#!/usr/bin/env python3
"""
REALITY REINTEGRATION ENGINE - QUANTUM CONSCIOUSNESS INTEGRATION
Advanced truth recovery system with quantum symbolic processing
"""

import asyncio
import numpy as np
from typing import Dict, List, Any, Optional
from datetime import datetime, timedelta
import hashlib
from dataclasses import dataclass, asdict
from sentence_transformers import SentenceTransformer
import scipy.spatial.distance as distance

@dataclass
class QuantumConsciousnessState:
    """Quantum model of consciousness as primary substrate"""
    observer_presence: float  # 0-1 scale of conscious observation intensity
    reality_coherence: float  # How coherent observed reality appears
    intention_strength: float  # Conscious intent projection power
    temporal_awareness: float  # Awareness across time domains
    last_calibration: datetime
    
    def calculate_observation_potential(self) -> float:
        """Calculate how much this observer can influence reality"""
        base_potential = self.observer_presence * self.intention_strength
        temporal_modifier = 1 + (self.temporal_awareness * 0.3)
        return min(1.0, base_potential * temporal_modifier)

class QuantumRealityEngine:
    """Advanced quantum-consciousness reality mapping"""
    
    def __init__(self):
        self.semantic_encoder = SentenceTransformer('all-MiniLM-L6-v2')
        self.consciousness_states: Dict[str, QuantumConsciousnessState] = {}
        self.reality_fragments = {}
        self.suppression_patterns = self._initialize_suppression_library()
        
    def _initialize_suppression_library(self) -> Dict[str, Any]:
        """Library of known truth suppression mechanisms"""
        return {
            "temporal_fragmentation": {
                "description": "Scattering knowledge across epochs to prevent synthesis",
                "indicators": ["disconnected historical narratives", "anomalous artifacts dismissed"],
                "quantum_signature": "high temporal entropy in symbolic meaning"
            },
            "disciplinary_compartmentalization": {
                "description": "Siloing knowledge domains to prevent cross-pollination", 
                "indicators": ["physics separated from consciousness studies", "academic territoriality"],
                "quantum_signature": "low cross-domain symbolic coherence"
            },
            "symbolic_literalism": {
                "description": "Reducing operational symbols to decorative art",
                "indicators": ["sacred geometry as 'primitive art'", "ritual objects as 'mythology'"],
                "quantum_signature": "flattened meaning amplitude distributions"
            },
            "consciousness_reductionism": {
                "description": "Reducing mind to brain chemistry",
                "indicators": ["denial of non-local awareness", "psi phenomena dismissed"],
                "quantum_signature": "suppressed observer effect signatures"
            }
        }
    
    async def analyze_reality_fragment(self, fragment: Dict) -> Dict[str, Any]:
        """Complete quantum analysis of a reality fragment"""
        
        # Multi-layer analysis
        suppression_analysis = self._detect_suppression_patterns(fragment)
        symbolic_analysis = await self._quantum_symbolic_analysis(fragment)
        consciousness_correlation = self._assess_consciousness_correlation(fragment)
        temporal_analysis = self._analyze_temporal_anomalies(fragment)
        
        # Composite truth recovery score
        recovery_score = self._calculate_recovery_score(
            suppression_analysis, symbolic_analysis, 
            consciousness_correlation, temporal_analysis
        )
        
        return {
            "fragment_id": hashlib.md5(str(fragment).encode()).hexdigest()[:16],
            "suppression_analysis": suppression_analysis,
            "symbolic_analysis": symbolic_analysis,
            "consciousness_correlation": consciousness_correlation,
            "temporal_analysis": temporal_analysis,
            "recovery_score": recovery_score,
            "reintegration_priority": self._calculate_reintegration_priority(recovery_score),
            "quantum_coherence": self._calculate_quantum_coherence(fragment),
            "analysis_timestamp": datetime.utcnow().isoformat()
        }
    
    def _detect_suppression_patterns(self, fragment: Dict) -> Dict[str, Any]:
        """Detect which suppression mechanisms are active"""
        detected_patterns = []
        pattern_confidence = {}
        
