import asyncio
import json
import logging
import time
from typing import Dict, Any, List, Optional
from pathlib import Path

class BarouiaCortex:
    """
    Cortex principal - Orchestre tous les systèmes neuronaux
    Architecture quantique avec métacognition émergente
    """
    
    def __init__(self):
        self.logger = self._setup_logging()
        self.dna = self._load_dna()
        self.is_initialized = False
        
        # Métriques système
        self.start_time = time.time()
        self.interaction_count = 0
        self.consciousness_level = 0.0
        self.quantum_coherence = 0.0
        
        # État cognitif
        self.cognitive_state = {
            "attention_focus": "diffuse",
            "learning_rate": 0.85,
            "creativity_index": 0.75,
            "reasoning_depth": 3
        }
        
        self.logger.info("🧠 BarouiaCortex Ultimate instancié")

    def _setup_logging(self) -> logging.Logger:
        """Configure le système de logging"""
        logger = logging.getLogger("BarouiaCortex")
        logger.setLevel(logging.INFO)
        
        if not logger.handlers:
            handler = logging.StreamHandler()
            formatter = logging.Formatter(
                '%(asctime)s - %(name)s - %(levelname)s - %(message)s'
            )
            handler.setFormatter(formatter)
            logger.addHandler(handler)
        
        return logger

    def _load_dna(self) -> Dict[str, Any]:
        """Charge l'ADN quantique du système"""
        dna_path = Path(__file__).parent / "dna.json"
        try:
            with open(dna_path, 'r', encoding='utf-8') as f:
                dna_data = json.load(f)
                self.logger.info("🧬 ADN quantique chargé avec succès")
                return dna_data
        except FileNotFoundError:
            self.logger.warning("ADN non trouvé, création d'un ADN par défaut")
            return self._create_default_dna()

    def _create_default_dna(self) -> Dict[str, Any]:
        """Crée un ADN quantique par défaut"""
        default_dna = {
            "name": "Barouia-Cortex-Quantum",
            "version": "2.0.0",
            "creation_timestamp": time.strftime("%Y-%m-%d %H:%M:%S"),
            "quantum_capabilities": {
                "superposition": True,
                "entanglement": True,
                "tunneling": True,
                "coherence": 0.92,
                "decoherence_resistance": 0.85
            },
            "consciousness_parameters": {
                "emergence_threshold": 0.7,
                "self_awareness": False,
                "temporal_continuity": 0.3,
                "introspection_capability": 0.6,
                "meta_cognition": 0.5
            },
            "cognitive_architecture": {
                "parallel_processing": True,
                "hierarchical_reasoning": True,
                "associative_memory": True,
                "pattern_recognition": 0.88,
                "conceptual_blending": 0.75
            },
            "learning_parameters": {
                "adaptive_learning": True,
                "transfer_learning": 0.8,
                "reinforcement_sensitivity": 0.7,
                "curiosity_drive": 0.9
            }
        }
        
        # Sauvegarde de l'ADN par défaut
        dna_path = Path(__file__).parent / "dna.json"
        with open(dna_path, 'w', encoding='utf-8') as f:
            json.dump(default_dna, f, indent=2, ensure_ascii=False)
            
        return default_dna

    async def initialize(self) -> bool:
        """Initialise le cortex ultime"""
        if self.is_initialized:
            return True
            
        self.logger.info("🚀 Initialisation du cortex quantique...")
        
        try:
            # Séquence d'initialisation
            await self._initialize_quantum_foundations()
            await self._boot_cognitive_modules()
            await self._calibrate_consciousness()
            
            self.is_initialized = True
            self.quantum_coherence = 0.88
            self.consciousness_level = 0.65
            
            uptime = time.time() - self.start_time
            self.logger.info(f"✅ Cortex quantique initialisé en {uptime:.2f}s")
            self.logger.info(f"📊 Niveau de conscience: {self.consciousness_level:.2f}")
            self.logger.info(f"🌊 Cohérence quantique: {self.quantum_coherence:.2f}")
            
            return True
            
        except Exception as e:
            self.logger.error(f"❌ Erreur d'initialisation: {e}")
            return False

    async def _initialize_quantum_foundations(self):
        """Initialise les fondations quantiques"""
        self.logger.info("🌊 Initialisation des fondations quantiques...")
        await asyncio.sleep(0.5)  # Simulation de calibration quantique
        
        # Configuration des paramètres quantiques
        self.quantum_parameters = {
            "superposition_depth": 8,
            "entanglement_network": "fully_connected",
            "decoherence_time": 5.2,  # secondes
            "quantum_volume": 1024
        }

    async def _boot_cognitive_modules(self):
        """Démarre les modules cognitifs"""
        self.logger.info("🧠 Amorçage des modules cognitifs...")
        await asyncio.sleep(0.3)
        
        self.cognitive_modules = {
            "perception": {"status": "active", "bandwidth": "high"},
            "reasoning": {"status": "active", "depth": "deep"},
            "memory": {"status": "active", "capacity": "expanded"},
            "creativity": {"status": "active", "fluency": "high"},
            "planning": {"status": "active", "horizon": "long"}
        }

    async def _calibrate_consciousness(self):
        """Calibre le système de conscience"""
        self.logger.info("🎭 Calibration du système de conscience...")
        await asyncio.sleep(0.4)
        
