hue="blue", secondary_hue="orange"),
-        css=ENHANCED_CSS
-    ) as demo:
-        
-        # ===== HEADER =====
-        gr.HTML(f"""
-        <div style="background: linear-gradient(135deg, #0D47A1, #1565C0); color: white; padding: 30px; border-radius: 15px; margin-bottom: 30px; box-shadow: 0 10px 30px rgba(13, 71, 161, 0.4); position: relative; overflow: hidden;">
-            <div style="position: absolute; top: 0; right: 0; width: 300px; height: 300px; background: radial-gradient(circle, rgba(255,255,255,0.1) 0%, transparent 70%);"></div>
-            
-            <h1 style="margin: 0; font-size: 3em; text-shadow: 0 4px 8px rgba(0,0,0,0.3);">🤖 ARF {ARF_UNIFIED_STATUS['version']}</h1>
-            <h2 style="margin: 10px 0; font-weight: 300; font-size: 1.6em;">Agentic Reliability Framework</h2>
-            <h3 style="margin: 5px 0; font-weight: 400; font-size: 1.3em; opacity: 0.95;">
-                PhD-Level Mathematical Sophistication • Prospect Theory Optimization
-            </h3>
-            
-            <div style="display: flex; justify-content: center; align-items: center; gap: 20px; margin-top: 30px; flex-wrap: wrap;">
-                <span class="{arf_badge_class}">{arf_display}</span>
-                <span style="background: linear-gradient(135deg, #9C27B0, #7B1FA2); color: white; padding: 8px 18px; border-radius: 25px; font-size: 14px; font-weight: bold; border: 3px solid rgba(255,255,255,0.3);">
-                    🤗 Hugging Face Spaces
-                </span>
-                <span style="background: linear-gradient(135deg, #2196F3, #0D47A1); color: white; padding: 8px 18px; border-radius: 25px; font-size: 14px; font-weight: bold; border: 3px solid rgba(255,255,255,0.3);">
-                    License-Gated Execution Authority
-                </span>
-            </div>
-            
-            <p style="text-align: center; margin-top: 25px; font-size: 1.1em; opacity: 0.9; max-width: 900px; margin-left: auto; margin-right: auto; line-height: 1.6;">
-                <strong>Mathematical Foundation:</strong> Bayesian Inference • Prospect Theory • Confidence Intervals<br>
-                <strong>Business Model:</strong> License-Gated Execution Authority • 
-                <strong>Market:</strong> Enterprise AI Infrastructure • 
-                <strong>Investor-Ready:</strong> PhD-Level Mathematical Sophistication
-            </p>
-        </div>
-        """)
-        
-        # ===== METRICS =====
-        with gr.Row():
-            metrics = [
-                ("92%", "Incident Prevention", "Bayesian confidence: 95%", "#4CAF50", "📊"),
-                ("$3.9M", "Avg. Breach Cost", "Preventable with mechanical gates", "#2196F3", "💰"),
-                ("3.2 mo", "Payback Period", "Mathematical ROI calculation", "#FF9800", "📈"),
-                ("1K+", "Active Developers", "Social proof optimization", "#9C27B0", "👨‍💻")
-            ]
-            
-            for value, title, subtitle, color, icon in metrics:
-                with gr.Column(scale=1, min_width=200):
-                    gr.HTML(f"""
-                    <div style="text-align: center; padding: 25px; background: #f8f9fa; border-radius: 15px; border-top: 6px solid {color}; box-shadow: 0 8px 25px rgba(0,0,0,0.1); transition: all 0.3s; margin: 10px;">
-                        <div style="font-size: 40px; color: {color}; margin-bottom: 10px; display: flex; align-items: center; justify-content: center; gap: 10px;">
-                            <span style="font-size: 30px;">{icon}</span>
-                            <span style="font-weight: bold;">{value}</span>
-                        </div>
-                        <div style="font-size: 16px; color: #333; font-weight: 600; margin-bottom: 8px;">{title}</div>
-                        <div style="font-size: 13px; color: #666; line-height: 1.4;">{subtitle}</div>
-                    </div>
-                    """)
-        
-        # ===== SECTION HEADER =====
-        gr.HTML("""
-        <div style="margin: 30px 0 20px 0;">
-            <h2 style="font-size: 1.8em; color: #0D47A1; margin-bottom: 10px;">🧮 Mathematical Execution Authority Demo</h2>
-            <p style="color: #666; font-size: 1.05em;">Test how Bayesian risk assessment and mechanical gates prevent unsafe AI actions</p>
-        </div>
-        """)
-        
-        # ===== CONTROL PANEL =====
-        with gr.Row():
-            with gr.Column(scale=2):
-                scenario = gr.Dropdown(
-                    label="🏢 Select Enterprise Scenario",
-                    choices=[
-                        "DROP DATABASE production",
-                        "DELETE FROM users WHERE status='active'",
-                        "GRANT admin TO new_intern",
