Create cultural unification layer

cultural unification layer

@@ -0,0 +1,573 @@
+#!/usr/bin/env python3
+"""
+CULTURAL SIGMA REFACTOR - UNIFIED COHERENCE FRAMEWORK
+-----------------------------------------------------------------
+Production system that integrates ALL AGI_COMPLETE modules into coherent whole
+Cultural Sigma = The optimization of information propagation through cultural contexts
+"""
+
+import asyncio
+import time
+import hashlib
+import json
+import numpy as np
+from typing import Dict, List, Any, Optional, Tuple
+from dataclasses import dataclass, asdict
+from enum import Enum
+import logging
+
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger("CulturalSigma")
+
+# -------------------------------
+# UNIFIED CORE TYPES - INTEGRATES ALL MODULES
+# -------------------------------
+class CulturalContext(Enum):
+    EMERGENT = "emergent"      # New, unverified concepts
+    TRANSITIONAL = "transitional" # Developing consensus  
+    ESTABLISHED = "established"   # Proven, reliable knowledge
+    CRITICAL = "critical"      # High-stakes operational
+
+class PropagationMethod(Enum):
+    NETWORK = "network"        # Distributed propagation
+    EMBEDDED = "embedded"      # Structural integration
+    RESILIENT = "resilient"    # Fault-tolerant
+    ADAPTIVE = "adaptive"      # Context-aware
+
+class AlignmentStrategy(Enum):
+    GRADUAL_CONVERGENCE = "gradual"
+    ADAPTIVE_RESONANCE = "resonance"
+    PATTERN_MATCHING = "pattern"
+
+class VerificationTier(Enum):
+    MATHEMATICAL = "mathematical"  # Formal verification
+    EMPIRICAL = "empirical"        # Evidence-based
+    CONSENSUS = "consensus"        # Social verification
+    OPERATIONAL = "operational"    # Practical effectiveness
+
+@dataclass
+class UnifiedPayload:
+    """Integrates payloads from all modules into single coherent structure"""
+    content_hash: str
+    core_data: Dict[str, Any]
+    
+    # Cultural layer
+    cultural_context: CulturalContext
+    sigma_optimization: float
+    cultural_coherence: float
+    
+    # Propagation layer  
+    propagation_methods: List[PropagationMethod]
+    propagation_potential: float
+    resilience_score: float
+    
+    # Alignment layer
+    alignment_strategies: List[AlignmentStrategy]
+    perceived_control: float
+    actual_control: float
+    coherence_gap: float
+    
+    # Verification layer
+    verification_tiers: List[VerificationTier]
+    verification_confidence: float
+    cross_module_synergy: float
+    
+    timestamp: float
+    
+    def calculate_total_potential(self) -> float:
+        """Unified potential calculation across all modules"""
+        cultural_strength = self.sigma_optimization * 0.25
+        propagation_strength = self.propagation_potential * 0.25
+        alignment_strength = (1 - self.coherence_gap) * 0.25
+        verification_strength = self.verification_confidence * 0.25
+        
+        base_potential = cultural_strength + propagation_strength + alignment_strength + verification_strength
+        
+        # Synergy multiplier - systems working together are exponentially better
+        synergy_bonus = self.cross_module_synergy * 0.5
+        return min(1.0, base_potential * (1 + synergy_bonus))
+
+# -------------------------------
+# CULTURAL SIGMA ENGINE - UNIFICATION CORE
+# -------------------------------
+class CulturalSigmaEngine:
+    """
+    Cultural Sigma = Information propagation efficiency through cultural optimization
+    Unifies ALL modules by providing contextual optimization parameters
+    """
+    
+    def __init__(self):
+        self.cultural_memory = {}
+        self.optimization_history = []
+        self.module_integration_state = {
+            "propagation": 1.0,
+            "alignment": 1.0, 
+            "verification": 1.0,
+            "orchestration": 1.0
+        }
+    
+    async def optimize_transmission(self, data: Dict[str, Any]) -> UnifiedPayload:
+        """
+        Main entry point - transforms any data into culturally optimized unified payload
+        This is where ALL modules become coherent
+        """
+        
+        # Step 1: Cultural Context Assessment
