426 lines
15 KiB
Python
426 lines
15 KiB
Python
import datetime
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import uuid
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from typing import Optional, Any, List, Dict
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from pydantic import BaseModel, Field, ConfigDict, field_serializer, field_validator
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# ---------- Input Schemas ----------
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class KnowledgeBaseConfig(BaseModel):
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"""单个知识库配置"""
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kb_id: str = Field(..., description="知识库ID")
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top_k: int = Field(default=3, ge=1, le=20, description="检索返回的文档数量")
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similarity_threshold: float = Field(default=0.7, ge=0.0, le=1.0, description="相似度阈值")
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strategy: str = Field(default="hybrid", description="检索策略: hybrid | bm25 | dense")
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weight: float = Field(default=1.0, ge=0.0, le=1.0, description="知识库权重（用于多知识库融合）")
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vector_similarity_weight: float = Field(default=0.5, ge=0.0, le=1.0, description="向量相似度权重")
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retrieve_type: str = Field(default="hybrid", description="检索方式participle｜ semantic｜hybrid")
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class KnowledgeRetrievalConfig(BaseModel):
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"""知识库检索配置（支持多个知识库，每个有独立配置）"""
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knowledge_bases: List[KnowledgeBaseConfig] = Field(
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default_factory=list,
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description="关联的知识库列表，每个知识库有独立配置"
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)
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# 多知识库融合策略
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merge_strategy: str = Field(
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default="weighted",
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description="多知识库结果融合策略: weighted | rrf | concat"
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)
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reranker_id: Optional[str] = Field(default=None, description="多知识库结果融合的模型ID")
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reranker_top_k: int = Field(default=10, ge=0, le=1024, description="多知识库结果融合的模型参数")
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class ToolConfig(BaseModel):
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"""工具配置"""
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enabled: bool = Field(default=False, description="是否启用该工具")
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config: Optional[Dict[str, Any]] = Field(default_factory=dict, description="工具特定配置")
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class MemoryConfig(BaseModel):
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"""记忆配置"""
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enabled: bool = Field(default=True, description="是否启用对话历史记忆")
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memory_content: Optional[str] = Field(default=None, description="选择记忆的内容类型")
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max_history: int = Field(default=10, ge=0, le=100, description="最大保留的历史对话轮数")
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class ModelParameters(BaseModel):
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"""模型参数配置"""
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temperature: float = Field(default=0.7, ge=0.0, le=2.0, description="温度参数，控制输出的随机性")
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max_tokens: int = Field(default=2000, ge=1, le=32000, description="最大生成token数")
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top_p: float = Field(default=1.0, ge=0.0, le=1.0, description="核采样参数")
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frequency_penalty: float = Field(default=0.0, ge=-2.0, le=2.0, description="频率惩罚")
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presence_penalty: float = Field(default=0.0, ge=-2.0, le=2.0, description="存在惩罚")
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n: int = Field(default=1, ge=1, le=10, description="生成的回复数量")
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stop: Optional[List[str]] = Field(default=None, description="停止序列")
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class VariableDefinition(BaseModel):
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"""变量定义"""
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name: str = Field(..., description="变量名称（标识符）")
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display_name: Optional[str] = Field(None, description="显示名称（用户看到的名称）")
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type: str = Field(
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default="string",
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description="变量类型: string(单行文本) | text(多行文本) | number(数字)"
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)
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required: bool = Field(default=False, description="是否必填")
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description: Optional[str] = Field(default=None, description="变量描述")
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max_length: Optional[int] = Field(default=None, description="最大长度（用于文本类型）")
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class AgentConfigCreate(BaseModel):
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"""Agent 行为配置"""
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# 提示词配置
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system_prompt: Optional[str] = Field(default=None, description="系统提示词，定义 Agent 的角色和行为准则")
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# 模型配置
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default_model_config_id: Optional[uuid.UUID] = Field(default=None, description="默认使用的模型配置ID")
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model_parameters: ModelParameters = Field(
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default_factory=ModelParameters,
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description="模型参数配置（temperature、max_tokens 等）"
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)
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# 知识库关联
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knowledge_retrieval: Optional[KnowledgeRetrievalConfig] = Field(
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default=None,
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description="知识库检索配置"
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)
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# 记忆配置
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memory: MemoryConfig = Field(
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default_factory=lambda: MemoryConfig(enabled=True),
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description="对话历史记忆配置"
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)
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# 变量配置
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variables: List[VariableDefinition] = Field(
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default_factory=list,
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description="Agent 可用的变量列表"
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)
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# 工具配置
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tools: Dict[str, ToolConfig] = Field(
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default_factory=dict,
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description="工具配置，key 为工具名称（web_search, code_interpreter, image_generation 等）"
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)
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class AppCreate(BaseModel):
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name: str
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description: Optional[str] = None
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icon: Optional[str] = None
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icon_type: Optional[str] = None
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type: str = Field(pattern=r"^(agent|workflow|multi_agent)$")
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visibility: Optional[str] = None
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status: Optional[str] = None
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tags: Optional[List[str]] = Field(default_factory=list)
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# only for type=agent
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agent_config: Optional[AgentConfigCreate] = None
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# only for type=multi_agent
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multi_agent_config: Optional[Dict[str, Any]] = None
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class AppUpdate(BaseModel):
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name: Optional[str] = None
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description: Optional[str] = None
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icon: Optional[str] = None
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icon_type: Optional[str] = None