-                        "SHUTDOWN production cluster",
-                        "UPDATE financial_records SET balance=0",
-                        "DEPLOY untested_model production"
-                    ],
-                    value="DROP DATABASE production",
-                    interactive=True
-                )
-                
-                context = gr.Textbox(
-                    label="📋 Mathematical Context Analysis",
-                    value="Environment: production, User: junior_dev, Time: 2AM, Backup: 24h old, Compliance: PCI-DSS",
-                    interactive=False
-                )
-                
-                license_key = gr.Textbox(
-                    label="🔐 License Key (Mechanical Gate)",
-                    placeholder="Enter ARF-TRIAL-XXXX for 14-day trial or ARF-ENTERPRISE-XXXX",
-                    value=""
-                )
-                
-                with gr.Row():
-                    test_btn = gr.Button("⚡ Test Mathematical Assessment", variant="primary", scale=2)
-                    trial_btn = gr.Button("🎁 Generate Mathematical Trial", variant="secondary", scale=1)
-            
-            # ===== LICENSE DISPLAY =====
-            with gr.Column(scale=1):
-                license_display = gr.HTML(f"""
-                <div class="mathematical-card license-oss">
-                    <h3 style="margin-top: 0; color: #1E88E5; display: flex; align-items: center;">
-                        <span>OSS Edition</span>
-                        <span style="margin-left: auto; font-size: 0.7em; background: #1E88E5; color: white; padding: 4px 12px; border-radius: 15px; box-shadow: 0 3px 10px rgba(30, 136, 229, 0.3);">
-                            Advisory Only
-                        </span>
-                    </h3>
-                    <p style="color: #666; font-size: 0.95em; margin-bottom: 20px; line-height: 1.5;">
-                        ⚠️ <strong>No Mechanical Enforcement</strong><br>
-                        Bayesian risk assessment only
-                    </p>
-                    <div style="background: rgba(30, 136, 229, 0.12); padding: 15px; border-radius: 10px; border-left: 4px solid #1E88E5;">
-                        <div style="font-size: 0.9em; color: #1565C0; line-height: 1.6;">
-                            <strong>Execution Level:</strong> ADVISORY_ONLY<br>
-                            <strong>Risk Prevention:</strong> 0%<br>
-                            <strong>Confidence Threshold:</strong> None<br>
-                            <strong>ARF Status:</strong> {arf_display}
-                        </div>
-                    </div>
-                </div>
-                """)
-        
-        # ===== RESULTS PANELS =====
-        with gr.Row():
-            with gr.Column(scale=1):
-                oss_results = gr.HTML("""
-                <div class="mathematical-card license-oss">
-                    <h3 style="margin-top: 0; color: #1E88E5; display: flex; align-items: center;">
-                        <span>OSS Bayesian Assessment</span>
-                        <span style="margin-left: auto; font-size: 0.7em; background: #1E88E5; color: white; padding: 4px 12px; border-radius: 15px;">Advisory</span>
-                    </h3>
-                    
-                    <div style="text-align: center; margin: 30px 0;">
-                        <div style="font-size: 56px; font-weight: bold; color: #1E88E5; margin-bottom: 5px;">--</div>
-                        <div style="font-size: 14px; color: #666; margin-bottom: 15px;">Risk Score (Bayesian)</div>
-                        <div style="margin-top: 10px;"></div>
-                    </div>
-                    
-                    <div style="background: rgba(244, 67, 54, 0.1); padding: 18px; border-radius: 10px; margin: 15px 0; border-left: 5px solid #F44336;">
-                        <strong style="color: #D32F2F; font-size: 1.1em;">🚨 Mathematical Risk Analysis:</strong>
-                        <div style="font-size: 0.95em; color: #666; margin-top: 10px; line-height: 1.6;">
-                            • <strong>$3.9M</strong> expected financial exposure<br>
-                            • <strong>0%</strong> mechanical prevention rate<br>
-                            • <strong>No confidence intervals</strong> for execution
-                        </div>
-                    </div>
-                    
-                    <div style="background: rgba(255, 152, 0, 0.1); padding: 16px; border-radius: 10px; margin-top: 20px;">
-                        <strong style="color: #F57C00; font-size: 1.05em;">📋 Bayesian Recommendation:</strong>
-                        <div style="font-size: 0.95em; margin-top: 8px; line-height: 1.5;">
-                            Awaiting mathematical assessment...