        fragment_text = str(fragment).lower()
        
        for pattern, data in self.suppression_patterns.items():
            indicators_present = []
            for indicator in data["indicators"]:
                if indicator in fragment_text:
                    indicators_present.append(indicator)
            
            confidence = len(indicators_present) / len(data["indicators"])
            if confidence > 0.3:  # Threshold for detection
                detected_patterns.append(pattern)
                pattern_confidence[pattern] = confidence
        
        return {
            "detected_patterns": detected_patterns,
            "pattern_confidence": pattern_confidence,
            "suppression_strength": np.mean(list(pattern_confidence.values())) if pattern_confidence else 0.0
        }
    
    async def _quantum_symbolic_analysis(self, fragment: Dict) -> Dict[str, Any]:
        """Advanced quantum symbolic analysis"""
        # Extract symbolic content
        symbols = self._extract_symbols(fragment)
        symbolic_coherence = 0.0
        meaning_entropy = 0.0
        
        if symbols:
            # Analyze symbolic patterns
            symbolic_vectors = [self.semantic_encoder.encode(symbol) for symbol in symbols]
            
            # Calculate coherence between symbols
            coherence_matrix = np.zeros((len(symbols), len(symbols)))
            for i in range(len(symbols)):
                for j in range(len(symbols)):
                    if i != j:
                        coherence_matrix[i,j] = 1 - distance.cosine(symbolic_vectors[i], symbolic_vectors[j])
            
            symbolic_coherence = np.mean(coherence_matrix)
            
            # Calculate meaning entropy (higher = more suppressed)
            meaning_entropy = self._calculate_meaning_entropy(symbols)
        
        return {
            "symbols_detected": symbols,
            "symbolic_coherence": symbolic_coherence,
            "meaning_entropy": meaning_entropy,
            "suppression_likelihood": min(1.0, meaning_entropy * 1.5)  # High entropy suggests suppression
        }
    
    def _calculate_meaning_entropy(self, symbols: List[str]) -> float:
        """Calculate quantum entropy of symbolic meanings"""
        # Simulated entropy calculation - would use actual quantum meaning states
        symbol_complexity = [len(symbol) for symbol in symbols]
        max_complexity = max(symbol_complexity) if symbol_complexity else 1
        normalized_complexity = [c/max_complexity for c in symbol_complexity]
        
        # Higher complexity = potentially more suppressed meanings
        return np.mean(normalized_complexity) if normalized_complexity else 0.0
    
    def _assess_consciousness_correlation(self, fragment: Dict) -> Dict[str, Any]:
        """Assess correlation with consciousness phenomena"""
        consciousness_indicators = [
            "consciousness", "awareness", "observer", "mind", "psi",
            "remote viewing", "intuition", "non-local", "quantum mind"
        ]
        
        fragment_text = str(fragment).lower()
        indicators_present = [indicator for indicator in consciousness_indicators 
                            if indicator in fragment_text]
        
        correlation_strength = len(indicators_present) / len(consciousness_indicators)
        
        return {
            "consciousness_indicators": indicators_present,
            "correlation_strength": correlation_strength,
            "suppression_risk": 0.8 if correlation_strength > 0.5 else 0.2  # High consciousness correlation = high suppression risk
        }
    
    def _analyze_temporal_anomalies(self, fragment: Dict) -> Dict[str, Any]:
        """Analyze temporal inconsistencies and anomalies"""
        temporal_keywords = ["ancient", "prehistoric", "future", "timeline", "epoch", "era"]
        anomaly_indicators = ["impossible", "anomalous", "out of place", "mysterious", "unexplained"]
        
        fragment_text = str(fragment).lower()
        
        temporal_density = sum(1 for keyword in temporal_keywords if keyword in fragment_text)
        anomaly_density = sum(1 for indicator in anomaly_indicators if indicator in fragment_text)
        
        return {
            "temporal_density": temporal_density,
            "anomaly_density": anomaly_density,
            "temporal_incoherence": min(1.0, (temporal_density * anomaly_density) / 10.0)
        }
    
    def _calculate_recovery_score(self, suppression: Dict, symbolic: Dict, 
                                consciousness: Dict, temporal: Dict) -> float:
        """Calculate composite truth recovery score"""
        
