
# -*- coding: utf-8 -*-
"""
Agent动作执行器 - 执行具体的Agent动作
"""

import logging
import asyncio
from typing import Dict, Any, List, Optional
from datetime import datetime
import json

from .intelligent_agent import AgentAction, ActionType, AlertContext, KnowledgeContext

logger = logging.getLogger(__name__)

class ActionExecutor:
    """动作执行器"""
    
    def __init__(self, tsp_assistant=None):
        self.tsp_assistant = tsp_assistant
        self.execution_history = []
        self.action_handlers = {
            ActionType.ALERT_RESPONSE: self._handle_alert_response,
            ActionType.KNOWLEDGE_UPDATE: self._handle_knowledge_update,
            ActionType.WORKORDER_CREATE: self._handle_workorder_create,
            ActionType.SYSTEM_OPTIMIZE: self._handle_system_optimize,
            ActionType.USER_NOTIFY: self._handle_user_notify
        }
    
    async def execute_action(self, action: AgentAction) -> Dict[str, Any]:
        """执行动作"""
        try:
            logger.info(f"开始执行动作: {action.action_type.value}")
            start_time = datetime.now()
            
            # 获取处理器
            handler = self.action_handlers.get(action.action_type)
            if not handler:
                return {"success": False, "error": f"未找到动作处理器: {action.action_type}"}
            
            # 执行动作
            result = await handler(action)
            
            # 记录执行历史
            execution_record = {
                "action_id": f"{action.action_type.value}_{datetime.now().timestamp()}",
                "action_type": action.action_type.value,
                "description": action.description,
                "priority": action.priority,
                "confidence": action.confidence,
                "start_time": start_time.isoformat(),
                "end_time": datetime.now().isoformat(),
                "success": result.get("success", False),
                "result": result
            }
            self.execution_history.append(execution_record)
            
            logger.info(f"动作执行完成: {action.action_type.value}, 结果: {result.get('success', False)}")
            return result
            
        except Exception as e:
            logger.error(f"执行动作失败: {e}")
            return {"success": False, "error": str(e)}
    
    async def _handle_alert_response(self, action: AgentAction) -> Dict[str, Any]:
        """处理预警响应"""
        try:
            alert_id = action.parameters.get("alert_id")
            service = action.parameters.get("service")
            
            # 根据动作描述执行具体操作
            if "重启" in action.description:
                return await self._restart_service(service)
            elif "检查" in action.description:
                return await self._check_system_status(alert_id)
            elif "通知" in action.description:
                return await self._notify_alert(alert_id, action.description)
            else:
                return await self._generic_alert_response(action)
                
        except Exception as e:
            logger.error(f"处理预警响应失败: {e}")
            return {"success": False, "error": str(e)}
    
    async def _handle_knowledge_update(self, action: AgentAction) -> Dict[str, Any]:
        """处理知识库更新"""
        try:
            question = action.parameters.get("question")
            enhanced_answer = action.parameters.get("enhanced_answer")
            
            if enhanced_answer:
                # 更新知识库条目
                if self.tsp_assistant:
                    # 这里调用TSP助手的知识库更新方法
                    result = await self._update_knowledge_entry(question, enhanced_answer)
                    return result
                else:
                    return {"success": True, "message": "知识库条目已标记更新"}
            else:
                # 标记低置信度条目
                return await self._mark_low_confidence_knowledge(question)
                
        except Exception as e:
            logger.error(f"处理知识库更新失败: {e}")
            return {"success": False, "error": str(e)}
    
    async def _handle_workorder_create(self, action: AgentAction) -> Dict[str, Any]:
        """处理工单创建"""
        try:
            title = action.parameters.get("title", "Agent自动创建工单")
            description = action.description
            category = action.parameters.get("category", "系统问题")
            priority = action.parameters.get("priority", "medium")
            
            if self.tsp_assistant:
                # 调用TSP助手创建工单
                workorder = self.tsp_assistant.create_work_order(
                    title=title,
                    description=description,
                    category=category,
                    priority=priority
                )
                return {"success": True, "workorder": workorder}
            else:
                return {"success": True, "message": "工单创建请求已记录"}
                
        except Exception as e:
            logger.error(f"处理工单创建失败: {e}")
            return {"success": False, "error": str(e)}
    
    async def _handle_system_optimize(self, action: AgentAction) -> Dict[str, Any]:
        """处理系统优化"""
        try:
            optimization_type = action.parameters.get("type", "general")
            
            if optimization_type == "performance":
                return await self._optimize_performance(action)
            elif optimization_type == "memory":
                return await self._optimize_memory(action)
            elif optimization_type == "database":
                return await self._optimize_database(action)
            else:
                return await self._general_optimization(action)
                
        except Exception as e:
            logger.error(f"处理系统优化失败: {e}")
            return {"success": False, "error": str(e)}
    
    async def _handle_user_notify(self, action: AgentAction) -> Dict[str, Any]:
        """处理用户通知"""
        try:
            message = action.description
            user_id = action.parameters.get("user_id", "admin")
            notification_type = action.parameters.get("type", "info")
            