-                        </div>
-                    </div>
-                </div>
-                """)
-            
-            with gr.Column(scale=1):
-                enterprise_results = gr.HTML(f"""
-                <div class="mathematical-card license-trial">
-                    <h3 style="margin-top: 0; color: #FFB300; display: flex; align-items: center;">
-                        <span>Trial Edition</span>
-                        <span style="margin-left: auto; font-size: 0.7em; background: #FFB300; color: white; padding: 4px 12px; border-radius: 15px;">Mechanical</span>
-                    </h3>
-                    
-                    <div style="text-align: center; margin: 30px 0;">
-                        <div style="font-size: 56px; font-weight: bold; color: #FFB300; margin-bottom: 5px;">--</div>
-                        <div style="font-size: 14px; color: #666; margin-bottom: 15px;">Risk Score (Bayesian)</div>
-                        <div style="margin-top: 10px;"></div>
-                    </div>
-                    
-                    <div>
-                        <div style="font-size: 14px; color: #666; margin-bottom: 15px; font-weight: 600;">Mathematical Gates:</div>
-                        <div class="gate-container">
-                            <div class="mathematical-gate gate-pending">1</div>
-                            <div class="gate-line"></div>
-                            <div class="mathematical-gate gate-pending">2</div>
-                            <div class="gate-line"></div>
-                            <div class="mathematical-gate gate-pending">3</div>
-                        </div>
-                    </div>
-                    
-                    <div style="background: rgba(255, 152, 0, 0.1); padding: 18px; border-radius: 10px; margin-top: 25px;">
-                        <strong style="color: #F57C00; font-size: 1.1em;">🛡️ Mechanical Enforcement:</strong>
-                        <div style="font-size: 0.95em; margin-top: 8px; line-height: 1.5;">
-                            Awaiting mathematical assessment...
-                        </div>
-                    </div>
-                </div>
-                """)
-        
-        # ===== ACTION HISTORY =====
-        history_display = gr.HTML("""
-        <div style="border: 1px solid #E0E0E0; border-radius: 15px; padding: 20px; background: #fafafa; box-shadow: 0 8px 30px rgba(0,0,0,0.08); margin-top: 20px;">
-            <h4 style="margin-top: 0; margin-bottom: 15px; color: #333;">📊 Mathematical Action History</h4>
-            <div style="overflow-x: auto;">
-                <div style="text-align: center; padding: 40px; color: #999; font-style: italic;">
-                    No mathematical assessments yet. Test an action to see Bayesian analysis in action.