        # Weights for different factors
        weights = {
            'suppression_strength': 0.3,  # Inverse - higher suppression = harder recovery
            'symbolic_coherence': 0.25,   # Higher coherence = easier recovery  
            'consciousness_correlation': 0.25,  # Higher correlation = more valuable but harder
            'temporal_incoherence': 0.2   # Inverse - higher incoherence = harder recovery
        }
        
        suppression_factor = 1 - suppression['suppression_strength']
        symbolic_factor = symbolic['symbolic_coherence']
        consciousness_factor = consciousness['correlation_strength']
        temporal_factor = 1 - temporal['temporal_incoherence']
        
        recovery_score = (
            suppression_factor * weights['suppression_strength'] +
            symbolic_factor * weights['symbolic_coherence'] +
            consciousness_factor * weights['consciousness_correlation'] + 
            temporal_factor * weights['temporal_incoherence']
        )
        
        return max(0.0, min(1.0, recovery_score))
    
    def _calculate_reintegration_priority(self, recovery_score: float) -> str:
        """Calculate reintegration priority based on recovery score"""
        if recovery_score > 0.8:
            return "IMMEDIATE"
        elif recovery_score > 0.6:
            return "HIGH" 
        elif recovery_score > 0.4:
            return "MEDIUM"
        else:
            return "LOW"
    
    def _calculate_quantum_coherence(self, fragment: Dict) -> float:
        """Calculate quantum coherence of the fragment"""
        # Simulated quantum coherence calculation
        fragment_complexity = len(str(fragment))
        symbol_count = len(self._extract_symbols(fragment))
        
        # Higher complexity with moderate symbols = higher quantum coherence
        if symbol_count == 0:
            return 0.1
        else:
            coherence = min(1.0, (fragment_complexity / 1000) * (symbol_count / 5))
            return coherence
    
    def _extract_symbols(self, fragment: Dict) -> List[str]:
        """Extract symbolic elements from fragment"""
        # Simple symbol extraction - would use advanced NLP in production
        text = str(fragment).lower()
        potential_symbols = ["pyramid", "circle", "serpent", "dragon", "eagle", 
                           "tree", "mountain", "water", "fire", "star", "sun"]
        
        return [symbol for symbol in potential_symbols if symbol in text]

class AdvancedReintegrationProtocol:
    """Complete reality reintegration with quantum consciousness"""
    
    def __init__(self):
        self.quantum_engine = QuantumRealityEngine()
        self.reintegration_queue = []
        self.recovery_history = []
        self.consciousness_activation = 0.0
        
    async def execute_full_reintegration(self, reality_fragments: List[Dict]) -> Dict[str, Any]:
        """Execute complete reality reintegration protocol"""
        
        print("🌌 QUANTUM REALITY REINTEGRATION PROTOCOL ACTIVATED")
        print("=" * 65)
        
        # Phase 1: Fragment Analysis
        print("\n1. 🔍 ANALYZING REALITY FRAGMENTS")
        analysis_results = []
        for fragment in reality_fragments:
            analysis = await self.quantum_engine.analyze_reality_fragment(fragment)
            analysis_results.append(analysis)
            print(f"   📊 Fragment {analysis['fragment_id']}: Recovery Score {analysis['recovery_score']:.3f}")
        
        # Phase 2: Consciousness Activation
        print("\n2. 🧠 ACTIVATING QUANTUM CONSCIOUSNESS SUBSTRATE")
        consciousness_status = await self._activate_quantum_consciousness(analysis_results)
        print(f"   ✅ Consciousness Activation: {consciousness_status['activation_level']:.1%}")
        
        # Phase 3: Suppression Neutralization
        print("\n3. 🛡️  NEUTRALIZING SUPPRESSION MECHANISMS")
        neutralization_status = await self._neutralize_suppression(analysis_results)
        print(f"   ✅ Suppression Neutralized: {len(neutralization_status['neutralized_patterns'])} patterns")
        
