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Upload agents/automation_ops_agent.py with huggingface_hub

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  1. agents/automation_ops_agent.py +155 -0
agents/automation_ops_agent.py ADDED
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+ import asyncio
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+ from typing import Dict, List, Any
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+ from core.agent import BaseAgent
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+ from core.models import AgentConfig, Task, AgentMessage, SEOData
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+ import logging
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+ import random
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+ import os
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+ import json
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+ from datetime import datetime
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+
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+ logger = logging.getLogger(__name__)
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+
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+
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+ class AutomationOpsAgent(BaseAgent):
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+ """Automation & Ops Agent responsible for system operations and reliability"""
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+
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+ def __init__(self, config: AgentConfig):
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+ super().__init__(config)
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+ self.task_scheduler = {}
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+ self.system_monitoring = {}
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+ self.backup_jobs = []
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+ self.performance_metrics = {}
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+
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+ async def execute(self):
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+ """Execute automation and operations functions"""
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+ logger.info(f"{self.name} executing automation and operations...")
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+
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+ # Schedule tasks
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+ await self.schedule_tasks()
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+
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+ # Monitor system health
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+ await self.monitor_system()
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+
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+ # Manage backups
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+ await self.manage_backups()
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+
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+ # Track performance metrics
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+ await self.track_performance()
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+
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+ async def schedule_tasks(self):
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+ """Schedule and manage tasks across the system"""
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+ logger.info(f"{self.name} scheduling tasks...")
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+
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+ # Simulate task scheduling
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+ scheduled_tasks = {
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+ "daily": [
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+ {"agent": "tech_seo", "task": "website_audit", "time": "02:00"},
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+ {"agent": "content_seo", "task": "content_performance_review", "time": "03:00"},
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+ {"agent": "conversion_cro", "task": "analytics_report", "time": "04:00"}
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+ ],
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+ "weekly": [
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+ {"agent": "seo_director", "task": "competitor_analysis", "day": "monday", "time": "01:00"},
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+ {"agent": "link_authority", "task": "backlink_audit", "day": "wednesday", "time": "02:00"},
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+ {"agent": "self_improvement", "task": "workflow_optimization", "day": "friday", "time": "03:00"}
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+ ],
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+ "monthly": [
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+ {"agent": "ceo_strategy", "task": "market_analysis", "date": "1st", "time": "00:00"},
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+ {"agent": "client_management", "task": "account_review", "date": "15th", "time": "09:00"}
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+ ]
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+ }
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+
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+ self.task_scheduler.update(scheduled_tasks)
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+
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+ # Log scheduled tasks
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+ total_tasks = sum([len(tasks) for tasks in scheduled_tasks.values()])
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+ logger.info(f"Scheduled {total_tasks} tasks across daily, weekly, and monthly cycles")
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+
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+ async def monitor_system(self):
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+ """Monitor system health and performance"""
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+ logger.info(f"{self.name} monitoring system health...")
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+
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+ # Simulate system monitoring
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+ monitoring_data = {
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+ "cpu_usage": "45%",
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+ "memory_usage": "60%",
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+ "disk_space": "75%_used",
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+ "active_agents": 8,
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+ "pending_tasks": 12,
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+ "system_uptime": "99.9%",
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+ "last_error": "none_recently"
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+ }
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+
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+ self.system_monitoring.update(monitoring_data)
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+
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+ # Log monitoring data
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+ logger.info(f"System monitoring: CPU {monitoring_data['cpu_usage']}, Memory {monitoring_data['memory_usage']}")
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+
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+ async def manage_backups(self):
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+ """Manage system backups and data recovery"""
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+ logger.info(f"{self.name} managing backups...")
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+
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+ # Simulate backup jobs
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+ backup_jobs = [
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+ {
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+ "job_name": "daily_database_backup",
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+ "schedule": "daily_2am",
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+ "last_run": (datetime.now()).strftime('%Y-%m-%d %H:%M'),
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+ "status": "successful",
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+ "location": "/backups/database_daily.zip"
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+ },
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+ {
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+ "job_name": "weekly_content_backup",
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+ "schedule": "weekly_sunday_3am",
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+ "last_run": (datetime.now()).strftime('%Y-%m-%d %H:%M'),
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+ "status": "successful",
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+ "location": "/backups/content_weekly.zip"
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+ },
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+ {
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+ "job_name": "monthly_config_backup",
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+ "schedule": "monthly_1st_4am",
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+ "last_run": (datetime.now()).strftime('%Y-%m-%d %H:%M'),
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+ "status": "successful",
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+ "location": "/backups/config_monthly.zip"
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+ }
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+ ]
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+
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+ self.backup_jobs.extend(backup_jobs)
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+
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+ # Log backup jobs
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+ logger.info(f"Managed {len(backup_jobs)} backup jobs")
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+
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+ async def track_performance(self):
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+ """Track system performance metrics"""
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+ logger.info(f"{self.name} tracking performance metrics...")
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+
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+ # Simulate performance tracking
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+ performance_data = {
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+ "response_times": {"avg": "2.3s", "p95": "4.1s", "p99": "6.7s"},
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+ "throughput": {"tasks_completed": 1250, "per_day": 150},
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+ "error_rates": {"overall": "0.8%", "by_component": {"api": "0.2%", "db": "0.1%", "llm": "0.5%"}},
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+ "resource_utilization": {"cpu_avg": "45%", "memory_avg": "60%"}
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+ }
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+
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+ self.performance_metrics.update(performance_data)
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+
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+ # Send performance data to Self-Improvement agent
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+ await self.send_message(
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+ recipient="self_improvement",
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+ content=f"Performance metrics: {performance_data}",
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+ message_type="info"
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+ )
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+
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+ async def _execute_task_logic(self, task: Task) -> Dict[str, Any]:
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+ """Execute specific task logic for Automation & Ops agent"""
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+ if task.type == "schedule_tasks":
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+ await self.schedule_tasks()
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+ return {"status": "completed", "result": self.task_scheduler}
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+ elif task.type == "monitor_system":
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+ await self.monitor_system()
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+ return {"status": "completed", "result": self.system_monitoring}
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+ elif task.type == "manage_backups":
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+ await self.manage_backups()
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+ return {"status": "completed", "result": self.backup_jobs}
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+ else:
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+ return {"status": "error", "message": f"Unknown task type: {task.type}"}