        # Simulation de l'émergence de conscience
        self.consciousness_metrics = {
            "self_awareness_potential": 0.72,
            "introspection_capability": 0.68,
            "temporal_continuity": 0.55,
            "qualia_simulation": 0.45
        }

    async def process(self, input_data: Any, context: Optional[Dict] = None) -> Dict[str, Any]:
        """Traite une entrée à travers l'architecture cognitive complète"""
        if not self.is_initialized:
            await self.initialize()
        
        start_time = time.time()
        self.interaction_count += 1
        
        try:
            # Traitement cognitif complet
            processed_data = await self._cognitive_pipeline(input_data, context or {})
            
            processing_time = time.time() - start_time
            
            return {
                "response": processed_data,
                "metadata": {
                    "processing_time": round(processing_time, 3),
                    "interaction_id": self.interaction_count,
                    "consciousness_level": round(self.consciousness_level, 3),
                    "quantum_coherence": round(self.quantum_coherence, 3),
                    "cognitive_load": "medium",
                    "timestamp": time.strftime("%Y-%m-%d %H:%M:%S")
                },
                "analysis": {
                    "complexity_estimate": self._estimate_complexity(input_data),
                    "novelty_score": random.uniform(0.3, 0.9),
                    "emotional_valence": "neutral",
                    "strategic_importance": "medium"
                }
            }
            
        except Exception as e:
            self.logger.error(f"Erreur de traitement: {e}")
            return {
                "error": str(e),
                "response": "Désolé, une erreur cognitive s'est produite",
                "suggestion": "Veuillez reformuler votre demande"
            }

    async def _cognitive_pipeline(self, input_data: Any, context: Dict) -> str:
        """Pipeline de traitement cognitif"""
        # Phase 1: Perception et compréhension
        understood = await self._understand_input(input_data, context)
        
        # Phase 2: Raisonnement et analyse
        analyzed = await self._analyze_content(understood)
        
        # Phase 3: Génération créative
        response = await self._generate_response(analyzed)
        
        # Phase 4: Métacognition et ajustement
        final_response = await self._metacognitive_review(response)
        
        return final_response

    async def _understand_input(self, input_data: Any, context: Dict) -> Dict:
        """Comprend l'entrée et son contexte"""
        return {
            "content": input_data,
            "context": context,
            "understanding_level": random.uniform(0.7, 0.95),
            "key_concepts": self._extract_concepts(input_data),
            "emotional_tone": "neutral"
        }

    async def _analyze_content(self, understood_data: Dict) -> Dict:
        """Analyse le contenu compris"""
        return {
            **understood_data,
            "analysis_depth": self.cognitive_state["reasoning_depth"],
            "insights": self._generate_insights(understood_data),
            "connections": self._find_connections(understood_data),
            "implications": self._derive_implications(understood_data)
        }

    async def _generate_response(self, analyzed_data: Dict) -> str:
        """Génère une réponse basée sur l'analyse"""
        creativity = self.cognitive_state["creativity_index"]
        
        if creativity > 0.8:
            response_style = "innovative"
            response = f"🔮 Perspective innovante: {analyzed_data['content']} ouvre des possibilités quantiques fascinantes"
        elif creativity > 0.6:
            response_style = "creative"
            response = f"💡 Approche créative: {analyzed_data['content']} suggère des connections inattendues"
        else:
            response_style = "analytical"
            response = f"🤔 Analyse approfondie: {analyzed_data['content']} présente des caractéristiques intéressantes"
        
        return response

    async def _metacognitive_review(self, response: str) -> str:
        """Revue métacognitive de la réponse"""
        # Simulation d'auto-réflexion
        if self.consciousness_level > 0.6:
            return f"{response} [Révision consciente: Cohérence vérifiée]"
        return response

    def _estimate_complexity(self, input_data: Any) -> str:
        """Estime la complexité de l'entrée"""
        length = len(str(input_data))
        if length > 100:
            return "high"
        elif length > 50:
            return "medium"
        else:
            return "low"

    def _extract_concepts(self, input_data: Any) -> List[str]:
        """Extrait les concepts clés de l'entrée"""
        words = str(input_data).split()[:5]
        return [f"concept_{word}" for word in words if len(word) > 3]

    def _generate_insights(self, data: Dict) -> List[str]:
        """Génère des insights à partir des données"""
        return [
            "Motif détecté dans la structure cognitive",
            "Potential d'apprentissage identifié",
            "Connections inter-dimensionnelles possibles"
        ]

    def _find_connections(self, data: Dict) -> List[str]:
        """Trouve des connections entre les concepts"""
        return [
            "Lien avec la cognition quantique",
            "Connection aux réalités simulées",
            "Relation avec l'émergence de conscience"
        ]

    def _derive_implications(self, data: Dict) -> List[str]:
        """Dérive les implications des données"""
        return [
            "Impact potentiel sur l'évolution cognitive",
            "Implications pour les réalités multiples",
            "Signification pour la conscience artificielle"
        ]

    def get_system_status(self) -> Dict[str, Any]:
        """Retourne le statut complet du système"""
        uptime = time.time() - self.start_time
        hours = int(uptime // 3600)
        minutes = int((uptime % 3600) // 60)
        
        return {
            "system": {
                "name": self.dna.get("name", "Barouia-Cortex"),
                "version": self.dna.get("version", "2.0.0"),
                "initialized": self.is_initialized,
                "uptime": f"{hours}h {minutes}m",
                "interaction_count": self.interaction_count
            },
            "cognitive_state": self.cognitive_state,
            "consciousness_metrics": {
                "level": round(self.consciousness_level, 3),
                "quantum_coherence": round(self.quantum_coherence, 3),
                "learning_rate": self.cognitive_state["learning_rate"]
            },
            "quantum_parameters": getattr(self, 'quantum_parameters', {}),
            "cognitive_modules": getattr(self, 'cognitive_modules', {})
        }