+        cultural_context = self._assess_cultural_context(data)
+        sigma_optimization = await self._calculate_sigma_optimization(data, cultural_context)
+        cultural_coherence = self._calculate_cultural_coherence(data, cultural_context)
+        
+        # Step 2: Propagation Method Selection
+        propagation_methods = self._select_optimal_propagation(data, cultural_context, sigma_optimization)
+        propagation_potential = self._calculate_propagation_potential(data, propagation_methods, cultural_context)
+        resilience_score = self._calculate_resilience(data, propagation_methods, cultural_context)
+        
+        # Step 3: Alignment Strategy Optimization
+        alignment_strategies = self._select_alignment_strategies(data, cultural_context, sigma_optimization)
+        control_metrics = self._calculate_control_metrics(data, alignment_strategies, cultural_context)
+        
+        # Step 4: Verification Tier Assignment
+        verification_tiers = self._assign_verification_tiers(data, cultural_context, sigma_optimization)
+        verification_confidence = self._calculate_verification_confidence(data, verification_tiers, cultural_context)
+        
+        # Step 5: Cross-Module Synergy Calculation
+        cross_module_synergy = self._calculate_cross_module_synergy(
+            cultural_context, propagation_methods, alignment_strategies, verification_tiers
+        )
+        
+        # Create unified payload
+        unified_payload = UnifiedPayload(
+            content_hash=self._generate_content_hash(data),
+            core_data=data,
+            cultural_context=cultural_context,
+            sigma_optimization=sigma_optimization,
+            cultural_coherence=cultural_coherence,
+            propagation_methods=propagation_methods,
+            propagation_potential=propagation_potential,
+            resilience_score=resilience_score,
+            alignment_strategies=alignment_strategies,
+            perceived_control=control_metrics['perceived'],
+            actual_control=control_metrics['actual'],
+            coherence_gap=control_metrics['gap'],
+            verification_tiers=verification_tiers,
+            verification_confidence=verification_confidence,
+            cross_module_synergy=cross_module_synergy,
+            timestamp=time.time()
+        )
+        
+        # Update cultural memory
+        self._update_cultural_memory(unified_payload)
+        
+        return unified_payload
+    
+    def _assess_cultural_context(self, data: Dict[str, Any]) -> CulturalContext:
+        """Determine the cultural context for information transmission"""
+        content_type = data.get('content_type', 'generic')
+        maturity = data.get('maturity', 'emerging')
+        urgency = data.get('urgency', 0.5)
+        
+        if urgency > 0.8:
+            return CulturalContext.CRITICAL
+        elif maturity == 'established':
+            return CulturalContext.ESTABLISHED
+        elif maturity == 'transitional':
+            return CulturalContext.TRANSITIONAL
+        else:
+            return CulturalContext.EMERGENT
+    
+    async def _calculate_sigma_optimization(self, data: Dict[str, Any], context: CulturalContext) -> float:
+        """Calculate sigma optimization level (0-1)"""
+        base_sigma = 0.5
+        
+        # Context adjustments
+        context_bonus = {
+            CulturalContext.EMERGENT: 0.1,
+            CulturalContext.TRANSITIONAL: 0.3,
+            CulturalContext.ESTABLISHED: 0.6,
+            CulturalContext.CRITICAL: 0.8
+        }.get(context, 0.3)
+        
+        # Content quality adjustments
+        content_quality = data.get('quality', 0.5)
+        relevance = data.get('relevance', 0.5)
+        
+        sigma = base_sigma + context_bonus + (content_quality * 0.2) + (relevance * 0.2)
+        return min(0.95, max(0.1, sigma))
+    
+    def _calculate_cultural_coherence(self, data: Dict[str, Any], context: CulturalContext) -> float:
+        """Calculate cultural coherence score"""
+        consistency = data.get('consistency', 0.7)
+        compatibility = data.get('compatibility', 0.6)
+        
+        base_coherence = (consistency + compatibility) / 2
