code: def get_model_names(using_args):
      """Get the model names from the using_args. Model names is a list of model names to train.
      If the model is not an ensemble, it only contains one model"""
      model_names = (
          anomaly_type_to_model_name(using_args["anomaly_type"])
          if "anomaly_type" in using_args
          else None
      )
      model_names = (
          using_args["model_name"]
          if "model_name" in using_args
          else model_names
      )
      model_names = (
          using_args["ensemble_models"]
          if "ensemble_models" in using_args
          else model_names
      )
      model_names = (
          [model_names] if model_names is None else model_names
      )
      model_names = (
          [model_names] if type(model_names) is str else model_names
      )
      return model_names
  
imports: from mindsdb.integrations.libs.base import BaseMLEngine
  import pandas
  from mindsdb.integrations.handlers.anomaly_detection_handler.utils import train_unsupervised, train_supervised, train_semisupervised
  from joblib import dump, load
  from pyod.models.ecod import ECOD
  from pyod.models.xgbod import XGBOD
  from catboost import CatBoostClassifier
  from pyod.models.lof import LOF
  from pyod.models.knn import KNN
  from pyod.models.pca import PCA
  from xgboost import XGBClassifier
  from sklearn.naive_bayes import GaussianNB
  import numpy
  import os
label_desc: Use image node_id 5 for calling a global function with example usage: get_model_names(using_args) and returns: model_names