#!/usr/bin/env python3 """ ARTIFICIALLY GENERATED INTELLIGENCE FRAMEWORK 1 Core Integration System """ import asyncio import numpy as np import hashlib import json from datetime import datetime from dataclasses import dataclass, field from typing import Dict, List, Any, Optional from enum import Enum import networkx as nx from cryptography.hazmat.primitives import hashes from cryptography.hazmat.primitives.kdf.hkdf import HKDF import secrets class ComponentType(Enum): QUANTUM_VERIFICATION = "quantum_verification" KNOWLEDGE_GRAPH = "knowledge_graph" CONSCIOUSNESS_MODEL = "consciousness_model" ENTERPRISE_SYSTEM = "enterprise_system" EPISTEMOLOGY_ENGINE = "epistemology_engine" NUMISMATIC_ANALYSIS = "numismatic_analysis" CELESTIAL_CYCLES = "celestial_cycles" @dataclass class ComponentInterface: input_schema: Dict[str, str] output_schema: Dict[str, str] methods: List[str] error_handling: Dict[str, str] @dataclass class SystemComponent: component_type: ComponentType interface: ComponentInterface dependencies: List[ComponentType] implementation: Dict[str, Any] = field(default_factory=dict) class IntegrationEngine: def __init__(self): self.component_registry: Dict[ComponentType, SystemComponent] = {} self.data_flow_graph = nx.DiGraph() self.integration_points: List[Dict[str, Any]] = [] def register_component(self, component: SystemComponent): self.component_registry[component.component_type] = component for dep in component.dependencies: self.data_flow_graph.add_edge(dep, component.component_type) def create_integration_point(self, source: ComponentType, target: ComponentType, data_mapping: Dict[str, str]): integration_id = f"int_{source.value}_{target.value}" self.integration_points.append({ 'id': integration_id, 'source': source, 'target': target, 'data_mapping': data_mapping, 'created': datetime.utcnow().isoformat() }) class QuantumVerificationComponent: def __init__(self): self.entropy_pool = secrets.token_bytes(64) def seal_claim(self, claim_data: Dict) -> Dict: data_str = json.dumps(claim_data, sort_keys=True) blake_hash = hashlib.blake3(data_str.encode()).digest() hkdf = HKDF( algorithm=hashes.SHA512(), length=64, salt=secrets.token_bytes(16), info=b'quantum_verification', ) return { "crypto_hash": hkdf.derive(blake_hash).hex(), "temporal_hash": hashlib.sha256(str(datetime.utcnow().timestamp()).encode()).hexdigest() } class KnowledgeGraphComponent: def __init__(self): self.graph = nx.MultiDiGraph() self.node_registry = {} def add_node(self, node_id: str, content: str, metadata: Dict): self.graph.add_node(node_id, content=content, metadata=metadata) self.node_registry[node_id] = datetime.utcnow().isoformat() def detect_contradictions(self, node_id: str) -> List[str]: contradictions = [] node_data = self.graph.nodes[node_id] for other_id in self.graph.nodes(): if other_id != node_id: other_data = self.graph.nodes[other_id] if self._semantic_conflict(node_data, other_data): contradictions.append(other_id) return contradictions def _semantic_conflict(self, data1: Dict, data2: Dict) -> bool: return False class ConsciousnessModelComponent: def __init__(self): self.state_history = [] self.current_state = "observational" def update_state(self, new_state: str, evidence: Dict): transition = { 'from': self.current_state, 'to': new_state, 'evidence': evidence, 'timestamp': datetime.utcnow().isoformat() } self.state_history.append(transition) self.current_state = new_state return transition def calculate_coherence(self, activations: Dict) -> float: if not activations: return 0.0 values = list(activations.values()) return float(np.mean(values)) class EnterpriseSystemComponent: def __init__(self): self.api_endpoints = {} self.security_tokens = {} def deploy_component(self, component_id: str, config: Dict) -> bool: self.api_endpoints[component_id] = { 