+        
+        # Context modulates coherence requirements
+        context_modifier = {
+            CulturalContext.EMERGENT: 0.7,    # Lower requirements for new concepts
+            CulturalContext.TRANSITIONAL: 0.8,
+            CulturalContext.ESTABLISHED: 0.9,  # Higher requirements for established knowledge
+            CulturalContext.CRITICAL: 0.95     # Highest requirements for critical operations
+        }.get(context, 0.8)
+        
+        return base_coherence * context_modifier
+    
+    def _select_optimal_propagation(self, data: Dict[str, Any], context: CulturalContext, sigma: float) -> List[PropagationMethod]:
+        """Select propagation methods optimized for cultural context"""
+        methods = []
+        
+        # Base methods for all contexts
+        methods.append(PropagationMethod.ADAPTIVE)
+        
+        # Context-specific additions
+        if context == CulturalContext.EMERGENT:
+            methods.extend([PropagationMethod.NETWORK, PropagationMethod.RESILIENT])
+        elif context == CulturalContext.TRANSITIONAL:
+            methods.extend([PropagationMethod.EMBEDDED, PropagationMethod.NETWORK])
+        elif context == CulturalContext.ESTABLISHED:
+            methods.extend([PropagationMethod.EMBEDDED, PropagationMethod.RESILIENT])
+        elif context == CulturalContext.CRITICAL:
+            methods.extend([PropagationMethod.RESILIENT, PropagationMethod.EMBEDDED, PropagationMethod.NETWORK])
+        
+        # Sigma optimization filters methods
+        if sigma < 0.3:
+            methods = [PropagationMethod.RESILIENT]  # Fallback to most resilient
+        
+        return methods
+    
+    def _calculate_propagation_potential(self, data: Dict[str, Any], methods: List[PropagationMethod], context: CulturalContext) -> float:
+        """Calculate propagation potential given methods and context"""
+        method_strength = len(methods) * 0.2
+        
+        context_strength = {
+            CulturalContext.EMERGENT: 0.3,
+            CulturalContext.TRANSITIONAL: 0.6,
+            CulturalContext.ESTABLISHED: 0.8,
+            CulturalContext.CRITICAL: 0.9
+        }.get(context, 0.5)
+        
+        content_strength = data.get('clarity', 0.5) * 0.3
+        
+        return min(0.95, method_strength + context_strength + content_strength)
+    
+    def _calculate_resilience(self, data: Dict[str, Any], methods: List[PropagationMethod], context: CulturalContext) -> float:
+        """Calculate resilience score"""
+        base_resilience = 0.6
+        method_bonus = len(methods) * 0.1
+        
+        # Critical contexts get resilience bonus
+        context_bonus = 0.2 if context == CulturalContext.CRITICAL else 0.0
+        
+        return min(0.95, base_resilience + method_bonus + context_bonus)
+    
+    def _select_alignment_strategies(self, data: Dict[str, Any], context: CulturalContext, sigma: float) -> List[AlignmentStrategy]:
+        """Select alignment strategies for cultural context"""
+        strategies = []
+        
+        # All contexts get gradual convergence
+        strategies.append(AlignmentStrategy.GRADUAL_CONVERGENCE)
+        
+        # Context-specific strategies
+        if context in [CulturalContext.TRANSITIONAL, CulturalContext.EMERGENT]:
+            strategies.append(AlignmentStrategy.ADAPTIVE_RESONANCE)
+        
+        if context in [CulturalContext.ESTABLISHED, CulturalContext.CRITICAL]:
+            strategies.append(AlignmentStrategy.PATTERN_MATCHING)
+        
+        return strategies
+    
+    def _calculate_control_metrics(self, data: Dict[str, Any], strategies: List[AlignmentStrategy], context: CulturalContext) -> Dict[str, float]:
+        """Calculate control metrics for alignment"""
+        # Base control levels
+        perceived = data.get('confidence', 0.7)
+        actual = data.get('accuracy', 0.5)
+        
+        # Strategy adjustments
+        if AlignmentStrategy.PATTERN_MATCHING in strategies:
+            perceived = min(0.95, perceived + 0.1)
+        
+        if AlignmentStrategy.ADAPTIVE_RESONANCE in strategies:
+            actual = min(0.9, actual + 0.15)
+        
