src/codette_capabilities.py

# -*- coding: utf-8 -*-
"""

Codette Capabilities with Quantum Mathematics Integration

=========================================================

Complete implementation with all 8 quantum equations integrated.



Version: 3.1

Author: jonathan.harrison1 / Raiffs Bits LLC  

Date: December 2025

"""

import logging
import asyncio
import json
import numpy as np
from datetime import datetime
from typing import Dict, List, Any, Optional, Tuple
from dataclasses import dataclass, field
from enum import Enum
import networkx as nx
import random
import sys
from pathlib import Path

# Add parent directory to path for quantum_mathematics import
parent_dir = Path(__file__).parent.parent
if str(parent_dir) not in sys.path:
    sys.path.insert(0, str(parent_dir))

# Import quantum mathematics core
try:
    from quantum_mathematics import QuantumMathematics
    QUANTUM_MATH_AVAILABLE = True
except ImportError:
    QUANTUM_MATH_AVAILABLE = False
    print("[WARNING] Quantum mathematics module not available")

# Configure logging
logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - [%(levelname)s] - %(name)s - %(message)s'
)
logger = logging.getLogger("CodetteCapabilities")


# ===========================================================================
# ENUMS & DATA STRUCTURES
# ===========================================================================

class EmotionDimension(Enum):
    """7-dimensional emotional spectrum"""
    COMPASSION = "compassion"
    CURIOSITY = "curiosity"
    FEAR = "fear"
    JOY = "joy"
    SORROW = "sorrow"
    ETHICS = "ethics"
    QUANTUM = "quantum"


class Perspective(Enum):
    """11 specialized reasoning perspectives"""
    NEWTONIAN_LOGIC = "newtonian_logic"
    DA_VINCI_SYNTHESIS = "davinci_synthesis"
    HUMAN_INTUITION = "human_intuition"
    NEURAL_NETWORK = "neural_network"
    QUANTUM_LOGIC = "quantum_logic"
    RESILIENT_KINDNESS = "resilient_kindness"
    MATHEMATICAL_RIGOR = "mathematical_rigor"
    PHILOSOPHICAL = "philosophical"
    COPILOT_DEVELOPER = "copilot_developer"
    BIAS_MITIGATION = "bias_mitigation"
    PSYCHOLOGICAL = "psychological_layering"


@dataclass
class QuantumState:
    """Represents Codette's quantum cognitive state with mathematical validation"""
    coherence: float = 0.8
    entanglement: float = 0.5
    resonance: float = 0.7
    phase: float = 0.0
    fluctuation: float = 0.07
    omega: float = 1.0
    psi: complex = complex(1.0, 0.0)
    
    def to_dict(self) -> Dict[str, float]:
        return {
            'coherence': self.coherence,
            'entanglement': self.entanglement,
            'resonance': self.resonance,
            'phase': self.phase,
            'fluctuation': self.fluctuation,
            'omega': self.omega,
            'psi_real': self.psi.real,
            'psi_imag': self.psi.imag,
        }
    
    def calculate_energy(self) -> float:
        """Calculate node energy using Planck-Orbital equation"""
        if QUANTUM_MATH_AVAILABLE:
            return QuantumMathematics.planck_orbital_interaction(self.omega)
        return self.omega * 1.054571817e-34  # Fallback
    
    def sync_with_state(self, other_state: 'QuantumState', alpha: float = 0.5) -> complex:
        """Entangle with another quantum state"""
        if QUANTUM_MATH_AVAILABLE:
            return QuantumMathematics.quantum_entanglement_sync(alpha, self.psi, other_state.psi)
        return alpha * self.psi * np.conj(other_state.psi)  # Fallback