'config': config, 'deployed_at': datetime.utcnow().isoformat(), 'status': 'active' } return True def monitor_system(self) -> Dict: return { 'active_components': len(self.api_endpoints), 'system_health': 'operational', 'timestamp': datetime.utcnow().isoformat() } class EpistemologyEngineComponent: def __init__(self): self.processing_history = [] self.method_registry = {} def process_catalyst(self, catalyst: Dict) -> Dict: result = { 'processed_catalyst': catalyst, 'understanding_metrics': { 'complexity': len(str(catalyst)) / 1000, 'domain_coverage': 0.7, 'certainty': 0.8 }, 'timestamp': datetime.utcnow().isoformat() } self.processing_history.append(result) return result class NumismaticAnalysisComponent: def __init__(self): self.coin_database = {} self.anomaly_registry = {} def analyze_coin(self, coin_data: Dict) -> Dict: analysis = { 'weight_variance': abs(coin_data.get('weight', 0) - 5.67) / 5.67, 'composition_match': 0.9, 'historical_context': 'verified', 'anomalies_detected': [] } return analysis class CelestialCyclesComponent: def __init__(self): self.cycle_data = {} self.alignment_history = [] def calculate_alignment(self, bodies: List[str], timeframe: Dict) -> Dict: return { 'bodies_aligned': bodies, 'alignment_strength': 0.75, 'temporal_markers': ['current_cycle'], 'calculated_at': datetime.utcnow().isoformat() } class AGIFramework: def __init__(self): self.integrator = IntegrationEngine() self.components = {} self.initialize_components() self.define_integrations() def initialize_components(self): quantum_verif = SystemComponent( component_type=ComponentType.QUANTUM_VERIFICATION, interface=ComponentInterface( input_schema={'claim_data': 'dict'}, output_schema={'seal': 'dict'}, methods=['seal_claim'], error_handling={'invalid_input': 'return_error', 'crypto_failure': 'retry'} ), dependencies=[], implementation={'instance': QuantumVerificationComponent()} ) knowledge_graph = SystemComponent( component_type=ComponentType.KNOWLEDGE_GRAPH, interface=ComponentInterface( input_schema={'node_data': 'dict'}, output_schema={'graph_operations': 'dict'}, methods=['add_node', 'detect_contradictions'], error_handling={'node_exists': 'update', 'invalid_data': 'reject'} ), dependencies=[ComponentType.QUANTUM_VERIFICATION], implementation={'instance': KnowledgeGraphComponent()} ) consciousness_model = SystemComponent( component_type=ComponentType.CONSCIOUSNESS_MODEL, interface=ComponentInterface( input_schema={'state_data': 'dict'}, output_schema={'state_analysis': 'dict'}, methods=['update_state', 'calculate_coherence'], error_handling={'invalid_state': 'default_observational', 'data_error': 'log_only'} ), dependencies=[ComponentType.KNOWLEDGE_GRAPH], implementation={'instance': ConsciousnessModelComponent()} ) enterprise_system = SystemComponent( component_type=ComponentType.ENTERPRISE_SYSTEM, interface=ComponentInterface( input_schema={'deployment_config': 'dict'}, output_schema={'system_status': 'dict'}, methods=['deploy_component', 'monitor_system'], error_handling={'deployment_failed': 'rollback', 'security_breach': 'shutdown'} ), dependencies=[ComponentType.QUANTUM_VERIFICATION, ComponentType.CONSCIOUSNESS_MODEL], implementation={'instance': EnterpriseSystemComponent()} ) epistemology_engine = SystemComponent( component_type=ComponentType.EPISTEMOLOGY_ENGINE, interface=ComponentInterface( input_schema={'catalyst': 'dict'}, output_schema={'understanding_vector': 'dict'}, methods=['process_catalyst'], error_handling={'processing_error': 'fallback_analysis', 'timeout': 'queue_retry'} ), dependencies=[ComponentType.CONSCIOUSNESS_MODEL, ComponentType.KNOWLEDGE_GRAPH], implementation={'instance': EpistemologyEngineComponent()} ) numismatic_analysis = SystemComponent( component_type=ComponentType.NUMISMATIC_ANALYSIS, interface=ComponentInterface( input_schema={'coin_data': 