#!/usr/bin/env python3
import requests
import pandas as pd
from datetime import datetime

class AgenticSupervisor:
    def __init__(self, config_path="supervisor_config.yml"):
        self.config = self._load_config(config_path)
        self.df = pd.read_csv(self.config['master_plan_path'])
        
    def _load_config(self, path):
        try:
            import yaml
            with open(path) as f:
                return yaml.safe_load(f)
        except Exception as e:
            self._alert(f"Config load failed: {str(e)}", critical=True)
    
    def _alert(self, message, critical=False):
        if critical:
            requests.post(self.config['alerts']['pagerduty'], json={
                "title": "CRITICAL: Agentic Supervisor",
                "message": message
            })
        print(f"[{datetime.now()}] {message}")

    def check_workflows(self):
        for _, row in self.df.iterrows():
            try:
                resp = requests.get(
                    f"{self.config['workflow_api']}/status/{row['Component']}",
                    timeout=5
                )
                if resp.status_code != 200:
                    self._alert(f"Workflow DOWN: {row['Component']}", critical=True)
            except Exception as e:
                self._alert(f"Workflow check failed: {str(e)}")

    def enforce_sla(self):
        for _, row in self.df[self.df['SLA_Penalty'].notna()].iterrows():
            metric = get_metric(row['Component'])  # Placeholder
            if metric > float(row['SLA_Threshold']):
                self._alert(f"SLA Violation: {row['Component']} at {metric}")

if __name__ == "__main__":
    supervisor = AgenticSupervisor()
    supervisor.check_workflows()
    supervisor.enforce_sla()