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main.py
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main.py
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from agents.autonomous_agent import AutonomousAgent
from models.autonomous_model_manager import AutonomousModelManager
from auto_improvement.autonomous_learning import AutonomousLearning
from monitoring.alert_system import AlertSystem
from supervision.autonomous_supervisor import AutonomousSupervisor
from data.datasets import load_data, preprocess_data
from models.auto_ml import auto_ml_tuning
# Initialize autonomous model manager and other components
alert_system = AlertSystem()
auto_ml_manager = auto_ml_tuning
autonomous_model_manager = AutonomousModelManager(transformer_model, auto_ml_manager)
autonomous_learning = AutonomousLearning(autonomous_model_manager)
# Autonomous supervisor for self-audit and intervention
autonomous_supervisor = AutonomousSupervisor()
# Creation of the autonomous agent
autonomous_agent = AutonomousAgent(
model=transformer_model,
agent_id=1,
autonomous_learning=autonomous_learning,
alert_system=alert_system
)
# Load and preprocess example data
data = load_data('data/sample_data.csv')
processed_data = preprocess_data(data)
# Execute an autonomous task
result = autonomous_agent.perform_task(processed_data)
# Add and execute prioritized tasks
autonomous_agent.add_task({"name": "Data Analysis", "priority": 3, "run": lambda: print("Executing data analysis...")})
autonomous_agent.add_task({"name": "Performance Report", "priority": 2, "run": lambda: print("Generating performance report...")})
autonomous_agent.execute_tasks()
# Automatic monitoring and intervention by the autonomous supervisor
autonomous_supervisor.audit_agent(agent_id=autonomous_agent.id, action="Access Allowed", context="Safe Task")
autonomous_supervisor.monitor_performance(agent_id=autonomous_agent.id, metric="accuracy", value=0.78)
# Display alert and KPI reports
print("Alert report:", alert_system.get_all_alerts())
kpi_report = autonomous_supervisor.performance_monitor.generate_kpi_report()
print("KPI Report:", kpi_report)
print("Autonomous superintelligence system successfully initiated.")