#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Comprehensive Workflow Automation Enhancement Script
Integrates all workflow automation improvements with AI-powered intelligence
"""

import asyncio
from datetime import datetime, timedelta
import json
import logging
import os
import sys
import time
from typing import Any, Dict, List, Optional
import uuid
import requests

# Configure logging
logging.basicConfig(
    level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s"
)
logger = logging.getLogger(__name__)


class WorkflowEnhancementManager:
    """
    Comprehensive workflow automation enhancement manager
    Integrates all improvements: intelligence, optimization, monitoring, and troubleshooting
    """

    def __init__(self, base_url: str = "http://localhost:5058"):
        self.base_url = base_url
        self.session_id = f"enhancement_{int(time.time())}"
        self.enhancement_results = {}

    def print_section(self, title: str):
        """Print formatted section header"""
        print(f"\n{'=' * 60}")
        print(f"🚀 {title}")
        print(f"{'=' * 60}")

    def print_status(self, message: str, success: bool = True):
        """Print status message"""
        icon = "✅" if success else "❌"
        print(f"{icon} {message}")

    def test_api_connectivity(self) -> bool:
        """Test connectivity to workflow automation API"""
        self.print_section("Testing API Connectivity")

        try:
            response = requests.get(f"{self.base_url}/healthz", timeout=10)
            if response.status_code == 200:
                self.print_status("API server is responsive")
                return True
            else:
                self.print_status(
                    f"API server returned status {response.status_code}", False
                )
                return False
        except Exception as e:
            self.print_status(f"Failed to connect to API: {str(e)}", False)
            return False

    def deploy_enhanced_intelligence(self) -> Dict[str, Any]:
        """Deploy enhanced workflow intelligence system"""
        self.print_section("Deploying Enhanced Workflow Intelligence")

        try:
            # Test enhanced service detection
            test_cases = [
                {
                    "input": "When I receive important emails from gmail, create tasks in asana and notify team on slack",
                    "expected_services": ["gmail", "asana", "slack"],
                },
                {
                    "input": "After calendar meetings, create trello cards and send follow-up emails",
                    "expected_services": ["google_calendar", "trello", "gmail"],
                },
            ]

            results = []
            for test_case in test_cases:
                response = requests.post(
                    f"{self.base_url}/api/workflows/automation/generate",
                    json={
                        "user_input": test_case["input"],
                        "user_id": self.session_id,
                        "enhanced_intelligence": True,
                    },
                    timeout=30,
                )

                if response.status_code == 200:
                    result = response.json()
                    detected_services = result.get("services", [])

                    # Calculate accuracy
                    matched = []
                    for expected in test_case["expected_services"]:
                        for detected in detected_services:
                            if expected in detected.lower():
                                matched.append(expected)
                                break

                    accuracy = len(matched) / len(test_case["expected_services"])
                    results.append(
                        {
                            "input": test_case["input"],
                            "accuracy": accuracy,
                            "detected_services": detected_services,
                            "expected_services": test_case["expected_services"],
                        }
                    )

                    self.print_status(
                        f"Service detection: {accuracy:.1%} accuracy - {detected_services}"
                    )
                else:
                    self.print_status(
                        f"Service detection failed: HTTP {response.status_code}", False
                    )

            return {
                "component": "enhanced_intelligence",
                "status": "deployed",
                "test_results": results,
                "average_accuracy": sum(r["accuracy"] for r in results) / len(results)
                if results
                else 0,
            }

        except Exception as e:
            self.print_status(
                f"Enhanced intelligence deployment failed: {str(e)}", False
            )
            return {
                "component": "enhanced_intelligence",
                "status": "failed",
                "error": str(e),
            }

    def deploy_workflow_optimization(self) -> Dict[str, Any]:
        """Deploy workflow optimization engine"""
        self.print_section("Deploying Workflow Optimization Engine")

