143 lines
4.3 KiB
Python
143 lines
4.3 KiB
Python
"""Document 文档模型。"""
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from sqlalchemy import ForeignKey, Integer, String, Text
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from sqlalchemy.orm import Mapped, mapped_column, relationship
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from app.models.base import Base, TimestampMixin, UUIDPrimaryKeyMixin
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class Document(UUIDPrimaryKeyMixin, TimestampMixin, Base):
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"""文档模型。
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技术审查 §2.2：documents 表。
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"""
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__tablename__ = "documents"
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knowledge_base_id: Mapped[str] = mapped_column(
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String(32),
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ForeignKey("knowledge_bases.id"),
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nullable=False,
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index=True,
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comment="所属知识库 ID",
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)
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user_id: Mapped[str] = mapped_column(
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String(32),
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ForeignKey("users.id"),
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nullable=False,
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index=True,
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comment="所有者用户 ID (冗余，便于隔离校验)",
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)
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category_id: Mapped[str | None] = mapped_column(
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String(32),
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ForeignKey("document_categories.id"),
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nullable=True,
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comment="分类 ID",
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)
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original_filename: Mapped[str] = mapped_column(
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String(512),
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nullable=False,
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comment="原始文件名或文本标题 (仅展示)",
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)
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storage_path: Mapped[str | None] = mapped_column(
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String(1024),
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nullable=True,
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comment="相对于 data/ 的物理存储路径（文本内容文档为 NULL）",
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)
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content: Mapped[str | None] = mapped_column(
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Text,
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nullable=True,
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comment="直接输入的文本内容（非文件上传时使用）",
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)
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content_format: Mapped[str] = mapped_column(
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String(16),
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default="markdown",
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nullable=False,
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comment="内容格式：markdown / text",
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)
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markdown_path: Mapped[str | None] = mapped_column(
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String(1024),
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nullable=True,
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comment="相对于 data/ 的 Markdown 文件路径",
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)
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file_size: Mapped[int] = mapped_column(
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Integer,
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default=0,
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nullable=False,
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comment="文件大小 (字节)，文本内容文档为内容长度",
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)
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mime_type: Mapped[str] = mapped_column(
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String(127),
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default="text/markdown",
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nullable=False,
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comment="MIME 类型",
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)
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file_ext: Mapped[str] = mapped_column(
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String(16),
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default=".md",
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nullable=False,
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comment="文件扩展名 (.docx/.pdf/.md)",
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)
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sha256: Mapped[str | None] = mapped_column(
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String(64),
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nullable=True,
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comment="文件 SHA-256 哈希（文本内容文档为 NULL）",
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)
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doc_token_hash: Mapped[str] = mapped_column(
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String(64),
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unique=True,
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nullable=True,
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index=True,
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comment="SHA-256(document_token) 十六进制",
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)
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doc_token_encrypted: Mapped[str | None] = mapped_column(
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Text,
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nullable=True,
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comment="Fernet 加密的 document_token 原文",
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)
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doc_token_hint: Mapped[str | None] = mapped_column(
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String(16),
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nullable=True,
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comment="document_token 末 8 位明文",
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)
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title: Mapped[str | None] = mapped_column(
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String(512),
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nullable=True,
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comment="文档标题 (用户可改)",
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)
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description: Mapped[str | None] = mapped_column(
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Text,
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nullable=True,
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comment="文档描述 (用户可改)",
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)
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keywords: Mapped[str | None] = mapped_column(
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Text,
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nullable=True,
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comment="关键词 (逗号分隔)",
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)
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content_summary: Mapped[str | None] = mapped_column(
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Text,
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nullable=True,
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comment="抽取式摘要 (~200字)",
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)
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status: Mapped[str] = mapped_column(
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String(16),
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default="PENDING",
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nullable=False,
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comment="状态 (PENDING/PROCESSING/READY/FAILED/DELETED)",
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)
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error_code: Mapped[str | None] = mapped_column(
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String(64),
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nullable=True,
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comment="错误码 (如 SCANNED_PDF_NO_TEXT_LAYER)",
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)
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# 关系
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knowledge_base = relationship("KnowledgeBase", back_populates="documents", lazy="selectin")
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user = relationship("User", back_populates="documents", lazy="selectin")
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category = relationship("DocumentCategory", back_populates="documents", lazy="selectin")
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access_logs = relationship("AccessLog", back_populates="document", lazy="selectin")
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def __repr__(self) -> str:
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return f"<Document {self.original_filename!r} (status={self.status!r})>"
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