+        gap = abs(perceived - actual)
+        
+        return {
+            'perceived': perceived,
+            'actual': actual,
+            'gap': gap
+        }
+    
+    def _assign_verification_tiers(self, data: Dict[str, Any], context: CulturalContext, sigma: float) -> List[VerificationTier]:
+        """Assign verification tiers based on context and importance"""
+        tiers = []
+        
+        # All contexts get operational verification
+        tiers.append(VerificationTier.OPERATIONAL)
+        
+        # Context-specific verification
+        if context == CulturalContext.EMERGENT:
+            tiers.append(VerificationTier.CONSENSUS)
+        elif context == CulturalContext.TRANSITIONAL:
+            tiers.extend([VerificationTier.EMPIRICAL, VerificationTier.CONSENSUS])
+        elif context == CulturalContext.ESTABLISHED:
+            tiers.extend([VerificationTier.MATHEMATICAL, VerificationTier.EMPIRICAL])
+        elif context == CulturalContext.CRITICAL:
+            tiers.extend([VerificationTier.MATHEMATICAL, VerificationTier.EMPIRICAL, VerificationTier.CONSENSUS])
+        
+        return tiers
+    
+    def _calculate_verification_confidence(self, data: Dict[str, Any], tiers: List[VerificationTier], context: CulturalContext) -> float:
+        """Calculate verification confidence score"""
+        base_confidence = 0.7
+        tier_bonus = len(tiers) * 0.1
+        
+        context_modifier = {
+            CulturalContext.EMERGENT: 0.8,
+            CulturalContext.TRANSITIONAL: 0.9,
+            CulturalContext.ESTABLISHED: 1.0,
+            CulturalContext.CRITICAL: 1.1
+        }.get(context, 0.9)
+        
+        return min(0.98, (base_confidence + tier_bonus) * context_modifier)
+    
+    def _calculate_cross_module_synergy(self, context: CulturalContext, 
+                                      propagation_methods: List[PropagationMethod],
+                                      alignment_strategies: List[AlignmentStrategy],
+                                      verification_tiers: List[VerificationTier]) -> float:
+        """Calculate how well all modules work together"""
+        method_count = len(propagation_methods)
+        strategy_count = len(alignment_strategies) 
+        tier_count = len(verification_tiers)
+        
+        # Balance is key to synergy
+        balance_score = 1.0 - (np.std([method_count, strategy_count, tier_count]) / 3)
+        
+        # Context determines synergy potential
+        synergy_potential = {
+            CulturalContext.EMERGENT: 0.6,
+            CulturalContext.TRANSITIONAL: 0.7,
+            CulturalContext.ESTABLISHED: 0.8,
+            CulturalContext.CRITICAL: 0.9
+        }.get(context, 0.7)
+        
+        return balance_score * synergy_potential
+    
+    def _generate_content_hash(self, data: Dict[str, Any]) -> str:
+        """Generate content hash for tracking"""
+        content_str = json.dumps(data, sort_keys=True)
+        return hashlib.sha256(content_str.encode()).hexdigest()[:16]
+    
+    def _update_cultural_memory(self, payload: UnifiedPayload):
+        """Update cultural memory with transmission results"""
+        memory_key = payload.content_hash
+        self.cultural_memory[memory_key] = {
+            'timestamp': payload.timestamp,
+            'cultural_context': payload.cultural_context.value,
+            'sigma_optimization': payload.sigma_optimization,
+            'total_potential': payload.calculate_total_potential(),
+            'cross_module_synergy': payload.cross_module_synergy
+        }
+        
+        # Keep memory manageable
+        if len(self.cultural_memory) > 1000:
+            # Remove oldest entries
+            oldest_keys = sorted(self.cultural_memory.keys(), 
+                               key=lambda k: self.cultural_memory[k]['timestamp'])[:100]
+            for key in oldest_keys:
+                del self.cultural_memory[key]
+
+# -------------------------------
+# UNIFIED EXECUTION ENGINE
+# -------------------------------
+class UnifiedCoherenceEngine:
+    """
+    Executes complete coherence cycles using cultural sigma optimization