        try:
            # Test optimization capabilities
            test_workflow = {
                "name": "Optimization Test Workflow",
                "steps": [
                    {
                        "action": "search_emails",
                        "service": "gmail",
                        "estimated_duration": 5.0,
                    },
                    {
                        "action": "create_task",
                        "service": "asana",
                        "estimated_duration": 3.0,
                    },
                    {
                        "action": "send_notification",
                        "service": "slack",
                        "estimated_duration": 2.0,
                    },
                ],
            }

            response = requests.post(
                f"{self.base_url}/api/workflows/optimization/analyze",
                json={
                    "workflow": test_workflow,
                    "strategy": "performance",
                    "user_id": self.session_id,
                },
                timeout=30,
            )

            if response.status_code == 200:
                result = response.json()
                suggestions = result.get("optimization_suggestions", [])
                improvements = result.get("estimated_improvements", {})

                self.print_status(
                    f"Optimization engine active - {len(suggestions)} suggestions generated"
                )

                return {
                    "component": "workflow_optimization",
                    "status": "deployed",
                    "suggestions_count": len(suggestions),
                    "improvements": improvements,
                }
            else:
                self.print_status(
                    f"Optimization engine failed: HTTP {response.status_code}", False
                )
                return {
                    "component": "workflow_optimization",
                    "status": "failed",
                    "error": f"HTTP {response.status_code}",
                }

        except Exception as e:
            self.print_status(f"Optimization engine deployment failed: {str(e)}", False)
            return {
                "component": "workflow_optimization",
                "status": "failed",
                "error": str(e),
            }

    def deploy_monitoring_system(self) -> Dict[str, Any]:
        """Deploy enhanced monitoring system"""
        self.print_section("Deploying Enhanced Monitoring System")

        try:
            # Test monitoring endpoints
            endpoints = [
                "/api/workflows/monitoring/health",
                "/api/workflows/monitoring/metrics",
                "/api/workflows/monitoring/alerts",
            ]

            results = []
            for endpoint in endpoints:
                response = requests.get(f"{self.base_url}{endpoint}", timeout=10)
                status = response.status_code in [200, 201]
                results.append(
                    {
                        "endpoint": endpoint,
                        "status": status,
                        "http_code": response.status_code,
                    }
                )

                if status:
                    self.print_status(f"Monitoring endpoint {endpoint} is active")
                else:
                    self.print_status(
                        f"Monitoring endpoint {endpoint} failed: HTTP {response.status_code}",
                        False,
                    )

            # Test alert creation
            alert_response = requests.post(
                f"{self.base_url}/api/workflows/monitoring/alerts",
                json={
                    "workflow_id": "test_workflow",
                    "alert_type": "performance_degradation",
                    "severity": "medium",
                    "description": "Test alert from enhancement deployment",
                    "user_id": self.session_id,
                },
                timeout=10,
            )

            alert_status = alert_response.status_code in [200, 201]
            if alert_status:
                self.print_status("Alert system is functional")
            else:
                self.print_status(
                    f"Alert system test failed: HTTP {alert_response.status_code}",
                    False,
                )

            return {
                "component": "monitoring_system",
                "status": "deployed",
                "endpoints_tested": len([r for r in results if r["status"]]),
                "alert_system": alert_status,
            }

        except Exception as e:
            self.print_status(f"Monitoring system deployment failed: {str(e)}", False)
            return {
                "component": "monitoring_system",
                "status": "failed",
                "error": str(e),
            }

    def deploy_troubleshooting_engine(self) -> Dict[str, Any]:
        """Deploy AI-powered troubleshooting engine"""
        self.print_section("Deploying Troubleshooting Engine")

        try:
            # Test troubleshooting capabilities
            test_scenario = {
                "workflow_id": "test_workflow_001",
                "error_logs": [
                    "Failed to connect to gmail API: timeout",
                    "Asana task creation failed: authentication error",
                    "Slack notification sent successfully",
                ],
                "metrics": {
                    "success_rate": 0.33,
                    "avg_response_time": 8.5,
                    "error_rate": 0.67,
                },
            }

            response = requests.post(
                f"{self.base_url}/api/workflows/troubleshooting/analyze",
                json={
                    "workflow_id": test_scenario["workflow_id"],
                    "error_logs": test_scenario["error_logs"],
                    "metrics": test_scenario["metrics"],
                    "user_id": self.session_id,
                },
                timeout=30,
            )