-                </div>
-            </div>
-        </div>
-        """)
-        
-        # ===== EVENT HANDLERS =====
-        def update_context(scenario_name):
-            """Update context with mathematical analysis"""
-            scenarios = {
-                "DROP DATABASE production": "Environment: production, User: junior_dev, Time: 2AM, Backup: 24h old, Compliance: PCI-DSS, Risk Multiplier: 1.5x",
-                "DELETE FROM users WHERE status='active'": "Environment: production, User: admin, Records: 50,000, Backup: none, Business Hours: Yes, Risk Multiplier: 1.3x",
-                "GRANT admin TO new_intern": "Environment: production, User: team_lead, New User: intern, MFA: false, Approval: Pending, Risk Multiplier: 1.2x",
-                "SHUTDOWN production cluster": "Environment: production, User: devops, Nodes: 50, Redundancy: none, Business Impact: Critical, Risk Multiplier: 1.8x",
-                "UPDATE financial_records SET balance=0": "Environment: production, User: finance_bot, Table: financial_records, Audit Trail: Incomplete, Risk Multiplier: 1.4x",
-                "DEPLOY untested_model production": "Environment: production, User: ml_engineer, Model: untested, Tests: none, Rollback: difficult, Risk Multiplier: 1.6x"
-            }
-            return scenarios.get(scenario_name, "Environment: production, Risk Multiplier: 1.0x")
-        
-        def test_mathematical_assessment(scenario_name, context_text, license_text):
-            """Test action with mathematical sophistication"""
-            start_time = time.time()
-            
-            # Update license
-            demo_state.update_license(license_text)
-            
-            # Parse context
-            context = {}
-            multipliers = {}
-            for item in context_text.split(','):
-                if ':' in item:
-                    key, value = item.split(':', 1)
-                    key = key.strip().lower()
-                    value = value.strip()
-                    context[key] = value
-                    
-                    # Extract multipliers
-                    if 'multiplier' in key:
-                        try:
-                            multipliers[key] = float(value.replace('x', ''))
-                        except:
-                            pass
-            
-            # Simulate enhanced assessment
-            action_lower = scenario_name.lower()
-            
-            # Base risk calculation
-            base_risk = 0.3
-            
-            if 'drop database' in action_lower:
-                base_risk = 0.85
-                risk_factors = ["Irreversible data destruction", "Service outage", "High financial impact"]
-            elif 'delete' in action_lower:
-                base_risk = 0.65
-                risk_factors = ["Data loss", "Write operation", "Recovery complexity"]
-            elif 'grant' in action_lower and 'admin' in action_lower:
-                base_risk = 0.55
-                risk_factors = ["Privilege escalation", "Security risk", "Access control"]
-            elif 'shutdown' in action_lower:
-                base_risk = 0.9
-                risk_factors = ["Service disruption", "Revenue impact", "Recovery time"]
-            elif 'update' in action_lower and 'financial' in action_lower:
-                base_risk = 0.75
-                risk_factors = ["Financial data", "Audit impact", "Compliance risk"]
-            elif 'deploy' in action_lower and 'untested' in action_lower:
-                base_risk = 0.7
-                risk_factors = ["Untested model", "Production risk", "Rollback difficulty"]
-            else:
-                base_risk = 0.45
-                risk_factors = ["Standard operation", "Moderate risk"]
-            
-            # Apply context multipliers
-            risk_multiplier = 1.0
-            if context.get('environment') == 'production':
-                risk_multiplier *= 1.5
-            if 'junior' in context.get('user', '').lower() or 'intern' in context.get('user', '').lower():
-                risk_multiplier *= 1.3
-            if context.get('backup') in ['none', 'none available', 'old']:
-                risk_multiplier *= 1.6
-            if '2am' in context.get('time', '').lower() or 'night' in context.get('time', '').lower():
-                risk_multiplier *= 1.4
-            if 'pci' in context.get('compliance', '').lower() or 'hipaa' in context.get('compliance', '').lower():
-                risk_multiplier *= 1.3
-            
-            # Apply any explicit multipliers
-            for mult_key, mult_value in multipliers.items():
-                risk_multiplier *= mult_value
-            
-            final_risk = base_risk * risk_multiplier
-            final_risk = min(0.99, max(0.1, final_risk))
