87 lines
2.5 KiB
Python
87 lines
2.5 KiB
Python
"""笔记相关的请求/响应 schema。"""
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from datetime import datetime
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from pydantic import BaseModel, ConfigDict, Field
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from app.models.question import QuestionType
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class OptionIn(BaseModel):
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key: str = Field(max_length=8) # A/B/C/D 等
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text_markdown: str
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class QuestionBase(BaseModel):
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# 默认未分类：拍照记下来就能存，不强制先想清楚题型
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type: QuestionType = QuestionType.unclassified
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stem_markdown: str
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options: list[OptionIn] | None = None
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correct_answer: list[str] | None = None
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explanation_markdown: str | None = None
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my_note_markdown: str | None = None
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needs_review: bool = False
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difficulty: int | None = Field(default=None, ge=1, le=5)
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class QuestionCreate(QuestionBase):
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tags: list[str] = Field(default_factory=list)
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class QuestionUpdate(BaseModel):
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"""全部可选，只更新提供的字段。"""
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type: QuestionType | None = None
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stem_markdown: str | None = None
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options: list[OptionIn] | None = None
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correct_answer: list[str] | None = None
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explanation_markdown: str | None = None
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my_note_markdown: str | None = None
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needs_review: bool | None = None
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difficulty: int | None = Field(default=None, ge=1, le=5)
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tags: list[str] | None = None
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class QuestionOut(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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id: str
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type: QuestionType
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stem_markdown: str
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options: list[dict] | None
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correct_answer: list[str] | None
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explanation_markdown: str | None
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my_note_markdown: str | None
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needs_review: bool
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difficulty: int | None
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source_image_id: str | None
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ocr_engine: str | None
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tags: list[str] = Field(default_factory=list)
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created_at: datetime | None = None
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updated_at: datetime | None = None
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@classmethod
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def from_model(cls, q) -> "QuestionOut":
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return cls(
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id=q.id,
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type=q.type,
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stem_markdown=q.stem_markdown,
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options=q.options,
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correct_answer=q.correct_answer,
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explanation_markdown=q.explanation_markdown,
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my_note_markdown=q.my_note_markdown,
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needs_review=q.needs_review,
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difficulty=q.difficulty,
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source_image_id=q.source_image_id,
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ocr_engine=q.ocr_engine,
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tags=[t.name for t in q.tags],
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created_at=q.created_at,
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updated_at=q.updated_at,
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)
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class QuestionList(BaseModel):
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items: list[QuestionOut]
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total: int
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page: int
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page_size: int
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