app/models/mlmodel.py

import uuid
import datetime
import json
from sqlalchemy import Column, String, DateTime, Text, Integer, Float, ForeignKey
from sqlalchemy.orm import relationship
from app.database import Base


class MLModel(Base):
    __tablename__ = "ml_models"

    id = Column(String, primary_key=True, default=lambda: str(uuid.uuid4()))
    user_id = Column(String, ForeignKey("users.id"), nullable=False)
    name = Column(String, nullable=False)
    model_type = Column(String, nullable=False)  # churn, lead
    feature_names_json = Column(Text, nullable=False)  # JSON list of feature names
    encoders_json = Column(Text, nullable=False)  # JSON dict of label encoders
    model_binary = Column(Text, nullable=False)  # base64 encoded XGBoost model
    metrics_json = Column(Text, default="{}")  # accuracy, roc_auc, etc.
    summary_json = Column(Text, default="{}")  # n_rows, n_features, etc.
    n_rows = Column(Integer, default=0)
    n_features = Column(Integer, default=0)
    created_at = Column(DateTime, default=datetime.datetime.utcnow)

    user = relationship("User", back_populates="ml_models")

    def get_feature_names(self):
        return json.loads(self.feature_names_json)

    def get_metrics(self):
        return json.loads(self.metrics_json)

    def get_summary(self):
        return json.loads(self.summary_json)