AGI_BASE_FRAME_1

#!/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'
        }