import time
import uuid
from typing import List, Dict, Any
from dataclasses import dataclass
from enum import Enum
import json
import logging
import asyncio
from .llm_executor import LLMExecutor

# 任务状态枚举
class TaskStatus(Enum):
    PENDING = "pending"  # 等待中
    IN_PROGRESS = "in_progress"  # 进行中
    COMPLETED = "completed"  # 已完成
    FAILED = "failed"  # 已失败

# 步骤状态数据类
@dataclass
class StepState:
    step_id: str  # 步骤ID
    status: TaskStatus  # 当前状态
    required_info: List[str]  # 所需信息
    available_info: List[str]  # 可用信息
    missing_info: List[str]  # 缺失信息
    resources_used: Dict[str, Any]  # 已用资源

# 任务执行器主类
class TaskExecutor:
    MAX_RETRIES = 3  # 最大重试次数
    TIMEOUT = 300  # 超时时间（秒）
    CHECKPOINT_INTERVAL = 5  # 检查点间隔（步骤数）

    def __init__(self, llm_model: str = None):
        """初始化任务执行器"""
        self.task_id = str(uuid.uuid4())  # 生成唯一任务ID
        self.start_time = time.time()  # 记录开始时间
        self.checkpoints = []  # 检查点列表
        self.execution_path = []  # 执行路径记录
        self.current_step = None  # 当前步骤
        self.retry_count = 0  # 重试计数器
        self.llm_executor = LLMExecutor(model=llm_model)  # LLM执行器
        self.task_input = None  # 任务输入
        
        # 配置日志
        logging.basicConfig(
            level=logging.INFO,
            format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
        )
        self.logger = logging.getLogger(f"TaskExecutor-{self.task_id}")

    def get_status_update(self) -> dict:
        """生成当前执行状态的状态更新"""
        return {
            "task_id": self.task_id,  # 任务ID
            "timestamp": time.strftime("%Y-%m-%dT%H:%M:%S"),  # 时间戳
            "current_step": self.current_step,  # 当前步骤
            "checkpoints": self.checkpoints,  # 检查点列表
            "resources": {
                "used": {
                    "time": time.time() - self.start_time,  # 已用时间
                    "memory": "N/A"  # 待实现：内存使用
                },
                "available": {
                    "time": self.TIMEOUT - (time.time() - self.start_time),  # 剩余时间
                    "memory": "N/A"  # 待实现：可用内存
                }
            },
            "execution_path": self.execution_path,  # 执行路径
            "status": TaskStatus.COMPLETED.value if self.current_step and self.current_step.get("status") == TaskStatus.COMPLETED.value else TaskStatus.IN_PROGRESS.value  # 当前状态
        }

    async def execute_step(self, step_id: str, step_data: Dict[str, Any]) -> bool:
        """使用LLM执行任务的单个步骤"""
        try:
            # 初始化当前步骤状态
            self.current_step = {
                "id": step_id,  # 步骤ID
                "name": step_data.get("name", "Unknown"),  # 步骤名称
                "status": TaskStatus.IN_PROGRESS.value,  # 状态设为进行中
                "progress": 0  # 进度初始化为0
            }
            
            # 检查是否超时
            if time.time() - self.start_time > self.TIMEOUT:
                raise TimeoutError("任务执行超时")
            
            # 使用LLM执行步骤
            step_result = await self.llm_executor.execute_step(
                step_instruction=step_data.get("instruction", ""),  # 步骤指令
                step_input=step_data.get("input", {}),  # 步骤输入
                context=step_data.get("context", {})  # 上下文信息
            )
            
            # 检查步骤是否成功
            if not step_result["success"]:
                raise Exception(f"步骤失败: {step_result['error']}")
            
            # 更新执行路径
            self.execution_path.append({
                "step_id": step_id,  # 步骤ID
                "result": step_result["output"]  # 步骤结果
            })
            
            # 更新步骤状态
            self.current_step["status"] = TaskStatus.COMPLETED.value  # 状态设为已完成
            self.current_step["progress"] = 100  # 进度设为100%
            
            # 如果需要创建检查点
            if len(self.execution_path) % self.CHECKPOINT_INTERVAL == 0:
                self.create_checkpoint()
                
            return True
            
        except Exception as e:
            # 处理异常
            self.current_step["status"] = TaskStatus.FAILED.value  # 状态设为失败
            return self.handle_error(e)  # 调用错误处理

    def validate_input(self, input_data: Dict[str, Any]) -> bool:
        """验证任务输入数据"""
        return True  # 默认实现，子类可重写

    def create_checkpoint(self):
        """创建当前执行状态的检查点"""
        checkpoint = {
            "timestamp": time.strftime("%Y-%m-%dT%H:%M:%S"),  # 时间戳
            "task_id": self.task_id,  # 任务ID
            "current_step": self.current_step,  # 当前步骤
            "execution_path": self.execution_path.copy(),  # 执行路径副本
            "resources": {
                "used": {
                    "time": time.time() - self.start_time,  # 已用时间
                    "memory": "N/A"  # 待实现：内存使用
                }
            }
        }
        self.checkpoints.append(checkpoint)  # 添加到检查点列表
        self.logger.info(f"创建检查点: {json.dumps(checkpoint, indent=2)}")  # 记录日志

    def rollback_to_checkpoint(self, checkpoint_index: int):
        """回滚到指定检查点"""
        if 0 <= checkpoint_index < len(self.checkpoints):
            checkpoint = self.checkpoints[checkpoint_index]  # 获取检查点
            # 实现状态恢复逻辑
            self.logger.info(f"回滚到检查点: {checkpoint['timestamp']}")  # 记录日志
            return True
        return False  # 检查点索引无效

    def get_next_actions(self) -> List[str]:
        """根据当前状态确定下一步可能的操作"""
        actions = []
        if self.current_step and self.current_step["status"] == TaskStatus.FAILED.value:
            actions.extend(["retry", "rollback", "abort"])  # 失败时可重试、回滚或中止
        elif self.current_step and self.current_step["status"] == TaskStatus.COMPLETED.value:
            actions.extend(["continue", "checkpoint"])  # 完成时可继续或创建检查点
        return actions

    def handle_error(self, error: Exception):
        """处理执行错误"""
        self.logger.error(f"发生错误: {str(error)}")  # 记录错误日志
        self.retry_count += 1  # 增加重试计数
        
        if self.retry_count >= self.MAX_RETRIES:
            self.logger.error("达到最大重试次数。终止执行。")  # 记录终止日志
            return False
            
        # 实现错误恢复逻辑
        return True  # 允许重试

    async def execute(self, task_input: Dict[str, Any]) -> Dict[str, Any]:
        """执行完整任务"""
        try:
            # 存储任务输入
            self.task_input = task_input
            
            # 验证输入
            if not self.validate_input(task_input):
                raise ValueError("无效的任务输入")

            self.logger.info(f"开始任务执行: {self.task_id}")  # 记录开始日志
            
            # 按顺序执行每个步骤
            if hasattr(self, 'task_steps'):
                for step in self.task_steps:
                    if not await self.execute_step(step["id"], step):
                        raise Exception(f"步骤 {step['id']} 失败")
                        
                    # 按间隔创建检查点
                    if len(self.execution_path) % self.CHECKPOINT_INTERVAL == 0:
                        self.create_checkpoint()
            else:
                raise ValueError("未定义任务步骤")
            
            return self.get_status_update()  # 返回最终状态
            
        except Exception as e:
            self.logger.error(f"任务失败: {str(e)}")  # 记录失败日志
            return self.get_status_update()  # 返回失败状态