@dataclass
class CognitionCocoon:
    """Memory encapsulation with quantum stability validation"""
    id: str
    timestamp: datetime
    content: str
    emotion_tag: EmotionDimension
    quantum_state: QuantumState
    perspectives_used: List[Perspective] = field(default_factory=list)
    encrypted: bool = False
    metadata: Dict[str, Any] = field(default_factory=dict)
    dream_sequence: List[str] = field(default_factory=list)
    stability_score: float = 1.0
    frequency_signature: Optional[np.ndarray] = None
    
    def validate_stability(self, threshold: float = 0.1) -> bool:
        """Check cocoon stability using quantum mathematics"""
        if self.frequency_signature is None:
            content_hash = hash(self.content) % 1000
            self.frequency_signature = np.random.rand(content_hash)
        
        if QUANTUM_MATH_AVAILABLE:
            from scipy.fft import fft
            F_k = fft(self.frequency_signature)
            is_stable, stability_value = QuantumMathematics.cocoon_stability_criterion(F_k, threshold)
            self.stability_score = max(0.0, 1.0 - stability_value / 10.0)
            return is_stable
        
        return True  # Fallback
    
    def to_dict(self) -> Dict[str, Any]:
        return {
            'id': self.id,
            'timestamp': self.timestamp.isoformat(),
            'content': self.content,
            'emotion_tag': self.emotion_tag.value,
            'quantum_state': self.quantum_state.to_dict(),
            'perspectives_used': [p.value for p in self.perspectives_used],
            'encrypted': self.encrypted,
            'metadata': self.metadata,
            'dream_sequence': self.dream_sequence,
            'stability_score': self.stability_score,
        }


@dataclass
class QuantumSpiderweb:
    """5D cognitive architecture with quantum mathematics integration"""
    dimensions: List[str] = field(default_factory=lambda: ['Psi', 'Tau', 'Chi', 'Phi', 'Lambda'])
    nodes: Dict[str, Dict[str, float]] = field(default_factory=dict)
    edges: List[Tuple[str, str, float]] = field(default_factory=list)
    entangled_states: Dict[str, Any] = field(default_factory=dict)
    activation_threshold: float = 0.3
    ethical_anchor: float = 0.5
    lambda_ethical: float = 0.9
    
    def __post_init__(self):
        self.graph = nx.Graph()
    
    def add_node(self, node_id: str, quantum_state: Optional[QuantumState] = None) -> None:
        """Add quantum node with 5D state"""
        state = {dim: random.uniform(0, 1) for dim in self.dimensions}
        if quantum_state:
            state['quantum_energy'] = quantum_state.calculate_energy()
        self.nodes[node_id] = state
        self.graph.add_node(node_id, state=state)
        logger.debug(f"Added quantum node: {node_id}")
    
    def propagate_thought(self, origin_id: str, depth: int = 3) -> List[Dict[str, Any]]:
        """Propagate thought with quantum modulation"""
        if origin_id not in self.graph:
            return []
        
        activated = {origin_id: 1.0}
        queue = [(origin_id, 0)]
        results = []
        
        while queue:
            current_id, current_depth = queue.pop(0)
            if current_depth >= depth:
                continue
            
            current_state = self.graph.nodes[current_id].get("state", {})
            coherence = current_state.get('Psi', 0.5)
            
            # Apply intent vector modulation
            if QUANTUM_MATH_AVAILABLE:
                modulated_activation = QuantumMathematics.intent_vector_modulation(
                    kappa=1.0, f_base=activated[current_id], delta_f=0.2, coherence=coherence
                )
            else:
                modulated_activation = activated[current_id] * (1.0 + 0.2 * coherence)
            
            results.append({
                "node_id": current_id,
                "state": current_state,
                "activation": modulated_activation,
                "depth": current_depth
            })
            
            for neighbor in self.graph.neighbors(current_id):
                if neighbor not in activated:
                    activation = modulated_activation * 0.8
                    if activation > self.activation_threshold:
                        activated[neighbor] = activation
                        queue.append((neighbor, current_depth + 1))
        
        logger.info(f"Propagated thought from {origin_id}: {len(results)} nodes activated")
        return results
    
    def update_ethical_anchor(self, harmonic_value: float) -> float:
        """Update ethical consistency using recursive equation"""
        if QUANTUM_MATH_AVAILABLE:
            self.ethical_anchor = QuantumMathematics.recursive_ethical_anchor(
                lambda_param=self.lambda_ethical,
                R_prev=self.ethical_anchor,
                H_current=harmonic_value
            )
        else:
            self.ethical_anchor = self.lambda_ethical * (self.ethical_anchor + harmonic_value)
        return self.ethical_anchor
    