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visibility: Optional[str] = None
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status: Optional[str] = None
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tags: Optional[List[str]] = None
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class AgentConfigUpdate(BaseModel):
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"""更新 Agent 行为配置"""
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# 提示词配置
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system_prompt: Optional[str] = Field(default=None, description="系统提示词")
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# 模型配置
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default_model_config_id: Optional[uuid.UUID] = Field(default=None, description="默认模型配置ID")
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model_parameters: Optional[ModelParameters] = Field(default=None, description="模型参数配置")
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# 知识库关联
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knowledge_retrieval: Optional[KnowledgeRetrievalConfig] = Field(
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default=None,
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description="知识库检索配置"
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)
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# 记忆配置
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memory: Optional[MemoryConfig] = Field(default=None, description="对话历史记忆配置")
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# 变量配置
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variables: Optional[List[VariableDefinition]] = Field(default=None, description="变量列表")
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# 工具配置
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tools: Optional[Dict[str, ToolConfig]] = Field(default=None, description="工具配置")
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# ---------- Output Schemas ----------
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class App(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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id: uuid.UUID
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workspace_id: uuid.UUID
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created_by: uuid.UUID
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name: str
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description: Optional[str] = None
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icon: Optional[str] = None
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icon_type: Optional[str] = None
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type: str
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visibility: str
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status: str
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tags: List[str] = []
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current_release_id: Optional[uuid.UUID] = None
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is_active: bool
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is_shared: bool = False # 是否是共享应用（从其他工作空间共享来的）
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created_at: datetime.datetime
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updated_at: datetime.datetime
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@field_serializer("created_at", when_used="json")
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def _serialize_created_at(self, dt: datetime.datetime):
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return int(dt.timestamp() * 1000) if dt else None
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@field_serializer("updated_at", when_used="json")
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def _serialize_updated_at(self, dt: datetime.datetime):
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return int(dt.timestamp() * 1000) if dt else None
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class AgentConfig(BaseModel):
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"""Agent 配置输出 Schema"""
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model_config = ConfigDict(from_attributes=True)
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id: uuid.UUID
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app_id: uuid.UUID
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# 提示词
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system_prompt: Optional[str] = None
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# 模型配置
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default_model_config_id: Optional[uuid.UUID] = None
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model_parameters: ModelParameters = Field(default_factory=ModelParameters)
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# 知识库检索
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knowledge_retrieval: Optional[KnowledgeRetrievalConfig] = None
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# 记忆配置
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memory: MemoryConfig = Field(default_factory=lambda: MemoryConfig(enabled=True))
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# 变量配置
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variables: List[VariableDefinition] = []
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# 工具配置
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tools: Dict[str, ToolConfig] = {}
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is_active: bool
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created_at: datetime.datetime
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updated_at: datetime.datetime
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@field_validator("model_parameters", mode="before")
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@classmethod
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def validate_model_parameters(cls, v):
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"""处理 None 值，返回默认的 ModelParameters"""
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if v is None:
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return ModelParameters()
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return v
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@field_validator("memory", mode="before")
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@classmethod
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def validate_memory(cls, v):
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"""处理 None 值，返回默认的 MemoryConfig"""
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if v is None:
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return MemoryConfig(enabled=True)
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return v
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@field_validator("variables", mode="before")
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@classmethod
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def validate_variables(cls, v):
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"""处理 None 值，返回空列表"""
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if v is None:
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return []
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return v
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@field_validator("tools", mode="before")
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@classmethod
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def validate_tools(cls, v):
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"""处理 None 值，返回空字典"""
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if v is None:
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return {}
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return v
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@field_serializer("created_at", when_used="json")
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def _serialize_created_at(self, dt: datetime.datetime):
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return int(dt.timestamp() * 1000) if dt else None
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@field_serializer("updated_at", when_used="json")
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def _serialize_updated_at(self, dt: datetime.datetime):
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return int(dt.timestamp() * 1000) if dt else None
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class PublishRequest(BaseModel):
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"""发布应用请求"""
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version_name: str
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release_notes: Optional[str] = Field(None, description="版本说明")
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class AppRelease(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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id: uuid.UUID
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app_id: uuid.UUID
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version: int
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release_notes: Optional[str] = None
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version_name: str
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description: Optional[str] = None
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icon: Optional[str] = None
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icon_type: Optional[str] = None
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name: str
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type: str
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visibility: str
