47 lines
1.7 KiB
Python
47 lines
1.7 KiB
Python
"""
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Implicit Emotions Storage Model
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数据库模型：存储用户的隐性记忆画像和情绪建议数据
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替代原有的Redis缓存方式
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"""
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import uuid
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from datetime import datetime
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from sqlalchemy import Column, String, Text, DateTime, Index
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from sqlalchemy.dialects.postgresql import UUID, JSONB
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from app.db import Base
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class ImplicitEmotionsStorage(Base):
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"""隐性记忆和情绪存储表"""
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__tablename__ = "implicit_emotions_storage"
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# 主键
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id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4, comment="主键ID")
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# 用户标识
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end_user_id = Column(String(255), nullable=False, unique=True, index=True, comment="终端用户ID")
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# 隐性记忆画像数据（JSON格式）
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implicit_profile = Column(JSONB, nullable=True, comment="隐性记忆用户画像数据")
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# 情绪建议数据（JSON格式）
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emotion_suggestions = Column(JSONB, nullable=True, comment="情绪个性化建议数据")
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# 时间戳
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created_at = Column(DateTime, nullable=False, default=datetime.utcnow, comment="创建时间")
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updated_at = Column(DateTime, nullable=False, default=datetime.utcnow, onupdate=datetime.utcnow, comment="更新时间")
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# 数据生成时间（用于业务逻辑）
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implicit_generated_at = Column(DateTime, nullable=True, comment="隐性记忆画像生成时间")
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emotion_generated_at = Column(DateTime, nullable=True, comment="情绪建议生成时间")
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# 索引
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__table_args__ = (
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Index('idx_end_user_id', 'end_user_id'),
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Index('idx_updated_at', 'updated_at'),
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)
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def __repr__(self):
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return f"<ImplicitEmotionsStorage(id={self.id}, end_user_id={self.end_user_id})>"
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