# -*- 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())