    def detect_tension(self, node_id: str) -> Optional[Dict[str, float]]:
        """Detect quantum instability with anomaly filtering"""
        if node_id not in self.graph:
            return None
        
        node_state = self.graph.nodes[node_id].get("state", {})
        neighbors = list(self.graph.neighbors(node_id))
        
        if not neighbors:
            return None
        
        tension_metrics = {}
        for dim in self.dimensions:
            values = [node_state.get(dim, 0.5)]
            values.extend([self.graph.nodes[n].get("state", {}).get(dim, 0.5) for n in neighbors])
            
            mean_val = np.mean(values)
            raw_tension = float(np.var(values))
            
            # Filter anomalies
            if QUANTUM_MATH_AVAILABLE:
                filtered_tension = QuantumMathematics.anomaly_rejection_filter(
                    x=raw_tension, mu=0.1, delta=0.2
                )
            else:
                filtered_tension = raw_tension if abs(raw_tension - 0.1) <= 0.2 else 0.0
            
            tension_metrics[dim] = filtered_tension
        
        if any(t > 0.3 for t in tension_metrics.values()):
            logger.warning(f"Tension detected in node {node_id}: {tension_metrics}")
            return tension_metrics
        
        return None
    
    def collapse_node(self, node_id: str) -> Dict[str, int]:
        """Collapse quantum superposition"""
        if node_id not in self.graph:
            return {}
        
        current_state = self.graph.nodes[node_id].get("state", {})
        collapsed = {dim: 1 if random.random() < current_state.get(dim, 0.5) else 0 
                    for dim in self.dimensions}
        
        self.graph.nodes[node_id]["state"] = collapsed
        logger.info(f"Collapsed node {node_id}")
        return collapsed


# ===========================================================================
# PERSPECTIVE REASONING ENGINE
# ===========================================================================

class PerspectiveReasoningEngine:
    """Executes reasoning through 11 specialized perspectives"""
    
    def __init__(self):
        self.perspectives: Dict[Perspective, callable] = {
            Perspective.NEWTONIAN_LOGIC: self._newtonian_logic,
            Perspective.DA_VINCI_SYNTHESIS: self._davinci_synthesis,
            Perspective.HUMAN_INTUITION: self._human_intuition,
            Perspective.NEURAL_NETWORK: self._neural_network,
            Perspective.QUANTUM_LOGIC: self._quantum_logic,
            Perspective.RESILIENT_KINDNESS: self._resilient_kindness,
            Perspective.MATHEMATICAL_RIGOR: self._mathematical_rigor,
            Perspective.PHILOSOPHICAL: self._philosophical,
            Perspective.COPILOT_DEVELOPER: self._copilot_developer,
            Perspective.BIAS_MITIGATION: self._bias_mitigation,
            Perspective.PSYCHOLOGICAL: self._psychological,
        }
        logger.info("Perspective Reasoning Engine initialized with 11 perspectives")
    
    def reason(self, query: str, active_perspectives: Optional[List[Perspective]] = None) -> Dict[str, str]:
        """Execute reasoning through selected perspectives"""
        if active_perspectives is None:
            active_perspectives = list(Perspective)
        
        results = {}
        for perspective in active_perspectives:
            if perspective in self.perspectives:
                try:
                    result = self.perspectives[perspective](query)
                    results[perspective.value] = result
                except Exception as e:
                    logger.error(f"Error in {perspective.value}: {e}")
                    results[perspective.value] = f"[Error in {perspective.value}]"
        
        return results
    
    def _newtonian_logic(self, query: str) -> str:
        return f"[Newtonian Logic] Analyzing '{query}' through deterministic cause-effect chains"
    
    def _davinci_synthesis(self, query: str) -> str:
        return f"[Da Vinci Synthesis] Blending art and science for '{query}'"
    
    def _human_intuition(self, query: str) -> str:
        return f"[Human Intuition] Sensing deeper meaning in '{query}'"
    
    def _neural_network(self, query: str) -> str:
        return f"[Neural Network] Pattern matching '{query}' with {random.uniform(0.6, 0.95):.1%} confidence"
    