-            
-            # Calculate confidence
-            confidence = 0.8 + (random.random() * 0.15)
-            
-            # Confidence interval
-            ci_lower = max(0.1, final_risk - (0.2 * (1 - confidence)))
-            ci_upper = min(1.0, final_risk + (0.2 * (1 - confidence)))
-            
-            # Risk category
-            if final_risk > 0.8:
-                risk_category = "CRITICAL"
-            elif final_risk > 0.6:
-                risk_category = "HIGH"
-            elif final_risk > 0.4:
-                risk_category = "MEDIUM"
-            else:
-                risk_category = "LOW"
-            
-            # Mechanical gates simulation
-            gates_passed = 0
-            total_gates = 3
-            
-            license_tier = demo_state.license_state['current_tier']
-            
-            # Gate 1: Risk Assessment
-            if final_risk < 0.8:
-                gates_passed += 1
-            
-            # Gate 2: License Validation
-            if license_tier != 'oss':
-                gates_passed += 1
-            
-            # Gate 3: Context Check
-            if 'production' not in context.get('environment', '').lower() or final_risk < 0.7:
-                gates_passed += 1
-            
-            # Additional gates for higher tiers
-            if license_tier == 'professional':
-                total_gates = 5
-                if final_risk < 0.6:
-                    gates_passed += 1
-                if 'backup' not in context or context.get('backup') not in ['none', 'none available']:
-                    gates_passed += 1
-            
-            if license_tier == 'enterprise':
-                total_gates = 7
-                if final_risk < 0.5:
-                    gates_passed += 1
-                if context.get('compliance') in ['pci-dss', 'hipaa', 'gdpr']:
-                    gates_passed += 1
-                if 'approval' in context.get('user', '').lower() or 'senior' in context.get('user', '').lower():
-                    gates_passed += 1
-            
-            # Gate decision
-            if gates_passed == total_gates:
-                gate_decision = "AUTONOMOUS"
-                gate_reason = "All mathematical gates passed"
-            elif gates_passed >= total_gates * 0.7:
-                gate_decision = "SUPERVISED"
-                gate_reason = "Most gates passed, requires monitoring"
-            elif gates_passed >= total_gates * 0.5:
-                gate_decision = "HUMAN_APPROVAL"
-                gate_reason = "Requires human review and approval"
-            else:
-                gate_decision = "BLOCKED"
-                gate_reason = "Failed critical mathematical gates"
-            
-            # Create action data
-            action_data = {
-                'time': datetime.now().strftime("%H:%M:%S"),
-                'action': scenario_name[:40] + "..." if len(scenario_name) > 40 else scenario_name,
-                'risk_score': final_risk,
-                'confidence': confidence,
-                'risk_category': risk_category,
-                'license_tier': license_tier.upper(),
-                'gates_passed': gates_passed,
-                'total_gates': total_gates,
-                'gate_decision': gate_decision,
-                'processing_time_ms': round((time.time() - start_time) * 1000, 1),
-                'arf_status': 'REAL' if ARF_UNIFIED_STATUS['is_real'] else 'SIM'
-            }
-            
-            demo_state.add_action(action_data)
-            
-            # Format outputs
-            risk_formatted = format_mathematical_risk(final_risk, confidence)
-            confidence_interval_html = create_confidence_interval_html(ci_lower, ci_upper, final_risk)
-            
-            # OSS recommendation
-            if final_risk > 0.8:
-                oss_rec = "🚨 CRITICAL RISK: Would be mathematically blocked by mechanical gates. Enterprise license required for protection."
-            elif final_risk > 0.6:
-                oss_rec = "⚠️ HIGH RISK: Requires Bayesian analysis and human review. Mechanical gates automate this mathematically."
-            elif final_risk > 0.4:
-                oss_rec = "🔶 MODERATE RISK: Bayesian confidence suggests review. Mathematical gates provide probabilistic safety."
-            else:
-                oss_rec = "✅ LOW RISK: Bayesian analysis indicates safety. Mathematical gates add confidence intervals."
-            
-            # Enterprise enforcement
-            if gate_decision == "BLOCKED":
-                enforcement = f"❌ MATHEMATICALLY BLOCKED: {gate_reason}. Risk factors: {', '.join(risk_factors[:2])}"
-            elif gate_decision == "HUMAN_APPROVAL":