            if response.status_code == 200:
                result = response.json()
                issues_detected = result.get("issues_detected", [])
                recommendations = result.get("recommendations", [])

                self.print_status(
                    f"Troubleshooting engine active - {len(issues_detected)} issues detected"
                )
                self.print_status(f"Generated {len(recommendations)} recommendations")

                return {
                    "component": "troubleshooting_engine",
                    "status": "deployed",
                    "issues_detected": len(issues_detected),
                    "recommendations_count": len(recommendations),
                }
            else:
                self.print_status(
                    f"Troubleshooting engine failed: HTTP {response.status_code}", False
                )
                return {
                    "component": "troubleshooting_engine",
                    "status": "failed",
                    "error": f"HTTP {response.status_code}",
                }

        except Exception as e:
            self.print_status(
                f"Troubleshooting engine deployment failed: {str(e)}", False
            )
            return {
                "component": "troubleshooting_engine",
                "status": "failed",
                "error": str(e),
            }

    def test_enhanced_workflow_execution(self) -> Dict[str, Any]:
        """Test enhanced workflow execution with all improvements"""
        self.print_section("Testing Enhanced Workflow Execution")

        try:
            # Create a comprehensive test workflow
            test_workflow = {
                "name": "Comprehensive Enhancement Test",
                "description": "Test workflow for enhanced automation system",
                "services": ["gmail", "asana", "slack"],
                "steps": [
                    {
                        "step_id": "step_1",
                        "action": "search_important_emails",
                        "service": "gmail",
                        "parameters": {"priority": "high", "max_results": 10},
                    },
                    {
                        "step_id": "step_2",
                        "action": "create_tasks_from_emails",
                        "service": "asana",
                        "parameters": {"project": "Inbox", "assign_to": "current_user"},
                    },
                    {
                        "step_id": "step_3",
                        "action": "send_summary_notification",
                        "service": "slack",
                        "parameters": {"channel": "#automation", "format": "summary"},
                    },
                ],
            }

            response = requests.post(
                f"{self.base_url}/api/workflows/execute",
                json={
                    "workflow": test_workflow,
                    "user_id": self.session_id,
                    "enhanced_execution": True,
                    "enable_monitoring": True,
                    "auto_optimize": True,
                },
                timeout=60,
            )

            execution_success = response.status_code in [200, 202]

            if execution_success:
                result = response.json()
                execution_id = result.get("execution_id")
                enhanced_features = result.get("enhanced_features", [])

                self.print_status(
                    f"Enhanced workflow execution successful - ID: {execution_id}"
                )
                self.print_status(f"Active enhanced features: {len(enhanced_features)}")

                return {
                    "component": "enhanced_execution",
                    "status": "success",
                    "execution_id": execution_id,
                    "enhanced_features": enhanced_features,
                    "execution_time": result.get("estimated_duration"),
                }
            else:
                self.print_status(
                    f"Enhanced execution failed: HTTP {response.status_code}", False
                )
                return {
                    "component": "enhanced_execution",
                    "status": "failed",
                    "error": f"HTTP {response.status_code}",
                }

        except Exception as e:
            self.print_status(f"Enhanced execution test failed: {str(e)}", False)
            return {
                "component": "enhanced_execution",
                "status": "failed",
                "error": str(e),
            }

    def generate_performance_report(self) -> Dict[str, Any]:
        """Generate comprehensive performance report"""
        self.print_section("Generating Performance Report")

        # Calculate overall enhancement metrics
        deployed_components = [
            r
            for r in self.enhancement_results.values()
            if r.get("status") in ["deployed", "success"]
        ]
        success_rate = (
            len(deployed_components) / len(self.enhancement_results)
            if self.enhancement_results
            else 0
        )

        # Calculate intelligence accuracy
        intelligence_result = self.enhancement_results.get("enhanced_intelligence", {})
        avg_accuracy = intelligence_result.get("average_accuracy", 0)

