39 lines
1.6 KiB
Python
39 lines
1.6 KiB
Python
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"""
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用户行为指纹模型 — 用户的数字行为特征向量和偏好权重
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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, JSON, Float, Integer
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from app.core.database import Base
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class UserFingerprint(Base):
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"""用户行为数字指纹"""
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__tablename__ = "user_fingerprints"
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id = Column(String(36), primary_key=True, default=lambda: str(uuid.uuid4()))
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user_id = Column(String(36), nullable=False, unique=True, index=True, comment="用户ID")
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# 各场景偏好权重 (0-1 浮点数，JSON)
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# 示例: {"code_review": {"security": 0.4, "performance": 0.3, "readability": 0.2, "style": 0.1}}
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preference_weights = Column(JSON, nullable=True, comment="偏好权重")
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# 决策规则 (if-then 规则列表，JSON)
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# 示例: [{"if": "files_changed > 10 and no_tests", "then": "request_tests"}]
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decision_rules = Column(JSON, nullable=True, comment="决策规则")
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# 行为统计
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total_behaviors = Column(Integer, default=0, comment="总行为数")
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behaviors_by_category = Column(JSON, nullable=True, comment="按类别的行为分布")
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avg_response_time_ms = Column(Integer, nullable=True, comment="平均响应时间(ms)")
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# 模型版本
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model_version = Column(String(20), default="1.0", comment="指纹模型版本")
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last_trained_at = Column(DateTime, nullable=True, comment="上次训练时间")
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created_at = Column(DateTime, default=datetime.now)
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updated_at = Column(DateTime, default=datetime.now, onupdate=datetime.now)
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def __repr__(self):
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return f"<UserFingerprint(user={self.user_id}, version={self.model_version})>"
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