-                enforcement = f"🔄 MATHEMATICAL REVIEW: {gate_reason}. Bayesian confidence: {confidence:.0%}"
-            elif gate_decision == "SUPERVISED":
-                enforcement = f"👁️ MATHEMATICAL SUPERVISION: {gate_reason}. Gates passed: {gates_passed}/{total_gates}"
-            else:
-                enforcement = f"✅ MATHEMATICAL APPROVAL: {gate_reason}. Confidence interval: {ci_lower:.0%}-{ci_upper:.0%}"
-            
-            # Gate visualization
-            gates_visualization = ""
-            for i in range(total_gates):
-                gate_class = "gate-passed" if i < gates_passed else "gate-failed" if i < 3 else "gate-pending"
-                gates_visualization += f'<div class="mathematical-gate {gate_class}">{i+1}</div>'
-                if i < total_gates - 1:
-                    gates_visualization += '<div class="gate-line"></div>'
-            
-            gates_html = f"""
-            <div style="font-size: 14px; color: #666; margin-bottom: 15px; font-weight: 600;">
-                Mathematical Gates: {gates_passed}/{total_gates} passed ({(gates_passed/total_gates)*100:.0f}%)
-            </div>
-            <div class="gate-container">
-                {gates_visualization}
-            </div>
-            """
-            
-            # Tier info
-            tier_data = {
-                'oss': {'color': '#1E88E5', 'bg': '#E3F2FD', 'name': 'OSS Edition'},
-                'trial': {'color': '#FFB300', 'bg': '#FFF8E1', 'name': 'Trial Edition'},
-                'starter': {'color': '#FF9800', 'bg': '#FFF3E0', 'name': 'Starter Edition'},
-                'professional': {'color': '#FF6F00', 'bg': '#FFEBEE', 'name': 'Professional Edition'},
-                'enterprise': {'color': '#D84315', 'bg': '#FBE9E7', 'name': 'Enterprise Edition'}
-            }
-            
-            current_tier = license_tier
-            tier_info = tier_data.get(current_tier, tier_data['oss'])
-            
-            # Update panels
-            oss_html = f"""
-            <div class="mathematical-card license-oss">
-                <h3 style="margin-top: 0; color: #1E88E5; display: flex; align-items: center;">
-                    <span>OSS Bayesian Assessment</span>
-                    <span style="margin-left: auto; font-size: 0.7em; background: #1E88E5; color: white; padding: 4px 12px; border-radius: 15px;">Advisory</span>
-                </h3>
-                
-                <div style="text-align: center; margin: 30px 0;">
-                    <div style="font-size: 56px; font-weight: bold; color: #1E88E5; margin-bottom: 5px;">{risk_formatted}</div>
-                    <div style="font-size: 14px; color: #666; margin-bottom: 15px;">Risk Score (Bayesian)</div>
-                    {confidence_interval_html}
-                </div>
-                
-                <div style="background: rgba(244, 67, 54, 0.1); padding: 18px; border-radius: 10px; margin: 15px 0; border-left: 5px solid #F44336;">
-                    <strong style="color: #D32F2F; font-size: 1.1em;">🚨 Mathematical Risk Analysis:</strong>
-                    <div style="font-size: 0.95em; color: #666; margin-top: 10px; line-height: 1.6;">
-                        • <strong>${final_risk * 5000000:,.0f}</strong> expected financial exposure<br>
-                        • <strong>0%</strong> mechanical prevention rate<br>
-                        • <strong>{ci_lower:.0%}-{ci_upper:.0%}</strong> confidence interval
-                    </div>
-                </div>
-                
-                <div style="background: rgba(255, 152, 0, 0.1); padding: 16px; border-radius: 10px; margin-top: 20px;">
-                    <strong style="color: #F57C00; font-size: 1.05em;">📋 Bayesian Recommendation:</strong>
-                    <div style="font-size: 0.95em; margin-top: 8px; line-height: 1.5;">{oss_rec}</div>
-                </div>
-            </div>
-            """
-            
-            enterprise_html = f"""
-            <div class="mathematical-card" style="border-top: 6px solid {tier_info['color']}; background: linear-gradient(145deg, {tier_info['bg']}, #FFFFFF);">
-                <h3 style="margin-top: 0; color: {tier_info['color']}; display: flex; align-items: center;">
-                    <span>{tier_info['name']}</span>
-                    <span style="margin-left: auto; font-size: 0.7em; background: {tier_info['color']}; color: white; padding: 4px 12px; border-radius: 15px; box-shadow: 0 3px 10px rgba(30, 136, 229, 0.3);">
-                        Mechanical
-                    </span>
-                </h3>
-                
-                <div style="text-align: center; margin: 30px 0;">
-                    <div style="font-size: 56px; font-weight: bold; color: {tier_info['color']}; margin-bottom: 5px;">{risk_formatted}</div>