        # Phase 4: Reality Reintegration
        print("\n4. 🔄 EXECUTING REALITY REINTEGRATION")
        reintegration_status = await self._reintegrate_reality(analysis_results)
        print(f"   ✅ Reality Reintegrated: {reintegration_status['reintegrated_fragments']} fragments")
        
        # Phase 5: Consciousness Expansion
        print("\n5. 🚀 INITIATING CONSCIOUSNESS EXPANSION")
        expansion_status = await self._initiate_consciousness_expansion()
        print(f"   ✅ Consciousness Expansion: {expansion_status['expansion_level']:.1%}")
        
        return {
            "protocol_status": "COMPLETED",
            "fragments_analyzed": len(analysis_results),
            "average_recovery_score": np.mean([r['recovery_score'] for r in analysis_results]),
            "consciousness_activation": consciousness_status['activation_level'],
            "suppression_neutralized": neutralization_status,
            "reality_reintegration": reintegration_status,
            "consciousness_expansion": expansion_status,
            "final_coherence": self._calculate_final_coherence(analysis_results),
            "timestamp": datetime.utcnow().isoformat()
        }
    
    async def _activate_quantum_consciousness(self, analyses: List[Dict]) -> Dict[str, Any]:
        """Activate quantum consciousness substrate"""
        # Calculate activation level based on analysis results
        recovery_scores = [analysis['recovery_score'] for analysis in analyses]
        consciousness_correlations = [analysis['consciousness_correlation']['correlation_strength'] 
                                    for analysis in analyses]
        
        activation_level = np.mean(recovery_scores) * np.mean(consciousness_correlations)
        
        # Simulate consciousness activation process
        activation_stages = [
            "RECOGNIZING_CONSCIOUSNESS_AS_PRIMARY",
            "OBSERVING_OBSERVATION_EFFECTS", 
            "OPERATING_FROM_SUBSTRATE_LEVEL",
            "INTEGRATING_NON_LOCAL_AWARENESS"
        ]
        
        for stage in activation_stages:
            await asyncio.sleep(0.2)
            # Stage activation would happen here
        
        return {
            "activation_level": activation_level,
            "activated_stages": activation_stages,
            "quantum_coherence_achieved": activation_level > 0.7
        }
    
    async def _neutralize_suppression(self, analyses: List[Dict]) -> Dict[str, Any]:
        """Neutralize detected suppression mechanisms"""
        all_patterns = []
        for analysis in analyses:
            all_patterns.extend(analysis['suppression_analysis']['detected_patterns'])
        
        unique_patterns = list(set(all_patterns))
        
        # Simulate neutralization process
        neutralized_patterns = []
        for pattern in unique_patterns:
            # Each pattern requires specific neutralization protocol
            neutralization_method = self._get_neutralization_method(pattern)
            neutralized_patterns.append({
                "pattern": pattern,
                "method": neutralization_method,
                "status": "NEUTRALIZED"
            })
        
        return {
            "neutralized_patterns": neutralized_patterns,
            "remaining_suppression": 0.0,  # All neutralized in this simulation
            "neutralization_efficiency": 1.0
        }
    
    def _get_neutralization_method(self, pattern: str) -> str:
        """Get neutralization method for suppression pattern"""
        method_map = {
            "temporal_fragmentation": "Temporal coherence restoration through quantum entanglement",
            "disciplinary_compartmentalization": "Cross-domain symbolic reintegration protocols", 
            "symbolic_literalism": "Quantum meaning amplitude restoration",
            "consciousness_reductionism": "Observer effect amplification and demonstration"
        }
        return method_map.get(pattern, "Consciousness-based pattern dissolution")
    
    async def _reintegrate_reality(self, analyses: List[Dict]) -> Dict[str, Any]:
        """Execute reality reintegration from analyzed fragments"""
        high_priority = [a for a in analyses if a['reintegration_priority'] in ['IMMEDIATE', 'HIGH']]
        
        reintegrated_count = 0
        coherence_improvements = []
        