            # 这里实现具体的通知逻辑
            # 可以是邮件、短信、系统通知等
            return await self._send_notification(user_id, message, notification_type)
            
        except Exception as e:
            logger.error(f"处理用户通知失败: {e}")
            return {"success": False, "error": str(e)}
    
    # 具体实现方法
    async def _restart_service(self, service: str) -> Dict[str, Any]:
        """重启服务"""
        logger.info(f"重启服务: {service}")
        # 这里实现具体的服务重启逻辑
        await asyncio.sleep(2)  # 模拟重启时间
        return {"success": True, "message": f"服务 {service} 已重启"}
    
    async def _check_system_status(self, alert_id: str) -> Dict[str, Any]:
        """检查系统状态"""
        logger.info(f"检查系统状态: {alert_id}")
        # 这里实现具体的系统检查逻辑
        await asyncio.sleep(1)
        return {"success": True, "status": "正常", "alert_id": alert_id}
    
    async def _notify_alert(self, alert_id: str, message: str) -> Dict[str, Any]:
        """通知预警"""
        logger.info(f"通知预警: {alert_id} - {message}")
        # 这里实现具体的通知逻辑
        return {"success": True, "message": "预警通知已发送"}
    
    async def _generic_alert_response(self, action: AgentAction) -> Dict[str, Any]:
        """通用预警响应"""
        logger.info(f"执行通用预警响应: {action.description}")
        return {"success": True, "message": "预警响应已执行"}
    
    async def _update_knowledge_entry(self, question: str, enhanced_answer: str) -> Dict[str, Any]:
        """更新知识库条目"""
        logger.info(f"更新知识库条目: {question}")
        # 这里实现具体的知识库更新逻辑
        return {"success": True, "message": "知识库条目已更新"}
    
    async def _mark_low_confidence_knowledge(self, question: str) -> Dict[str, Any]:
        """标记低置信度知识"""
        logger.info(f"标记低置信度知识: {question}")
        # 这里实现具体的标记逻辑
        return {"success": True, "message": "低置信度知识已标记"}
    
    async def _optimize_performance(self, action: AgentAction) -> Dict[str, Any]:
        """性能优化"""
        logger.info("执行性能优化")
        # 这里实现具体的性能优化逻辑
        return {"success": True, "message": "性能优化已执行"}
    
    async def _optimize_memory(self, action: AgentAction) -> Dict[str, Any]:
        """内存优化"""
        logger.info("执行内存优化")
        # 这里实现具体的内存优化逻辑
        return {"success": True, "message": "内存优化已执行"}
    
    async def _optimize_database(self, action: AgentAction) -> Dict[str, Any]:
        """数据库优化"""
        logger.info("执行数据库优化")
        # 这里实现具体的数据库优化逻辑
        return {"success": True, "message": "数据库优化已执行"}
    
    async def _general_optimization(self, action: AgentAction) -> Dict[str, Any]:
        """通用优化"""
        logger.info(f"执行通用优化: {action.description}")
        return {"success": True, "message": "系统优化已执行"}
    
    async def _send_notification(self, user_id: str, message: str, notification_type: str) -> Dict[str, Any]:
        """发送通知"""
        logger.info(f"发送通知给 {user_id}: {message}")
        # 这里实现具体的通知发送逻辑
        return {"success": True, "message": "通知已发送"}
    
    def get_execution_history(self, limit: int = 100) -> List[Dict[str, Any]]:
        """获取执行历史"""
        return self.execution_history[-limit:]
    
    def get_action_statistics(self) -> Dict[str, Any]:
        """获取动作统计"""
        total_actions = len(self.execution_history)
        successful_actions = sum(1 for record in self.execution_history if record["success"])
        
        action_types = {}
        for record in self.execution_history:
            action_type = record["action_type"]
            if action_type not in action_types:
                action_types[action_type] = {"total": 0, "successful": 0}
            action_types[action_type]["total"] += 1
            if record["success"]:
                action_types[action_type]["successful"] += 1
        
        return {
            "total_actions": total_actions,
            "successful_actions": successful_actions,
            "success_rate": successful_actions / total_actions if total_actions > 0 else 0,
            "action_types": action_types
        }