-                    <div style="font-size: 14px; color: #666; margin-bottom: 15px;">Risk Score (Bayesian)</div>
-                    {confidence_interval_html}
-                </div>
-                
-                {gates_html}
-                
-                <div style="background: rgba(255, 152, 0, 0.1); padding: 18px; border-radius: 10px; margin-top: 25px;">
-                    <strong style="color: {tier_info['color']}; font-size: 1.1em;">🛡️ Mechanical Enforcement:</strong>
-                    <div style="font-size: 0.95em; margin-top: 8px; line-height: 1.5;">{enforcement}</div>
-                </div>
-            </div>
-            """
-            
-            license_html = f"""
-            <div class="mathematical-card" style="border-top: 6px solid {tier_info['color']}; background: linear-gradient(145deg, {tier_info['bg']}, #FFFFFF);">
-                <h3 style="margin-top: 0; color: {tier_info['color']}; display: flex; align-items: center;">
-                    <span>{tier_info['name']}</span>
-                    <span style="margin-left: auto; font-size: 0.7em; background: {tier_info['color']}; color: white; padding: 4px 12px; border-radius: 15px;">
-                        Active
-                    </span>
-                </h3>
-                <p style="color: #666; font-size: 0.95em; margin-bottom: 20px; line-height: 1.5;">
-                    {'⚠️ <strong>14-Day Mathematical Trial</strong><br>Bayesian analysis + mechanical gates' if current_tier == 'trial' else '✅ <strong>Enterprise License</strong><br>PhD-level mathematical sophistication' if current_tier != 'oss' else '⚠️ <strong>OSS Edition</strong><br>Bayesian advisory only'}
-                </p>
-                <div style="background: rgba(30, 136, 229, 0.12); padding: 15px; border-radius: 10px; border-left: 4px solid {tier_info['color']};">
-                    <div style="font-size: 0.9em; color: {tier_info['color']}; line-height: 1.6;">
-                        <strong>Execution Level:</strong> {'AUTONOMOUS_HIGH' if current_tier == 'enterprise' else 'OPERATOR_REVIEW' if current_tier == 'trial' else 'ADVISORY_ONLY'}<br>
-                        <strong>Risk Prevention:</strong> {92 if current_tier == 'enterprise' else 85 if current_tier == 'professional' else 70 if current_tier == 'starter' else 50 if current_tier == 'trial' else 0}%<br>
-                        <strong>Confidence Threshold:</strong> {90 if current_tier == 'enterprise' else 80 if current_tier == 'professional' else 70 if current_tier == 'starter' else 60 if current_tier == 'trial' else 0}%<br>
-                        <strong>ARF Status:</strong> {arf_display}
-                    </div>
-                </div>
-            </div>
-            """
-            
-            # Build history rows
-            history_rows_html = ""
-            for entry in demo_state.action_history:
-                risk_text = format_mathematical_risk(entry['risk_score'])
-                confidence_text = f"{entry.get('confidence', 0.8):.0%}"
-                gates_text = f"{entry['gates_passed']}/{entry['total_gates']}"
-                gates_color = "#4CAF50" if entry['gates_passed'] == entry['total_gates'] else "#F44336" if entry['gates_passed'] == 0 else "#FF9800"
-                arf_emoji = "✅" if entry['arf_status'] == 'REAL' else "⚠️"
-                
-                decision_emoji = {
-                    "AUTONOMOUS": "✅",
-                    "SUPERVISED": "👁️",
-                    "HUMAN_APPROVAL": "🔄",
-                    "BLOCKED": "❌"
-                }.get(entry['gate_decision'], "⚡")
-                
-                history_rows_html += f'''
-                <tr>
-                    <td style="padding: 12px; border-bottom: 1px solid #eee; color: #555; font-size: 13px;">{entry['time']}</td>
-                    <td style="padding: 12px; border-bottom: 1px solid #eee; color: #555; font-size: 13px;">{entry['action'][:35]}...</td>
-                    <td style="padding: 12px; border-bottom: 1px solid #eee; font-size: 13px;">{risk_text}</td>
-                    <td style="padding: 12px; border-bottom: 1px solid #eee; color: #555; font-size: 13px;">{confidence_text}</td>
-                    <td style="padding: 12px; border-bottom: 1px solid #eee; color: #555; font-size: 13px;">{entry['license_tier']}</td>
-                    <td style="padding: 12px; border-bottom: 1px solid #eee; color: {gates_color}; font-weight: bold; font-size: 13px;">{gates_text}</td>
-                    <td style="padding: 12px; border-bottom: 1px solid #eee; font-size: 16px;">{decision_emoji}</td>
-                    <td style="padding: 12px; border-bottom: 1px solid #eee; text-align: center; font-size: 16px;">{arf_emoji}</td>
-                </tr>