'dict'}, output_schema={'analysis_results': 'dict'}, methods=['analyze_coin'], error_handling={'invalid_coin_data': 'skip', 'database_error': 'cache_retry'} ), dependencies=[ComponentType.KNOWLEDGE_GRAPH], implementation={'instance': NumismaticAnalysisComponent()} ) celestial_cycles = SystemComponent( component_type=ComponentType.CELESTIAL_CYCLES, interface=ComponentInterface( input_schema={'celestial_data': 'dict'}, output_schema={'cycle_analysis': 'dict'}, methods=['calculate_alignment'], error_handling={'invalid_data': 'default_cycle', 'calculation_error': 'approximate'} ), dependencies=[ComponentType.KNOWLEDGE_GRAPH], implementation={'instance': CelestialCyclesComponent()} ) components = [quantum_verif, knowledge_graph, consciousness_model, enterprise_system, epistemology_engine, numismatic_analysis, celestial_cycles] for component in components: self.integrator.register_component(component) self.components[component.component_type] = component def define_integrations(self): integrations = [ (ComponentType.QUANTUM_VERIFICATION, ComponentType.KNOWLEDGE_GRAPH, {'seal': 'integrity_hash'}), (ComponentType.KNOWLEDGE_GRAPH, ComponentType.CONSCIOUSNESS_MODEL, {'contradictions': 'cognitive_dissonance'}), (ComponentType.CONSCIOUSNESS_MODEL, ComponentType.EPISTEMOLOGY_ENGINE, {'coherence_score': 'processing_confidence'}), (ComponentType.NUMISMATIC_ANALYSIS, ComponentType.KNOWLEDGE_GRAPH, {'anomalies': 'historical_contradictions'}), (ComponentType.CELESTIAL_CYCLES, ComponentType.KNOWLEDGE_GRAPH, {'alignment_strength': 'temporal_certainty'}), (ComponentType.QUANTUM_VERIFICATION, ComponentType.ENTERPRISE_SYSTEM, {'crypto_hash': 'request_validation'}) ] for source, target, mapping in integrations: self.integrator.create_integration_point(source, target, mapping) async def execute_workflow(self, start_component: ComponentType, input_data: Dict) -> Dict: current_component = start_component current_data = input_data execution_path = [] results = {} while current_component: execution_path.append(current_component.value) component = self.components[current_component] instance = component.implementation['instance'] method_name = component.interface.methods[0] method = getattr(instance, method_name) if asyncio.iscoroutinefunction(method): result = await method(current_data) else: result = method(current_data) results[current_component.value] = result next_components = list(self.integrator.data_flow_graph.successors(current_component)) if not next_components: break current_component = next_components[0] integration_key = f"{execution_path[-1]}_{current_component.value}" integration = next((i for i in self.integrator.integration_points if i['id'] == f"int_{integration_key}"), None) if integration: current_data = self._transform_data(result, integration['data_mapping']) else: current_data = result return { 'execution_path': execution_path, 'component_results': results, 'final_output': current_data, 'timestamp': datetime.utcnow().isoformat() } def _transform_data(self, source_data: Dict, mapping: Dict[str, str]) -> Dict: transformed = {} for source_key, target_key in mapping.items(): if source_key in source_data: transformed[target_key] = source_data[source_key] return transformed def get_system_status(self) -> Dict: return { 'registered_components': len(self.components), 'integration_points': len(self.integrator.integration_points), 'data_flow_edges': list(self.integrator.data_flow_graph.edges()), 'system_initialized': True } # Component factory for dynamic instantiation class ComponentFactory: @staticmethod def create_component(component_type: ComponentType) -> Any: component_map = { ComponentType.QUANTUM_VERIFICATION: QuantumVerificationComponent, ComponentType.KNOWLEDGE_GRAPH: KnowledgeGraphComponent, ComponentType.CONSCIOUSNESS_MODEL: ConsciousnessModelComponent, ComponentType.ENTERPRISE_SYSTEM: EnterpriseSystemComponent, ComponentType.EPISTEMOLOGY_ENGINE: EpistemologyEngineComponent, ComponentType.NUMISMATIC_ANALYSIS: NumismaticAnalysisComponent, ComponentType.CELESTIAL_CYCLES: CelestialCyclesComponent } return component_map[component_type]() # Data validation and schema enforcement class SchemaValidator: def __init__(self): self.schema_registry = {} def register_schema(self, schema_name: str, schema: Dict[str, str]): self.schema_registry[schema_name] = schema def validate_data(self, data: Dict, schema_name: str) -> bool: if schema_name not in self.schema_registry: return False schema = self.schema_registry[schema_name] return all(field in data for field in schema.keys()) # Error handling and recovery system class ErrorHandler: def __init__(self): self.error_log = [] self.recovery_strategies = {} def log_error(self, component: ComponentType, error: Exception, context: Dict): error_entry = { 'component': component.value, 'error_type': type(error).__name__, 'error_message': str(error), 'context': context, 'timestamp': datetime.utcnow().isoformat() } self.error_log.append(error_entry) def register_recovery_strategy(self, error_type: str, strategy: callable): self.recovery_strategies[error_type] = strategy def attempt_recovery(self, error: Exception, context: Dict) -> Any: error_type = type(error).__name__ if error_type in self.recovery_strategies: return self.recovery_strategies[error_type](error, context) return None # Performance monitoring and metrics class PerformanceMonitor: def __init__(self): self.metrics = {} self.execution_times = {} def start_timing(self, operation: str): self.execution_times[operation] = datetime.utcnow() def stop_timing(self, operation: str): if operation in self.execution_times: start_time = self.execution_times[operation] duration = (datetime.utcnow() - start_time).total_seconds() if operation not in self.metrics: self.metrics[operation] = [] self.metrics[operation].append(duration) def get_metrics(self) -> Dict[str, Any]: summary = {} for operation, times in self.metrics.items(): if times: summary[operation] = { 'count': len(times), 'average_time': sum(times) / len(times), 'min_time': min(times), 'max_time': max(times) } return summary # Main system controller class AGIController: def __init__(self): self.framework = AGIFramework() self.validator = SchemaValidator() self.error_handler = ErrorHandler() self.performance_monitor = PerformanceMonitor() self.workflow_registry = {} async def execute_workflow_with_monitoring(self, start_component: ComponentType, input_data: Dict) -> Dict: workflow_id = f"workflow_{hashlib.sha256(str(input_data).encode()).hexdigest()[:12]}" self.performance_monitor.start_timing(workflow_id) try: result = await self.framework.execute_workflow(start_component, input_data) self.performance_monitor.stop_timing(workflow_id) self.workflow_registry[workflow_id] = result return { 'workflow_id': workflow_id, 'success': True, 'result': result, 'performance_metrics': self.performance_monitor.get_metrics().get(workflow_id, {}) } except Exception as e: self.error_handler.log_error(start_component, e, {'input_data': input_data}) self.performance_monitor.stop_timing(workflow_id) return { 'workflow_id': workflow_id, 'success': False, 'error': str(e), 'component': start_component.value } def get_system_health(self) -> Dict: framework_status = self.framework.get_system_status() performance_metrics = self.performance_monitor.get_metrics() error_count = len(self.error_handler.error_log) return { 'framework_status': framework_status, 'performance_metrics': performance_metrics, 'error_count': error_count, 'active_workflows': len(self.workflow_registry), 'system_uptime': 'operational' }