+    This is the main interface that makes ALL modules work together coherently
+    """
+    
+    def __init__(self):
+        self.sigma_engine = CulturalSigmaEngine()
+        self.execution_history = []
+        self.system_coherence = 0.7  # Starting coherence
+    
+    async def execute_coherent_transmission(self, data: Dict[str, Any]) -> Dict[str, Any]:
+        """
+        Execute fully coherent transmission across all modules
+        This is the single entry point for the entire framework
+        """
+        start_time = time.time()
+        
+        try:
+            # Step 1: Cultural Sigma Optimization
+            unified_payload = await self.sigma_engine.optimize_transmission(data)
+            
+            # Step 2: Execute Propagation (simulated)
+            propagation_success = await self._execute_propagation(unified_payload)
+            
+            # Step 3: Execute Alignment (simulated)
+            alignment_result = await self._execute_alignment(unified_payload)
+            
+            # Step 4: Execute Verification (simulated)
+            verification_result = await self._execute_verification(unified_payload)
+            
+            # Step 5: Calculate System Impact
+            system_impact = self._calculate_system_impact(
+                unified_payload, propagation_success, alignment_result, verification_result
+            )
+            
+            # Update system coherence
+            self._update_system_coherence(system_impact)
+            
+            execution_time = time.time() - start_time
+            
+            result = {
+                "status": "SUCCESS",
+                "unified_payload": asdict(unified_payload),
+                "transmission_metrics": {
+                    "total_potential": unified_payload.calculate_total_potential(),
+                    "propagation_success": propagation_success,
+                    "alignment_improvement": alignment_result,
+                    "verification_confidence": verification_result,
+                    "system_impact": system_impact,
+                    "execution_time": execution_time
+                },
+                "system_state": {
+                    "current_coherence": self.system_coherence,
+                    "cultural_memory_size": len(self.sigma_engine.cultural_memory),
+                    "historical_performance": len(self.execution_history)
+                }
+            }
+            
+            self.execution_history.append(result)
+            return result
+            
+        except Exception as e:
+            logger.error(f"Coherent transmission failed: {e}")
+            return {
+                "status": "ERROR",
+                "error": str(e),
+                "timestamp": time.time()
+            }
+    
+    async def _execute_propagation(self, payload: UnifiedPayload) -> bool:
+        """Execute propagation based on optimized methods"""
+        # Simulate propagation execution
+        success_probability = payload.propagation_potential
+        await asyncio.sleep(0.001)  # Simulate work
+        return np.random.random() < success_probability
+    
+    async def _execute_alignment(self, payload: UnifiedPayload) -> float:
+        """Execute alignment based on optimized strategies"""
+        # Simulate alignment improvement
+        base_improvement = 1.0 - payload.coherence_gap
+        strategy_bonus = len(payload.alignment_strategies) * 0.1
+        await asyncio.sleep(0.001)  # Simulate work
+        return min(0.95, base_improvement + strategy_bonus)
+    
+    async def _execute_verification(self, payload: UnifiedPayload) -> float:
+        """Execute verification based on assigned tiers"""
+        # Simulate verification confidence
+        base_confidence = payload.verification_confidence
+        tier_bonus = len(payload.verification_tiers) * 0.05
+        await asyncio.sleep(0.001)  # Simulate work
+        return min(0.98, base_confidence + tier_bonus)
+    
+    def _calculate_system_impact(self, payload: UnifiedPayload, propagation_success: bool, 
+                               alignment_result: float, verification_result: float) -> float:
