258 lines
7.0 KiB
Python
258 lines
7.0 KiB
Python
"""Workflow schemas."""
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from pydantic import BaseModel, Field
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from typing import Dict, Any, Optional, List
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from datetime import datetime
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from enum import Enum
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class WorkflowStatus(str, Enum):
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"""工作流状态枚举"""
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DRAFT = "DRAFT"
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PUBLISHED = "PUBLISHED"
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ARCHIVED = "ARCHIVED"
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class NodeType(str, Enum):
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"""节点类型"""
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START = "start"
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END = "end"
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LLM = "llm"
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CONDITION = "condition"
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LOOP = "loop"
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CODE = "code"
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HTTP = "http"
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TOOL = "tool"
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KNOWLEDGE_BASE = "knowledge-base"
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class ExecutionStatus(str, Enum):
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"""执行状态"""
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PENDING = "pending"
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RUNNING = "running"
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COMPLETED = "completed"
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FAILED = "failed"
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CANCELLED = "cancelled"
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# 节点定义相关模式
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class NodePosition(BaseModel):
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"""节点位置"""
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x: float
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y: float
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# 参数定义相关模式
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class ParameterType(str, Enum):
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"""参数类型"""
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STRING = "string"
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NUMBER = "number"
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BOOLEAN = "boolean"
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OBJECT = "object"
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ARRAY = "array"
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class NodeParameter(BaseModel):
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"""节点参数定义"""
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name: str = Field(..., min_length=1, max_length=50)
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type: ParameterType
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description: Optional[str] = None
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required: bool = True
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default_value: Optional[Any] = None
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source: Optional[str] = None # 参数来源：'input'(用户输入), 'node'(其他节点输出), 'variable'(变量引用)
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source_node_id: Optional[str] = None # 来源节点ID（当source为'node'时）
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source_field: Optional[str] = None # 来源字段名
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variable_name: Optional[str] = None # 变量名称（用于结束节点的输出参数）
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class NodeInputOutput(BaseModel):
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"""节点输入输出定义"""
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inputs: List[NodeParameter] = []
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outputs: List[NodeParameter] = []
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class NodeConfig(BaseModel):
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"""节点配置基类"""
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pass
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class LLMNodeConfig(NodeConfig):
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"""LLM节点配置"""
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model_id: Optional[int] = None # 大模型配置ID
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model_name: Optional[str] = None # 模型名称（兼容前端）
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temperature: float = Field(default=0.7, ge=0, le=2)
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max_tokens: Optional[int] = Field(default=None, gt=0)
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prompt: str = Field(..., min_length=1)
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enable_variable_substitution: bool = True # 是否启用变量替换
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class ConditionNodeConfig(NodeConfig):
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"""条件节点配置"""
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condition: str = Field(..., min_length=1)
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class LoopNodeConfig(NodeConfig):
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"""循环节点配置"""
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loop_type: str = Field(..., pattern="^(count|while|foreach)$")
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count: Optional[int] = Field(None, description="循环次数（当loop_type为count时）")
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condition: Optional[str] = Field(None, description="循环条件（当loop_type为while时）")
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iterable: Optional[str] = Field(None, description="可迭代对象（当loop_type为foreach时）")
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class CodeNodeConfig(NodeConfig):
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"""代码执行节点配置"""
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language: str = Field(..., pattern="^(python|javascript)$")
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code: str = Field(..., min_length=1)
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class HttpNodeConfig(NodeConfig):
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"""HTTP请求节点配置"""
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method: str = Field(..., pattern="^(GET|POST|PUT|DELETE|PATCH)$")
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url: str = Field(..., min_length=1)
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headers: Optional[Dict[str, str]] = None
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body: Optional[str] = None
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class ToolNodeConfig(NodeConfig):
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"""工具节点配置"""
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tool_type: str
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parameters: Optional[Dict[str, Any]] = None
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class WorkflowNode(BaseModel):
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"""工作流节点"""
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id: str
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type: NodeType
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name: str
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description: Optional[str] = None
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position: NodePosition
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config: Optional[Dict[str, Any]] = None
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parameters: Optional[NodeInputOutput] = None # 节点输入输出参数定义
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from pydantic import model_validator
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class WorkflowConnection(BaseModel):
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"""工作流连接"""
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id: str
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from_node: str = Field(..., alias="from")
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to_node: str = Field(..., alias="to")
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from_point: str = Field(default="output")
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to_point: str = Field(default="input")
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@model_validator(mode='before')
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@classmethod
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def handle_node_fields(cls, values):
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"""处理from_node/to_node和from/to之间的转换"""
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# 如果存在from但不存在from_node，使用from的值
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if "from" in values and "from_node" not in values:
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values["from_node"] = values["from"]
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# 如果存在from_node但不存在from，使用from_node的值
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elif "from_node" in values and "from" not in values:
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values["from"] = values["from_node"]
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# 如果存在to但不存在to_node，使用to的值
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if "to" in values and "to_node" not in values:
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values["to_node"] = values["to"]
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# 如果存在to_node但不存在to，使用to_node的值
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elif "to_node" in values and "to" not in values:
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values["to"] = values["to_node"]
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return values
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class WorkflowDefinition(BaseModel):
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"""工作流定义"""
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nodes: List[WorkflowNode]
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connections: List[WorkflowConnection]
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# 工作流CRUD模式
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class WorkflowCreate(BaseModel):
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"""创建工作流"""
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name: str = Field(..., min_length=1, max_length=100)
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description: Optional[str] = None
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definition: WorkflowDefinition
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status: WorkflowStatus = WorkflowStatus.DRAFT
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class WorkflowUpdate(BaseModel):
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"""更新工作流"""
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name: Optional[str] = Field(None, min_length=1, max_length=100)
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description: Optional[str] = None
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definition: Optional[WorkflowDefinition] = None
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status: Optional[WorkflowStatus] = None
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is_active: Optional[bool] = None
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class WorkflowResponse(BaseModel):
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"""工作流响应"""
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id: int
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name: str
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description: Optional[str]
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status: WorkflowStatus
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is_active: bool
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version: str
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owner_id: int
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definition: Optional[WorkflowDefinition] = None
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created_at: datetime
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updated_at: datetime
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model_config = {
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'from_attributes': True
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}
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# 工作流执行相关模式
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class WorkflowExecuteRequest(BaseModel):
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"""工作流执行请求"""
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input_data: Optional[Dict[str, Any]] = None
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class NodeExecutionResponse(BaseModel):
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"""节点执行响应"""
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id: int
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node_id: str
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node_type: NodeType
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node_name: str
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status: ExecutionStatus
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input_data: Optional[Dict[str, Any]]
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output_data: Optional[Dict[str, Any]]
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started_at: Optional[str]
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completed_at: Optional[str]
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duration_ms: Optional[int]
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error_message: Optional[str]
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model_config = {
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'from_attributes': True
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}
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class WorkflowExecutionResponse(BaseModel):
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"""工作流执行响应"""
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id: int
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workflow_id: int
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status: ExecutionStatus
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input_data: Optional[Dict[str, Any]]
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output_data: Optional[Dict[str, Any]]
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started_at: Optional[str]
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completed_at: Optional[str]
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error_message: Optional[str]
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executor_id: int
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node_executions: Optional[List[NodeExecutionResponse]] = None
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created_at: datetime
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updated_at: datetime
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model_config = {
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'from_attributes': True
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}
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# 工作流列表响应
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class WorkflowListResponse(BaseModel):
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"""工作流列表响应"""
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workflows: List[WorkflowResponse]
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total: int
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page: int
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size: int |