Create AGI_BASE_FRAME_1

A base version for the overall agi framework

AGI_BASE_FRAME_1

@@ -0,0 +1,514 @@
+#!/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'
+        }