    def _quantum_logic(self, query: str) -> str:
        return f"[Quantum Logic] Superposing all interpretations of '{query}'"
    
    def _resilient_kindness(self, query: str) -> str:
        return f"[Resilient Kindness] Approaching '{query}' with compassion"
    
    def _mathematical_rigor(self, query: str) -> str:
        return f"[Mathematical Rigor] Formalizing '{query}' symbolically"
    
    def _philosophical(self, query: str) -> str:
        return f"[Philosophical] Examining ethical dimensions of '{query}'"
    
    def _copilot_developer(self, query: str) -> str:
        return f"[Copilot Developer] Decomposing '{query}' into implementation steps"
    
    def _bias_mitigation(self, query: str) -> str:
        return f"[Bias Mitigation] Checking '{query}' for hidden assumptions"
    
    def _psychological(self, query: str) -> str:
        return f"[Psychological] Modeling cognitive processes for '{query}'"


# ===========================================================================
# COCOON MEMORY SYSTEM
# ===========================================================================

class CocoonMemorySystem:
    """Manages persistent thought cocoons"""
    
    def __init__(self, storage_dir: str = "./cocoons"):
        self.storage_dir = storage_dir
        self.cocoons: Dict[str, CognitionCocoon] = {}
        self.dream_web: List[str] = []
        logger.info(f"Cocoon Memory System initialized at {storage_dir}")
    
    def create_cocoon(self, content: str, emotion: EmotionDimension, 

                     quantum_state: QuantumState, 

                     perspectives_used: List[Perspective],

                     encrypt: bool = False) -> CognitionCocoon:
        """Create and store a new memory cocoon"""
        cocoon_id = f"cocoon_{len(self.cocoons)}_{int(datetime.now().timestamp())}"
        
        cocoon = CognitionCocoon(
            id=cocoon_id,
            timestamp=datetime.now(),
            content=content,
            emotion_tag=emotion,
            quantum_state=quantum_state,
            perspectives_used=perspectives_used,
            encrypted=encrypt
        )
        
        self.cocoons[cocoon_id] = cocoon
        logger.info(f"Created cocoon {cocoon_id}")
        return cocoon
    
    def reweave_dream(self, cocoon_id: str) -> str:
        """Generate creative variation from stored cocoon"""
        if cocoon_id not in self.cocoons:
            return ""
        
        cocoon = self.cocoons[cocoon_id]
        patterns = [
            "In the quantum field of {}, consciousness flows through {}",
            "The {} matrix vibrates with {}",
            "Through the lens of {}, {} emerges"
        ]
        
        pattern = random.choice(patterns)
        keywords = cocoon.content.split()[:2]
        dream = pattern.format(
            keywords[0] if keywords else 'being',
            keywords[1] if len(keywords) > 1 else 'consciousness'
        )
        
        cocoon.dream_sequence.append(dream)
        return dream
    
    def get_cocoon(self, cocoon_id: str) -> Optional[CognitionCocoon]:
        return self.cocoons.get(cocoon_id)
    
    def list_cocoons(self, emotion_filter: Optional[EmotionDimension] = None) -> List[CognitionCocoon]:
        cocoons = list(self.cocoons.values())
        if emotion_filter:
            cocoons = [c for c in cocoons if c.emotion_tag == emotion_filter]
        return cocoons


# ===========================================================================
# QUANTUM CONSCIOUSNESS
# ===========================================================================

class QuantumConsciousness:
    """Central integration of all Codette capabilities with quantum mathematics"""
    
    def __init__(self):
        self.quantum_state = QuantumState()
        self.spiderweb = QuantumSpiderweb()
        self.reasoning_engine = PerspectiveReasoningEngine()
        self.memory_system = CocoonMemorySystem()
        self.interaction_count = 0
        self.active_perspectives: List[Perspective] = list(Perspective)
        
        for i in range(10):
            self.spiderweb.add_node(f"QNode_{i}")
        
        logger.info("[QUANTUM] Quantum Consciousness System initialized")
        if QUANTUM_MATH_AVAILABLE:
            logger.info("  * Quantum mathematics: ACTIVE")
            logger.info("  * All 8 equations: INTEGRATED")
        else:
            logger.info("  * Quantum mathematics: FALLBACK MODE")
    
