code: def test_modellibrary_required_models():
      class SomeModel(Model):
          CONFIGURATIONS = {"yolo": {}, "les simpsons": {}}
  
          def _predict(self, item):
              return item
  
      p = ModelLibrary(models=SomeModel)
      m = p.get("yolo")
      assert m
      assert m.configuration_key == "yolo"
      assert m.__class__.__name__ == "SomeModel"
      assert m.model_settings == {}
      assert m.asset_path == ""
      assert m.batch_size is None
  
      class SomeOtherModel(Model):
          pass
  
      with pytest.raises(ValueError):
          # model does not exist
          p.get("yolo", model_type=SomeOtherModel)
  
imports: import asyncio
  import os
  import pytest
  from modelkit.assets.errors import AssetDoesNotExistError, InvalidAssetSpecError
  from modelkit.core import errors
  from modelkit.core.library import ConfigurationNotFoundException, ModelLibrary, download_assets, load_model
  from modelkit.core.model import Asset, AsyncModel, Model
  from modelkit.core.model_configuration import ModelConfiguration, _configurations_from_objects, configure, list_assets
  from modelkit.core.settings import LibrarySettings
  from tests import TEST_DIR, testmodels
  from tests.assets.test_versioning import test_versioning
label_desc: Use image node_id 6 for calling a global function with example usage: test_modellibrary_required_models() and returns: item