102 lines
3.6 KiB
Python
102 lines
3.6 KiB
Python
"""题目、标签、题目-标签关联。"""
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import enum
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from sqlalchemy import (
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Boolean,
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ForeignKey,
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Integer,
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String,
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Text,
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UniqueConstraint,
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)
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from sqlalchemy import Enum as SAEnum
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from sqlalchemy.orm import Mapped, mapped_column, relationship
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from sqlalchemy.types import JSON
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from app.models.base import new_uuid
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from app.db import Base, TimestampMixin
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class QuestionType(str, enum.Enum):
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# 拍照入库的默认值：先收进来，想练习时再补题型/答案
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unclassified = "unclassified"
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single_choice = "single_choice"
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multiple_choice = "multiple_choice"
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true_false = "true_false"
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fill_blank = "fill_blank"
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short_answer = "short_answer"
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# 客观题：有标准答案时可本地精确判分；其余交给 AI 判
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OBJECTIVE_TYPES = {
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QuestionType.single_choice,
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QuestionType.multiple_choice,
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QuestionType.true_false,
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}
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class Tag(Base, TimestampMixin):
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__tablename__ = "tags"
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__table_args__ = (UniqueConstraint("user_id", "name", name="uq_tag_user_name"),)
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id: Mapped[str] = mapped_column(String(36), primary_key=True, default=new_uuid)
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user_id: Mapped[str] = mapped_column(
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ForeignKey("users.id", ondelete="CASCADE"), index=True
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)
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name: Mapped[str] = mapped_column(String(128))
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questions: Mapped[list["Question"]] = relationship(
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secondary="question_tags", back_populates="tags"
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)
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class QuestionTag(Base):
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__tablename__ = "question_tags"
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question_id: Mapped[str] = mapped_column(
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ForeignKey("questions.id", ondelete="CASCADE"), primary_key=True
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)
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tag_id: Mapped[str] = mapped_column(
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ForeignKey("tags.id", ondelete="CASCADE"), primary_key=True
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)
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class Question(Base, TimestampMixin):
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"""一条笔记。
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只有 type 和 stem_markdown 是必填，其中 type 可以是 unclassified，
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所以"拍照识别完直接存"不需要用户补任何东西。
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"""
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__tablename__ = "questions"
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id: Mapped[str] = mapped_column(String(36), primary_key=True, default=new_uuid)
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user_id: Mapped[str] = mapped_column(
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ForeignKey("users.id", ondelete="CASCADE"), index=True
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)
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type: Mapped[QuestionType] = mapped_column(
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SAEnum(QuestionType), default=QuestionType.unclassified
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)
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stem_markdown: Mapped[str] = mapped_column(Text)
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# 选项：[{"key": "A", "text_markdown": "..."}]，选择/判断题用
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options: Mapped[list | None] = mapped_column(JSON, nullable=True)
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# 标准答案：选择题 ["A","C"]，填空/简答 ["文本"]
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correct_answer: Mapped[list | None] = mapped_column(JSON, nullable=True)
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# AI 生成的讲解（每次 /ai/explain 会覆写，别往这里写用户内容）
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explanation_markdown: Mapped[str | None] = mapped_column(Text, nullable=True)
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# 用户自己写的笔记 / 错因反思，AI 永不触碰
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my_note_markdown: Mapped[str | None] = mapped_column(Text, nullable=True)
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# 手动标记"待复习"；复习清单 = 这个标记 ∪ 最近一次作答判错
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needs_review: Mapped[bool] = mapped_column(Boolean, default=False, index=True)
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difficulty: Mapped[int | None] = mapped_column(Integer, nullable=True) # 1-5
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source_image_id: Mapped[str | None] = mapped_column(
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ForeignKey("images.id", ondelete="SET NULL"), nullable=True, index=True
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)
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ocr_engine: Mapped[str | None] = mapped_column(String(32), nullable=True)
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tags: Mapped[list["Tag"]] = relationship(
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secondary="question_tags", back_populates="questions"
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)
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# 便于详情页把原图和笔记一起展示
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source_image: Mapped["Image | None"] = relationship("Image")
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