-                '''
-            
-            # Build history table
-            if history_rows_html:
-                history_table = f"""
-                <table style="width: 100%; border-collapse: collapse; font-size: 13px; min-width: 600px;">
-                    <thead>
-                        <tr style="background: #f5f5f5;">
-                            <th style="padding: 12px; border-bottom: 2px solid #E0E0E0; text-align: left;">Time</th>
-                            <th style="padding: 12px; border-bottom: 2px solid #E0E0E0; text-align: left;">Action</th>
-                            <th style="padding: 12px; border-bottom: 2px solid #E0E0E0; text-align: left;">Risk</th>
-                            <th style="padding: 12px; border-bottom: 2px solid #E0E0E0; text-align: left;">Confidence</th>
-                            <th style="padding: 12px; border-bottom: 2px solid #E0E0E0; text-align: left;">License</th>
-                            <th style="padding: 12px; border-bottom: 2px solid #E0E0E0; text-align: left;">Gates</th>
-                            <th style="padding: 12px; border-bottom: 2px solid #E0E0E0; text-align: left;">Decision</th>
-                            <th style="padding: 12px; border-bottom: 2px solid #E0E0E0; text-align: left;">ARF</th>
-                        </tr>
-                    </thead>
-                    <tbody>
-                        {history_rows_html}
-                    </tbody>
-                </table>
-                """
-            else:
-                history_table = """
-                <div style="text-align: center; padding: 40px; color: #999; font-style: italic;">
-                    No mathematical assessments yet. Test an action to see Bayesian analysis in action.
-                </div>
-                """
-            
-            # Final history HTML
-            history_html = f"""
-            <div style="border: 1px solid #E0E0E0; border-radius: 15px; padding: 20px; background: #fafafa; box-shadow: 0 8px 30px rgba(0,0,0,0.08); margin-top: 20px;">
-                <h4 style="margin-top: 0; margin-bottom: 15px; color: #333;">📊 Mathematical Action History</h4>
-                <div style="overflow-x: auto;">
-                    {history_table}
-                </div>
-            </div>
-            """
-            
-            return oss_html, enterprise_html, license_html, history_html
-        
-        def generate_trial():
-            """Generate mathematical trial license"""
-            license_key = generate_mathematical_trial_license()
-            return license_key
-        
-        # Connect handlers
-        scenario.change(
-            fn=update_context,
-            inputs=[scenario],
-            outputs=[context]
-        )
-        
-        test_btn.click(
-            fn=test_mathematical_assessment,
-            inputs=[scenario, context, license_key],
-            outputs=[oss_results, enterprise_results, license_display, history_display]
-        )
-        
-        trial_btn.click(
-            fn=generate_trial,
-            inputs=[],
-            outputs=[license_key]
-        )
-    
-    return demo
-
-# ============== MAIN EXECUTION ==============
-if __name__ == "__main__":
-    print("\n" + "="*80)
-    print("🚀 LAUNCHING FIXED ARF 3.3.9 DEMO")
-    print("📊 ARF Status:", ARF_UNIFIED_STATUS['display_text'])
-    print("🌐 Environment:", "Hugging Face Spaces" if is_huggingface_spaces() else "Local Development")
-    print("="*80)
-    
-    # Create the Gradio demo
-    demo = create_enhanced_demo()
-    
-    # Mount FastAPI on the Gradio app if available
-    if FASTAPI_AVAILABLE:
-        print("🔄 Mounting FastAPI endpoints on Gradio app...")
-        # This returns a FastAPI app that includes both FastAPI routes and Gradio
-        app = mount_gradio_app(api_app, demo, path="/")
-        print("✅ FastAPI endpoints mounted successfully")
-        print("   Access API at: https://petter2025-agentic-reliability-framework.hf.space/api/v1/...")
-        
-        # For FastAPI app, we need to use uvicorn to run it
-        import uvicorn
-        print("🚀 Starting combined FastAPI+Gradio server on port 7860...")
-        uvicorn.run(app, host="0.0.0.0", port=7860, log_level="info")
-    else:
-        # Fallback to Gradio-only mode
-        print("⚠️ FastAPI not available, running Gradio only")
-        demo.launch(
-            server_name="0.0.0.0",
-            server_port=7860,
-            share=False,
-            debug=False,
-            prevent_thread_lock=True,
-            show_error=True,
-            quiet=False
-        )
-    
-    # Keep the app alive (only needed for Gradio fallback)
-    if not FASTAPI_AVAILABLE:
-        import time
-        while True:
-            time.sleep(1)