"""Workflow models."""

from typing import Optional
from sqlalchemy import String, Text, Boolean, Integer, JSON, ForeignKey, Enum
from sqlalchemy.orm import relationship, Mapped, mapped_column
import enum

from ..db.base import BaseModel

class WorkflowStatus(enum.Enum):
    """工作流状态枚举"""
    DRAFT = "DRAFT"          # 草稿
    PUBLISHED = "PUBLISHED"  # 已发布
    ARCHIVED = "ARCHIVED"    # 已归档

class NodeType(enum.Enum):
    """节点类型枚举"""
    START = "start"          # 开始节点
    END = "end"              # 结束节点
    LLM = "llm"              # 大模型节点
    CONDITION = "condition"  # 条件分支节点
    LOOP = "loop"            # 循环节点
    CODE = "code"            # 代码执行节点
    HTTP = "http"            # HTTP请求节点
    TOOL = "tool"            # 工具节点

class ExecutionStatus(enum.Enum):
    """执行状态枚举"""
    PENDING = "pending"      # 等待执行
    RUNNING = "running"      # 执行中
    COMPLETED = "completed"  # 执行完成
    FAILED = "failed"        # 执行失败
    CANCELLED = "cancelled"  # 已取消

class Workflow(BaseModel):
    """工作流模型"""
    __tablename__ = "workflows"
    
    name: Mapped[str] = mapped_column(String(100), nullable=False, comment="工作流名称")
    description: Mapped[Optional[str]] = mapped_column(Text, nullable=True, comment="工作流描述")
    status: Mapped[WorkflowStatus] = mapped_column(Enum(WorkflowStatus), default=WorkflowStatus.DRAFT, nullable=False, comment="工作流状态")
    is_active: Mapped[bool] = mapped_column(Boolean, default=True, nullable=False, comment="是否激活")

    # 工作流定义（JSON格式存储节点和连接信息）
    definition: Mapped[dict] = mapped_column(JSON, nullable=False, comment="工作流定义")
    
    # 版本信息
    version: Mapped[str] = mapped_column(String(20), default="1.0.0", nullable=False, comment="版本号")
    
    # 关联用户
    owner_id: Mapped[int] = mapped_column(Integer, ForeignKey("users.id"), nullable=False, comment="所有者ID")
    
    # 关系
    executions = relationship("WorkflowExecution", back_populates="workflow", cascade="all, delete-orphan")
    
    def __repr__(self):
        return f"<Workflow(id={self.id}, name='{self.name}', status='{self.status.value}')>"
    
    def to_dict(self, include_definition=True):
        """转换为字典"""
        data = super().to_dict()
        data.update({
            'name': self.name,
            'description': self.description,
            'status': self.status.value,
            'is_active': self.is_active,
            'version': self.version,
            'owner_id': self.owner_id
        })
        
        if include_definition:
            data['definition'] = self.definition
            
        return data

class WorkflowExecution(BaseModel):
    """工作流执行记录"""
    
    __tablename__ = "workflow_executions"
    
    workflow_id: Mapped[int] = mapped_column(Integer, ForeignKey("workflows.id"), nullable=False, comment="工作流ID")
    status: Mapped[ExecutionStatus] = mapped_column(Enum(ExecutionStatus), default=ExecutionStatus.PENDING, nullable=False, comment="执行状态")
    
    # 执行输入和输出
    input_data: Mapped[Optional[dict]] = mapped_column(JSON, nullable=True, comment="输入数据")
    output_data: Mapped[Optional[dict]] = mapped_column(JSON, nullable=True, comment="输出数据")
    
    # 执行信息
    started_at: Mapped[Optional[str]] = mapped_column(String(50), nullable=True, comment="开始时间")
    completed_at: Mapped[Optional[str]] = mapped_column(String(50), nullable=True, comment="完成时间")
    error_message: Mapped[Optional[str]] = mapped_column(Text, nullable=True, comment="错误信息")
    
    # 执行者
    executor_id: Mapped[int] = mapped_column(Integer, ForeignKey("users.id"), nullable=False, comment="执行者ID")
    
    # 关系
    workflow = relationship("Workflow", back_populates="executions")
    node_executions = relationship("NodeExecution", back_populates="workflow_execution", cascade="all, delete-orphan")
    
    def __repr__(self):
        return f"<WorkflowExecution(id={self.id}, workflow_id={self.workflow_id}, status='{self.status.value}')>"
    
    def to_dict(self, include_nodes=False):
        """转换为字典"""
        data = super().to_dict()
        data.update({
            'workflow_id': self.workflow_id,
            'status': self.status.value,
            'input_data': self.input_data,
            'output_data': self.output_data,
            'started_at': self.started_at,
            'completed_at': self.completed_at,
            'error_message': self.error_message,
            'executor_id': self.executor_id
        })
        
        if include_nodes:
            data['node_executions'] = [node.to_dict() for node in self.node_executions]
            
        return data

class NodeExecution(BaseModel):
    """节点执行记录"""
    __tablename__ = "node_executions"
    
    workflow_execution_id: Mapped[int] = mapped_column(Integer, ForeignKey("workflow_executions.id"), nullable=False, comment="工作流执行ID")
    node_id: Mapped[str] = mapped_column(String(50), nullable=False, comment="节点ID")
    node_type: Mapped[NodeType] = mapped_column(Enum(NodeType), nullable=False, comment="节点类型")
    node_name: Mapped[str] = mapped_column(String(100), nullable=False, comment="节点名称")
    
    # 执行状态和结果
    status: Mapped[ExecutionStatus] = mapped_column(Enum(ExecutionStatus), default=ExecutionStatus.PENDING, nullable=False, comment="执行状态")
    input_data: Mapped[Optional[dict]] = mapped_column(JSON, nullable=True, comment="输入数据")
    output_data: Mapped[Optional[dict]] = mapped_column(JSON, nullable=True, comment="输出数据")
    
    # 执行时间
    started_at: Mapped[Optional[str]] = mapped_column(String(50), nullable=True, comment="开始时间")
    completed_at: Mapped[Optional[str]] = mapped_column(String(50), nullable=True, comment="完成时间")
    duration_ms: Mapped[Optional[int]] = mapped_column(Integer, nullable=True, comment="执行时长(毫秒)")
    
    # 错误信息
    error_message: Mapped[Optional[str]] = mapped_column(Text, nullable=True, comment="错误信息")
    
    # 关系
    workflow_execution = relationship("WorkflowExecution", back_populates="node_executions")
    
    def __repr__(self):
        return f"<NodeExecution(id={self.id}, node_id='{self.node_id}', status='{self.status.value}')>"
    
    def to_dict(self):
        """转换为字典"""
        data = super().to_dict()
        data.update({
            'workflow_execution_id': self.workflow_execution_id,
            'node_id': self.node_id,
            'node_type': self.node_type.value,
            'node_name': self.node_name,
            'status': self.status.value,
            'input_data': self.input_data,
            'output_data': self.output_data,
            'started_at': self.started_at,
            'completed_at': self.completed_at,
            'duration_ms': self.duration_ms,
            'error_message': self.error_message
        })
        
        return data