def METHOD_NAME(sklearn_knn_model):
    model_name = f"wheels-test-{random_int()}"
    artifact_path = "model"
    model_uri = f"models:/{model_name}/1"
    # Log a model
    with mlflow.start_run():
        original_run_id = mlflow.tracking.fluent._get_or_start_run().info.run_id
        mlflow.sklearn.log_model(
            sk_model=sklearn_knn_model.model,
            artifact_path=artifact_path,
            registered_model_name=model_name,
        )
    model_version_without_source = ModelVersion(name=model_name, version=1, creation_timestamp=124)
    assert model_version_without_source.run_id is None
    with mock.patch.object(
        MlflowClient, "get_model_version", return_value=model_version_without_source
    ) as mlflow_client_mock:
        wheeled_model_info = add_libraries_to_model(model_uri)
        assert wheeled_model_info.run_id is not None
        assert wheeled_model_info.run_id != original_run_id
        mlflow_client_mock.assert_called_once_with(model_name, "1")