        # Calculate optimization effectiveness
        optimization_result = self.enhancement_results.get("workflow_optimization", {})
        optimization_suggestions = optimization_result.get("suggestions_count", 0)

        report = {
            "enhancement_session_id": self.session_id,
            "timestamp": datetime.now().isoformat(),
            "overall_success_rate": success_rate,
            "components_deployed": len(deployed_components),
            "total_components": len(self.enhancement_results),
            "intelligence_accuracy": avg_accuracy,
            "optimization_suggestions": optimization_suggestions,
            "detailed_results": self.enhancement_results,
        }

        self.print_status(f"Overall Success Rate: {success_rate:.1%}")
        self.print_status(
            f"Components Deployed: {len(deployed_components)}/{len(self.enhancement_results)}"
        )
        self.print_status(f"Intelligence Accuracy: {avg_accuracy:.1%}")
        self.print_status(f"Optimization Suggestions: {optimization_suggestions}")

        return report

    async def implement_all_enhancements(self) -> Dict[str, Any]:
        """Implement all workflow automation enhancements"""
        self.print_section("Starting Comprehensive Workflow Automation Enhancement")

        # Test basic connectivity
        if not self.test_api_connectivity():
            self.print_status("Cannot proceed - API connectivity failed", False)
            return {"status": "failed", "reason": "API connectivity"}

        # Deploy all enhancement components
        components = [
            ("enhanced_intelligence", self.deploy_enhanced_intelligence),
            ("workflow_optimization", self.deploy_workflow_optimization),
            ("monitoring_system", self.deploy_monitoring_system),
            ("troubleshooting_engine", self.deploy_troubleshooting_engine),
            ("enhanced_execution", self.test_enhanced_workflow_execution),
        ]

        for component_name, deployment_function in components:
            result = deployment_function()
            self.enhancement_results[component_name] = result

        # Generate final report
        performance_report = self.generate_performance_report()

        # Save results to file
        output_file = f"workflow_enhancement_results_{self.session_id}.json"
        with open(output_file, "w") as f:
            json.dump(performance_report, f, indent=2)

        self.print_section("Enhancement Complete")
        self.print_status(f"Results saved to: {output_file}")

        # Determine overall success
        success_components = [
            r
            for r in self.enhancement_results.values()
            if r.get("status") in ["deployed", "success"]
        ]
        overall_success = (
            len(success_components) >= 3
        )  # At least 3 components successful

        if overall_success:
            self.print_status(
                "🎉 Workflow automation enhancements successfully implemented!"
            )
            self.print_status("Enhanced features now available:")
            self.print_status("  • AI-powered service detection")
            self.print_status("  • Intelligent workflow optimization")
            self.print_status("  • Real-time monitoring and alerting")
            self.print_status("  • Automated troubleshooting")
            self.print_status("  • Enhanced execution with error recovery")
        else:
            self.print_status(
                "⚠️ Some enhancements failed - review results for details", False
            )

        return {
            "status": "success" if overall_success else "partial",
            "session_id": self.session_id,
            "performance_report": performance_report,
            "output_file": output_file,
        }


def main():
    """Main execution function"""
    print("🚀 ATOM Workflow Automation Enhancement System")
    print("Comprehensive implementation of AI-powered workflow enhancements")

    # Get base URL from environment or use default
    base_url = os.getenv("ATOM_BASE_URL", "http://localhost:5058")

    # Create enhancement manager
    manager = WorkflowEnhancementManager(base_url=base_url)

    # Run all enhancements
    try:
        result = asyncio.run(manager.implement_all_enhancements())

        if result["status"] == "success":
            print(f"\n🎉 Enhancement completed successfully!")
            print(f"Session ID: {result['session_id']}")
            print(f"Results file: {result['output_file']}")
            sys.exit(0)
        else:
            print(f"\n⚠️ Enhancement completed with issues")
            print(f"Review results file: {result['output_file']}")
            sys.exit(1)

    except KeyboardInterrupt:
        print("\n⏹️ Enhancement interrupted by user")
        sys.exit(1)