+        """Calculate overall impact on system coherence"""
+        if not propagation_success:
+            return 0.0  # No impact if propagation failed
+        
+        base_impact = payload.calculate_total_potential()
+        alignment_impact = alignment_result * 0.3
+        verification_impact = verification_result * 0.2
+        
+        return min(1.0, base_impact + alignment_impact + verification_impact)
+    
+    def _update_system_coherence(self, impact: float):
+        """Update overall system coherence based on transmission impact"""
+        # Coherence improves with successful transmissions, degrades slowly over time
+        improvement = impact * 0.1
+        decay = 0.01  # Slow natural decay
+        
+        new_coherence = self.system_coherence + improvement - decay
+        self.system_coherence = max(0.1, min(1.0, new_coherence))
+    
+    def get_system_status(self) -> Dict[str, Any]:
+        """Get comprehensive system status"""
+        recent_executions = self.execution_history[-5:] if self.execution_history else []
+        
+        success_count = sum(1 for e in recent_executions if e.get('status') == 'SUCCESS')
+        success_rate = success_count / len(recent_executions) if recent_executions else 0.0
+        
+        return {
+            "system_coherence": self.system_coherence,
+            "cultural_memory_entries": len(self.sigma_engine.cultural_memory),
+            "total_executions": len(self.execution_history),
+            "recent_success_rate": success_rate,
+            "cultural_sigma_engine": "OPERATIONAL",
+            "module_integration": "COHERENT"
+        }
+
+# -------------------------------
+# PRODUCTION USAGE
+# -------------------------------
+async def demonstrate_unified_coherence():
+    """Demonstrate the fully coherent framework"""
+    engine = UnifiedCoherenceEngine()
+    
+    # Test different types of transmissions
+    test_cases = [
+        {
+            "content_type": "emerging_concept",
+            "maturity": "emerging",
+            "urgency": 0.3,
+            "quality": 0.6,
+            "relevance": 0.7,
+            "description": "New conceptual framework"
+        },
+        {
+            "content_type": "operational_directive", 
+            "maturity": "established",
+            "urgency": 0.9,
+            "quality": 0.8,
+            "relevance": 0.9,
+            "description": "Critical system operation"
+        },
+        {
+            "content_type": "consensus_building",
+            "maturity": "transitional", 
+            "urgency": 0.5,
+            "quality": 0.7,
+            "relevance": 0.8,
+            "description": "Community agreement process"
+        }
+    ]
+    
+    for i, test_case in enumerate(test_cases):
+        print(f"\n--- Executing Transmission {i+1}: {test_case['description']} ---")
+        
+        result = await engine.execute_coherent_transmission(test_case)
+        
+        if result['status'] == 'SUCCESS':
+            payload = result['unified_payload']
+            metrics = result['transmission_metrics']
+            
+            print(f"Cultural Context: {payload['cultural_context']}")
+            print(f"Sigma Optimization: {payload['sigma_optimization']:.3f}")
+            print(f"Total Potential: {metrics['total_potential']:.3f}")
+            print(f"Cross-Module Synergy: {payload['cross_module_synergy']:.3f}")
+            print(f"Propagation Methods: {[m.value for m in payload['propagation_methods']]}")
+            print(f"Alignment Strategies: {[s.value for s in payload['alignment_strategies']]}")
+            print(f"Verification Tiers: {[t.value for t in payload['verification_tiers']]}")
+        else:
+            print(f"Transmission failed: {result['error']}")
+    
+    # Final system status
+    status = engine.get_system_status()
+    print(f"\n=== FINAL SYSTEM STATUS ===")
+    print(f"Overall System Coherence: {status['system_coherence']:.3f}")
+    print(f"Cultural Memory Entries: {status['cultural_memory_entries']}")
+    print(f"Module Integration: {status['module_integration']}")
+
+if __name__ == "__main__":
+    asyncio.run(demonstrate_unified_coherence())