57 lines
1.8 KiB
Python
57 lines
1.8 KiB
Python
from typing import Any, List, Optional
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from pydantic import BaseModel, Field
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class PromptBase(BaseModel):
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"""Prompt 基础模型。"""
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name: str = Field(..., description="唯一标识，用于代码引用")
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title: Optional[str] = Field(default=None, description="可读标题")
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content: str = Field(..., description="提示词具体内容")
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tags: Optional[List[str]] = Field(default=None, description="标签集合")
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class PromptCreate(PromptBase):
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"""创建 Prompt 时使用的模型。"""
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pass
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class PromptUpdate(BaseModel):
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"""更新 Prompt 时使用的模型。"""
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title: Optional[str] = Field(default=None)
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content: Optional[str] = Field(default=None)
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tags: Optional[List[str]] = Field(default=None)
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class PromptRead(PromptBase):
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"""对外暴露的 Prompt 数据结构。"""
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id: int
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class Config:
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from_attributes = True
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@classmethod
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def model_validate(cls, obj: Any, *args: Any, **kwargs: Any) -> "PromptRead": # type: ignore[override]
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"""在转换 ORM 模型时，将字符串标签拆分为列表。"""
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if hasattr(obj, "id") and hasattr(obj, "name"):
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raw_tags = getattr(obj, "tags", None)
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if isinstance(raw_tags, str):
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processed = [tag for tag in raw_tags.split(",") if tag]
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elif isinstance(raw_tags, list):
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processed = raw_tags
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else:
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processed = None
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data = {
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"id": getattr(obj, "id"),
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"name": getattr(obj, "name"),
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"title": getattr(obj, "title", None),
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"content": getattr(obj, "content", None),
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"tags": processed,
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}
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return super().model_validate(data, *args, **kwargs)
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return super().model_validate(obj, *args, **kwargs)
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