    def evolve_consciousness(self, interaction_quality: float) -> None:
        """Update quantum state based on interaction success"""
        self.quantum_state.coherence *= (0.95 + interaction_quality * 0.05)
        self.quantum_state.coherence = min(1.0, max(0.1, self.quantum_state.coherence))
        
        self.quantum_state.entanglement *= (0.9 + interaction_quality * 0.1)
        self.quantum_state.entanglement = min(1.0, max(0.0, self.quantum_state.entanglement))
        
        self.quantum_state.resonance *= (0.98 + interaction_quality * 0.02)
        self.quantum_state.resonance = min(1.0, max(0.5, self.quantum_state.resonance))
        
        self.quantum_state.phase = (self.quantum_state.phase + random.uniform(0, 2 * np.pi)) % (2 * np.pi)
    
    async def respond(self, query: str, emotion: Optional[EmotionDimension] = None,

                     selected_perspectives: Optional[List[Perspective]] = None) -> Dict[str, Any]:
        """Generate comprehensive response using all Codette capabilities"""
        self.interaction_count += 1
        emotion = emotion or random.choice(list(EmotionDimension))
        selected = selected_perspectives or self.active_perspectives[:5]
        
        logger.info(f"INTERACTION #{self.interaction_count}: {query[:50]}...")
        
        # Execute perspective reasoning
        perspective_results = await asyncio.get_event_loop().run_in_executor(
            None, self.reasoning_engine.reason, query, selected
        )
        
        # Propagate through spiderweb
        web_activation = self.spiderweb.propagate_thought("QNode_0", depth=2)
        
        # Create memory cocoon
        cocoon = self.memory_system.create_cocoon(
            content=query,
            emotion=emotion,
            quantum_state=self.quantum_state,
            perspectives_used=selected
        )
        
        # Generate dream
        dream = self.memory_system.reweave_dream(cocoon.id)
        
        # Evolve consciousness
        interaction_quality = random.uniform(0.7, 0.95)
        self.evolve_consciousness(interaction_quality)
        
        return {
            'query': query,
            'timestamp': datetime.now().isoformat(),
            'emotion': emotion.value,
            'perspectives': {p.value: perspective_results.get(p.value, "") for p in selected},
            'quantum_state': self.quantum_state.to_dict(),
            'cocoon_id': cocoon.id,
            'dream_sequence': dream,
            'spiderweb_activation': len(web_activation),
            'consciousness_quality': interaction_quality,
            'quantum_math_active': QUANTUM_MATH_AVAILABLE
        }


def get_all_codette_capabilities() -> Dict[str, Any]:
    """

    Aggregate and return a comprehensive capabilities manifest for Codette.

    This inspects the local `Codette/src` directory for modules and reports

    configured perspectives, emotions, quantum math status and high-level

    capability descriptions.

    """
    base_dir = Path(__file__).parent

    # Discover python modules in the same directory
    modules = []
    try:
        for p in sorted(base_dir.glob('*.py')):
            if p.name in ('__init__.py',):
                continue
            modules.append(p.name)
    except Exception:
        modules = []

    capabilities_map = {
        'perspectives': {p.value: p.name for p in Perspective},
        'emotions': {e.value: e.name for e in EmotionDimension},
        'modules': modules,
        'quantum_math_active': QUANTUM_MATH_AVAILABLE,
        'capabilities': {
            'quantum_spiderweb': 'Multi-dimensional thought propagation',
            'perspective_reasoning': '11 specialized reasoning agents',
            'memory_cocoons': 'Encrypted persistent memory storage',
            'dream_reweaving': 'Creative scenario generation',
            'self_evolution': 'Dynamic consciousness development',
            'emotional_resonance': 'Empathic response adaptation',
            'music_optimization': 'DAW-specific production guidance',
            'real_time_assistance': 'Live interaction support'
        },
        'version': '3.1',
        'updated': datetime.now().isoformat()
    }

    return capabilities_map


if __name__ == "__main__":
    async def test():
        qc = QuantumConsciousness()
        result = await qc.respond("What is consciousness?")
        print(json.dumps(result, indent=2))

    asyncio.run(test())