from ..base_gcp_agent import BaseGCPAgent
from ..gcp_connector import GCPConnector
from datetime import datetime, timedelta
from googleapiclient import discovery

class CostManagementAgent(BaseGCPAgent):
    """
    An agent specialized in handling GCP Cost Management tasks.
    """

    def execute(self, command: str, **kwargs):
        """
        Executes a given command related to Cost Management.
        """
        if command == 'get_cost_trends':
            return self._get_cost_trends(**kwargs)
        else:
            raise NotImplementedError(f"Command '{command}' is not supported by CostManagementAgent.")

    def _get_cost_trends(self, project_id: str, days: int = 30):
        """
        Retrieves cost trends for a specified project over a given period.
        Note: This requires a billing account linked to the project and appropriate permissions.
        This implementation uses a placeholder as direct cost trend API is complex and requires
        BigQuery Export or Cloud Billing API with specific setup.
        """
        print(f"CostManagementAgent: Getting cost trends for project '{project_id}' for the last {days} days...")
        try:
            # Placeholder for actual cost trend retrieval.
            # In a real scenario, this would involve:
            # 1. Enabling Cloud Billing API.
            # 2. Setting up BigQuery Export for billing data.
            # 3. Querying BigQuery for cost data.
            # 4. Alternatively, using the Cloud Billing API (which is more complex for trends).

            # For demonstration, we'll return a simulated trend.
            end_date = datetime.now()
            start_date = end_date - timedelta(days=days)

            simulated_data = {
                "period": f"{start_date.strftime('%Y-%m-%d')} to {end_date.strftime('%Y-%m-%d')}",
                "total_estimated_cost_usd": f"{(days * 10.5):.2f}", # Example: $10.50 per day
                "currency": "USD",
                "details": "(Simulated data: Actual implementation requires Cloud Billing API and/or BigQuery Export setup)"
            }

            return {"status": "success", "message": f"Simulated cost trends for project '{project_id}'.", "cost_trends": simulated_data}
        except Exception as e:
            print(f"Error getting cost trends: {e}")
            return {"status": "error", "message": str(e)}