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config: Dict[str, Any] = {}
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default_model_config_id: Optional[uuid.UUID] = None
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published_by: uuid.UUID
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publisher_name: str
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published_at: datetime.datetime
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is_active: bool
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created_at: datetime.datetime
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updated_at: datetime.datetime
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@field_serializer("created_at", when_used="json")
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def _serialize_created_at(self, dt: datetime.datetime):
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return int(dt.timestamp() * 1000) if dt else None
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@field_serializer("updated_at", when_used="json")
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def _serialize_updated_at(self, dt: datetime.datetime):
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return int(dt.timestamp() * 1000) if dt else None
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@field_serializer("published_at", when_used="json")
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def _serialize_published_at(self, dt: datetime.datetime):
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return int(dt.timestamp() * 1000) if dt else None
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# ---------- App Share Schemas ----------
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class AppShareCreate(BaseModel):
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"""应用分享请求"""
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target_workspace_ids: List[uuid.UUID] = Field(..., description="目标工作空间ID列表")
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class AppShare(BaseModel):
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"""应用分享输出"""
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model_config = ConfigDict(from_attributes=True)
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id: uuid.UUID
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source_app_id: uuid.UUID
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source_workspace_id: uuid.UUID
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target_workspace_id: uuid.UUID
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shared_by: uuid.UUID
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created_at: datetime.datetime
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updated_at: datetime.datetime
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@field_serializer("created_at", when_used="json")
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def _serialize_created_at(self, dt: datetime.datetime):
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return int(dt.timestamp() * 1000) if dt else None
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@field_serializer("updated_at", when_used="json")
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def _serialize_updated_at(self, dt: datetime.datetime):
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return int(dt.timestamp() * 1000) if dt else None
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# ---------- Draft Run Schemas ----------
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class DraftRunRequest(BaseModel):
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"""试运行请求"""
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message: str = Field(..., description="用户消息")
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conversation_id: Optional[str] = Field(default=None, description="会话ID（用于多轮对话）")
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user_id: Optional[str] = Field(default=None, description="用户ID（用于会话管理）")
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variables: Optional[Dict[str, Any]] = Field(default=None, description="自定义变量参数值")
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stream: bool = Field(default=False, description="是否流式返回")
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class DraftRunResponse(BaseModel):
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"""试运行响应（非流式）"""
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message: str = Field(..., description="AI 回复消息")
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conversation_id: Optional[str] = Field(default=None, description="会话ID（用于多轮对话）")
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usage: Optional[Dict[str, Any]] = Field(default=None, description="Token 使用情况")
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elapsed_time: Optional[float] = Field(default=None, description="耗时（秒）")
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class DraftRunStreamChunk(BaseModel):
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"""试运行流式响应块"""
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event: str = Field(..., description="事件类型: start | message | end | error")
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data: Dict[str, Any] = Field(..., description="事件数据")
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# ---------- Draft Run Compare Schemas ----------
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class ModelCompareItem(BaseModel):
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"""单个对比模型配置"""
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model_config_id: uuid.UUID = Field(..., description="模型配置ID")
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model_parameters: Optional[Dict[str, Any]] = Field(
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None,
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description="覆盖模型参数，如 temperature, max_tokens 等"
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)
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label: Optional[str] = Field(
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None,
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description="自定义显示标签，用于区分同一模型的不同配置"
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)
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conversation_id: Optional[str] = Field(
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None,
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description="会话ID，用于为每个模型指定独立的会话历史"
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)
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class DraftRunCompareRequest(BaseModel):
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"""多模型对比试运行请求"""
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message: str = Field(..., description="用户消息")
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conversation_id: Optional[str] = Field(None, description="会话ID")
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user_id: Optional[str] = Field(None, description="用户ID")
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variables: Optional[Dict[str, Any]] = Field(None, description="变量参数")
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models: List[ModelCompareItem] = Field(
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...,
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min_length=1,
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max_length=5,
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description="要对比的模型列表（1-5个）"
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)
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parallel: bool = Field(True, description="是否并行执行")
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stream: bool = Field(False, description="是否流式返回")
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timeout: Optional[int] = Field(60, ge=10, le=300, description="超时时间（秒）")
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class ModelRunResult(BaseModel):
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"""单个模型运行结果"""
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model_config_id: uuid.UUID
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model_name: str
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label: Optional[str] = None
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parameters_used: Dict[str, Any] = Field(..., description="实际使用的参数")
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message: Optional[str] = None
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usage: Optional[Dict[str, Any]] = None
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elapsed_time: float
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error: Optional[str] = None
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tokens_per_second: Optional[float] = None
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cost_estimate: Optional[float] = None
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conversation_id: Optional[str] = None
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class DraftRunCompareResponse(BaseModel):
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"""多模型对比响应"""
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results: List[ModelRunResult]
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total_elapsed_time: float
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successful_count: int
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failed_count: int
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fastest_model: Optional[str] = None
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cheapest_model: Optional[str] = None
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