"""
用户行为指纹模型 — 用户的数字行为特征向量和偏好权重
"""
import uuid
from datetime import datetime
from sqlalchemy import Column, String, Text, DateTime, JSON, Float, Integer
from app.core.database import Base


class UserFingerprint(Base):
    """用户行为数字指纹"""
    __tablename__ = "user_fingerprints"

    id = Column(String(36), primary_key=True, default=lambda: str(uuid.uuid4()))
    user_id = Column(String(36), nullable=False, unique=True, index=True, comment="用户ID")

    # 各场景偏好权重 (0-1 浮点数，JSON)
    # 示例: {"code_review": {"security": 0.4, "performance": 0.3, "readability": 0.2, "style": 0.1}}
    preference_weights = Column(JSON, nullable=True, comment="偏好权重")

    # 决策规则 (if-then 规则列表，JSON)
    # 示例: [{"if": "files_changed > 10 and no_tests", "then": "request_tests"}]
    decision_rules = Column(JSON, nullable=True, comment="决策规则")

    # 行为统计
    total_behaviors = Column(Integer, default=0, comment="总行为数")
    behaviors_by_category = Column(JSON, nullable=True, comment="按类别的行为分布")
    avg_response_time_ms = Column(Integer, nullable=True, comment="平均响应时间(ms)")

    # 模型版本
    model_version = Column(String(20), default="1.0", comment="指纹模型版本")
    last_trained_at = Column(DateTime, nullable=True, comment="上次训练时间")

    created_at = Column(DateTime, default=datetime.now)
    updated_at = Column(DateTime, default=datetime.now, onupdate=datetime.now)

    def __repr__(self):
        return f"<UserFingerprint(user={self.user_id}, version={self.model_version})>"