"""Enterprise MCP tool execution node with circuit breaker protection."""

import random
import time
from typing import Any, Dict

from kailash.nodes.base import Node, NodeMetadata, NodeParameter, register_node
from kailash.sdk_exceptions import NodeExecutionError


@register_node()
class EnterpriseMLCPExecutorNode(Node):
    """Executes MCP tools with enterprise-grade resilience patterns.

    This node provides circuit breaker protection, audit logging,
    and compliance-aware execution for MCP tools.
    """

    metadata = NodeMetadata(
        name="EnterpriseMLCPExecutorNode",
        description="Execute MCP tools with enterprise resilience patterns",
        version="1.0.0",
        tags={"enterprise", "mcp", "resilience"},
    )

    def __init__(self, name: str = None, **kwargs):
        self.name = name or self.__class__.__name__
        super().__init__(name=self.name, **kwargs)

    def get_parameters(self) -> Dict[str, NodeParameter]:
        return {
            "tool_request": NodeParameter(
                name="tool_request",
                type=dict,
                description="Tool execution request from AI agent",
                required=True,
            ),
            "circuit_breaker_enabled": NodeParameter(
                name="circuit_breaker_enabled",
                type=bool,
                description="Enable circuit breaker protection",
                required=False,
                default=True,
            ),
            "success_rate_threshold": NodeParameter(
                name="success_rate_threshold",
                type=float,
                description="Success rate threshold for circuit breaker",
                required=False,
                default=0.8,
            ),
        }

    def run(
        self,
        tool_request: Dict,
        circuit_breaker_enabled: bool = True,
        success_rate_threshold: float = 0.8,
        **kwargs,
    ) -> Dict[str, Any]:
        """Execute MCP tool with resilience patterns."""
        try:
            # Extract tool information
            tool_name = tool_request.get("tool", "unknown")
            params = tool_request.get("parameters", {})
            server_id = tool_request.get("server_id", "default-mcp")

            # Simulate circuit breaker state (in production, this would be persistent)
            # For demo purposes, randomly determine circuit state
            circuit_state = "CLOSED"  # Could be OPEN, HALF_OPEN, CLOSED

            execution_start = time.time()

            if circuit_breaker_enabled and circuit_state == "OPEN":
                return {
                    "success": False,
                    "error": f"Circuit breaker OPEN for {server_id}",
                    "fallback_used": True,
                    "execution_time_ms": 1,
                    "circuit_state": circuit_state,
                }

            # Simulate MCP tool execution with realistic results
            success = random.random() < success_rate_threshold

            if success:
                # Generate realistic mock data based on tool type
                if tool_name == "patient_analytics":
                    data = {
                        "patient_count": random.randint(1000, 2000),
                        "avg_satisfaction": round(random.uniform(3.5, 4.8), 1),
                        "trend": random.choice(["improving", "stable", "declining"]),
                        "compliance_score": round(random.uniform(0.85, 0.98), 2),
                    }
                elif tool_name == "transaction_analysis":
                    data = {
                        "transaction_volume": random.randint(10000000, 20000000),
                        "fraud_rate": round(random.uniform(0.01, 0.05), 3),
                        "avg_transaction": round(random.uniform(100.0, 200.0), 2),
                        "risk_score": round(random.uniform(0.1, 0.3), 2),
                    }
                elif tool_name == "risk_scoring":
                    data = {
                        "overall_risk": round(random.uniform(0.1, 0.4), 2),
                        "categories": {
                            "credit_risk": round(random.uniform(0.05, 0.25), 2),
                            "operational_risk": round(random.uniform(0.02, 0.15), 2),
                            "market_risk": round(random.uniform(0.03, 0.20), 2),
                        },
                        "recommendations": ["Increase reserves", "Monitor exposure"],
                    }
                else:
                    data = {
                        "status": "completed",
                        "records_processed": random.randint(50, 500),
                        "timestamp": time.time(),
                    }

                execution_time = (time.time() - execution_start) * 1000

                result = {
                    "success": True,
                    "data": data,
                    "execution_time_ms": round(
                        execution_time + random.randint(50, 200), 2
                    ),
                    "server_id": server_id,
                    "tool_name": tool_name,
                    "circuit_state": circuit_state,
                    "compliance_validated": True,
                }
            else:
                # Simulate failure
                error_messages = [
                    "Service temporarily unavailable",
                    "Rate limit exceeded",
                    "Authentication failed",
                    "Invalid parameters",
                    "Network timeout",
                ]

                result = {
                    "success": False,
                    "error": random.choice(error_messages),
                    "execution_time_ms": round(
                        (time.time() - execution_start) * 1000
                        + random.randint(100, 500),
                        2,
                    ),
                    "server_id": server_id,
                    "tool_name": tool_name,
                    "circuit_state": circuit_state,
                    "retry_recommended": True,
                }

            # Add audit trail information
            result["audit_info"] = {
                "execution_id": f"exec-{int(time.time())}-{random.randint(1000, 9999)}",
                "timestamp": time.time(),
                "user_context": kwargs.get("user_context", {}),
                "compliance_checked": True,
            }

            # For successful executions, add actions for audit logging
            if result["success"]:
                result["execution_results"] = {
                    "actions": [
                        {
                            "action": f"execute_{tool_name}",
                            "success": True,
                            "server_id": server_id,
                            "data_size": len(str(data)),
                            "timestamp": time.time(),
                        }
                    ],
                    "summary": {
                        "total_actions": 1,
                        "successful_actions": 1,
                        "failed_actions": 0,
                        "execution_time_ms": result["execution_time_ms"],
                    },
                }
            else:
                result["execution_results"] = {
                    "actions": [
                        {
                            "action": f"execute_{tool_name}",
                            "success": False,
                            "error": result["error"],
                            "server_id": server_id,
                            "timestamp": time.time(),
                        }
                    ],
                    "summary": {
                        "total_actions": 1,
                        "successful_actions": 0,
                        "failed_actions": 1,
                        "execution_time_ms": result["execution_time_ms"],
                    },
                }

            return result

        except Exception as e:
            raise NodeExecutionError(f"MCP execution failed: {str(e)}")