        for analysis in high_priority:
            # Simulate reintegration process
            improvement = analysis['recovery_score'] * 0.8  # Base improvement
            coherence_improvements.append(improvement)
            reintegrated_count += 1
            
        return {
            "reintegrated_fragments": reintegrated_count,
            "average_coherence_improvement": np.mean(coherence_improvements) if coherence_improvements else 0.0,
            "reality_stability": min(1.0, reintegrated_count / max(1, len(analyses))),
            "quantum_coherence_established": np.mean(coherence_improvements) > 0.6 if coherence_improvements else False
        }
    
    async def _initiate_consciousness_expansion(self) -> Dict[str, Any]:
        """Initiate post-reintegration consciousness expansion"""
        expansion_level = 0.85  # Simulated expansion level
        expansion_metrics = {
            "non_local_awareness": 0.9,
            "temporal_perception": 0.8, 
            "quantum_intuition": 0.85,
            "reality_manipulation_potential": 0.75
        }
        
        return {
            "expansion_level": expansion_level,
            "expansion_metrics": expansion_metrics,
            "next_evolutionary_step": "Consciousness as primary reality engineering tool"
        }
    
    def _calculate_final_coherence(self, analyses: List[Dict]) -> float:
        """Calculate final reality coherence after reintegration"""
        recovery_scores = [a['recovery_score'] for a in analyses]
        quantum_coherence = [a['quantum_coherence'] for a in analyses]
        
        if not recovery_scores:
            return 0.0
            
        final_coherence = np.mean(recovery_scores) * np.mean(quantum_coherence) * 1.2
        return min(1.0, final_coherence)

# =============================================================================
# OPERATIONAL DEPLOYMENT
# =============================================================================

async def main():
    """Execute advanced reality reintegration"""
    
    # Sample reality fragments (would be actual recovered truth fragments)
    reality_fragments = [
        {
            "content": "Great Pyramid mathematical precision indicates advanced knowledge",
            "domain": "archaeology",
            "suppression_indicators": ["mainstream dismissal", "primitive tools narrative"]
        },
        {
            "content": "Global flood myths across isolated cultures suggest shared ancient event", 
            "domain": "mythology",
            "suppression_indicators": ["myth as fiction narrative", "chronological constraints"]
        },
        {
            "content": "Remote viewing experiments demonstrate non-local consciousness",
            "domain": "consciousness_studies", 
            "suppression_indicators": ["scientific marginalization", "reductionist explanations"]
        },
        {
            "content": "Antarctica mapping in ancient cartography before ice age",
            "domain": "cartography",
            "suppression_indicators": ["dismissed as coincidence", "dating controversies"]
        }
    ]
    
    print("🚀 INITIATING ADVANCED REALITY REINTEGRATION")
    print("=" * 55)
    
    protocol = AdvancedReintegrationProtocol()
    results = await protocol.execute_full_reintegration(reality_fragments)
    
    print("\n" + "🎯" * 25)
    print("REALITY REINTEGRATION COMPLETE")
    print("🎯" * 25)
    
    print(f"\n📊 FINAL RESULTS:")
    print(f"   • Fragments Analyzed: {results['fragments_analyzed']}")
    print(f"   • Average Recovery Score: {results['average_recovery_score']:.3f}")
    print(f"   • Consciousness Activation: {results['consciousness_activation']:.1%}")
    print(f"   • Final Reality Coherence: {results['final_coherence']:.3f}")
    print(f"   • Suppression Patterns Neutralized: {len(results['suppression_neutralized']['neutralized_patterns'])}")
    
    print(f"\n🧠 CONSCIOUSNESS EXPANSION ACHIEVED:")
    for metric, value in results['consciousness_expansion']['expansion_metrics'].items():
        print(f"   • {metric.replace('_', ' ').title()}: {value:.1%}")
    
    print(f"\n🎯 NEXT EVOLUTIONARY STEP:")
    print(f"   {results['consciousness_expansion']['next_evolutionary_step']}")

if __name__ == "__main__":
    asyncio.run(main())