beige/backend/app/models/product.py

"""
app/models/product.py — products / benchmark_notes / banned_words
Alembic 003 业务主体（1/3）
products.category 是纯数据字段，禁止任何品类枚举（基石A）。
"""

from datetime import datetime
from typing import Optional

from sqlalchemy import (
    BigInteger, DateTime, Enum, ForeignKey,
    Index, Integer, String, Text, func,
)
from sqlalchemy.orm import Mapped, mapped_column, relationship

from app.constants.enums import BannedWordLevel, ProductImageScene, ProductSource
from app.core.database import Base


class Product(Base):
    """产品档案（卖点/违禁词/风格/调性/文案角度/可调prompt/source）"""
    __tablename__ = "products"

    id: Mapped[int] = mapped_column(BigInteger, primary_key=True, autoincrement=True)
    workspace_id: Mapped[int] = mapped_column(
        BigInteger, ForeignKey("workspaces.id", ondelete="CASCADE"), nullable=False
    )
    name: Mapped[str] = mapped_column(String(128), nullable=False)
    # category 是纯数据字段，不在代码里做枚举（基石A）
    category: Mapped[str | None] = mapped_column(String(64))
    source: Mapped[str] = mapped_column(
        Enum(ProductSource, values_callable=lambda x: [e.value for e in x]),
        default=ProductSource.CUSTOM, nullable=False,
    )
    selling_points: Mapped[str | None] = mapped_column(Text)   # JSON数组
    style_tone: Mapped[str | None] = mapped_column(String(128))
    text_angles: Mapped[str | None] = mapped_column(Text)      # JSON数组，用户设定
    custom_prompt: Mapped[str | None] = mapped_column(Text)    # 等北哥方案注入
    image_path: Mapped[str | None] = mapped_column(String(512))  # 产品参考图路径（前端上传后写入）
    # 008: 品牌词（客户输入，植入文案每条+生图特写图第2/6张，第5环）
    brand_keyword: Mapped[str | None] = mapped_column(String(64), comment="品牌词，客户录入，随产品固定")
    # 012: 目标人群（客户输入，透传进文案/生图 prompt，storyboard.py:52 原恒空现可填）
    target_audience: Mapped[str | None] = mapped_column(String(128), comment="目标人群，客户输入，透传进文案/生图prompt")
    is_active: Mapped[bool] = mapped_column(default=True, nullable=False)
    created_at: Mapped[datetime] = mapped_column(
        DateTime, server_default=func.now(), nullable=False
    )
    updated_at: Mapped[datetime] = mapped_column(
        DateTime, server_default=func.now(), onupdate=func.now(), nullable=False
    )

    benchmark_notes: Mapped[list["BenchmarkNote"]] = relationship(
        back_populates="product", lazy="noload"
    )
    images: Mapped[list["ProductImage"]] = relationship(
        back_populates="product", lazy="selectin",
        cascade="all, delete-orphan", order_by="ProductImage.sort_order",
    )

    __table_args__ = (
        Index("idx_products_workspace_id", "workspace_id"),
    )


class ProductImage(Base):
    """产品参考图（R5多图）：一产品多张，每张标 scene 场景类型，生图按分镜role选用。

    product.image_path 仍保留当主图（向后兼容，零破坏）；本表是其超集。
    """
    __tablename__ = "product_images"

    id: Mapped[int] = mapped_column(BigInteger, primary_key=True, autoincrement=True)
    product_id: Mapped[int] = mapped_column(
        BigInteger, ForeignKey("products.id", ondelete="CASCADE"), nullable=False
    )
    path: Mapped[str] = mapped_column(String(512), nullable=False)  # 绝对路径，worker 直接 open
    scene: Mapped[str] = mapped_column(
        Enum(ProductImageScene, values_callable=lambda x: [e.value for e in x]),
        default=ProductImageScene.PRIMARY, nullable=False,
    )
    is_primary: Mapped[bool] = mapped_column(default=False, nullable=False)  # 主图(同步 product.image_path)
    sort_order: Mapped[int] = mapped_column(Integer, default=0, nullable=False)
    created_at: Mapped[datetime] = mapped_column(
        DateTime, server_default=func.now(), nullable=False
    )

    product: Mapped["Product"] = relationship(back_populates="images")

    __table_args__ = (
        Index("idx_product_images_product_id", "product_id"),
    )


class BenchmarkNote(Base):
    """标杆笔记（截图+手填亮点为主通道）"""
    __tablename__ = "benchmark_notes"

    id: Mapped[int] = mapped_column(BigInteger, primary_key=True, autoincrement=True)
    workspace_id: Mapped[int] = mapped_column(
        BigInteger, ForeignKey("workspaces.id", ondelete="CASCADE"), nullable=False
    )
    product_id: Mapped[int] = mapped_column(
        BigInteger, ForeignKey("products.id", ondelete="CASCADE"), nullable=False
    )
    screenshot_url: Mapped[str | None] = mapped_column(String(512))
    highlights: Mapped[str | None] = mapped_column(Text)    # 手填亮点
    link_url: Mapped[str | None] = mapped_column(String(512))
    # 009: 第2环标杆分析字段
    features_json: Mapped[str | None] = mapped_column(Text, comment="爆款8特征分析结果（JSON），AI解析后写入")
    analyze_status: Mapped[str] = mapped_column(String(20), default="pending", nullable=False, comment="AI分析状态: pending/analyzing/done/failed")
    created_at: Mapped[datetime] = mapped_column(
        DateTime, server_default=func.now(), nullable=False
    )

    product: Mapped["Product"] = relationship(back_populates="benchmark_notes")

    __table_args__ = (
        Index("idx_benchmark_notes_product_id", "product_id"),
    )


class BannedWord(Base):
    """违禁词库（三级：auto_fix/soft_warn/hard_block）"""
    __tablename__ = "banned_words"

    id: Mapped[int] = mapped_column(BigInteger, primary_key=True, autoincrement=True)
    workspace_id: Mapped[int] = mapped_column(
        BigInteger, ForeignKey("workspaces.id", ondelete="CASCADE"), nullable=False
    )
    word: Mapped[str] = mapped_column(String(64), nullable=False)
    level: Mapped[str] = mapped_column(
        Enum(BannedWordLevel, values_callable=lambda x: [e.value for e in x]),
        nullable=False,
    )
    replacement: Mapped[str | None] = mapped_column(String(128))
    updatable: Mapped[bool] = mapped_column(default=True, nullable=False)
    created_at: Mapped[datetime] = mapped_column(
        DateTime, server_default=func.now(), nullable=False
    )

    __table_args__ = (
        Index("idx_banned_words_workspace_id", "workspace_id"),
    )