How to use the dtlpy.services function in dtlpy

parser.add_argument("--zazu_timer", action='store_true', default=False)
    args = parser.parse_args()

    with open('configs.json', 'r') as fp:
        configs = json.load(fp)
    try:
        maybe_login(configs['dataloop']['setenv'])
    except:
        pass
    maybe_do_deployment_stuff()

    if args.remote:

        configs_input = dl.FunctionIO(type='Json', name='configs', value=configs)
        inputs = [configs_input]
        zazu_service = dl.services.get('zazu')
        # get project id for billing bla bla bla
        dataset_obj = get_dataset_obj(configs['dataloop'])
        id = dataset_obj.project.id

        if args.search:
            zazu_service.execute(function_name='search', execution_input=inputs, project_id=id)
        if args.predict:
            zazu_service.execute(function_name='predict', execution_input=inputs, project_id=id)

    else:
        logger = init_logging(__name__)
        this_path = path = os.getcwd()
        configs_path = os.path.join(this_path, 'configs.json')
        configs = ConfigSpec(configs_path)
        opt_model = OptModel()
        opt_model.add_child_spec(configs, 'configs')

def _update_predict_service(self, new_best_checkpoint_obj):
        logger.info('update predict service')
        predict_service = dl.services.get('predict')
        logger.info('service: ' + str(predict_service))
        predict_service.input_params = {'model_id': self.model_obj.id,
                                        'checkpoint_id': new_best_checkpoint_obj.id}
        predict_service.update()
        logger.info('service: ' + str(predict_service))

def __init__(self, configs, time, test_dataset_id, query):
        logger.info('dtlpy version: ' + str(dl.__version__))
        logger.info('dtlpy info: ' + str(dl.info()))
        time = int(time)
        dl.setenv('prod')
        configs = json.loads(configs)
        query = json.loads(query)
        self.configs_input = dl.FunctionIO(type='Json', name='configs', value=configs)
        self.service = dl.services.get('zazu')
        project_name = configs['dataloop']['project']
        self.project = dl.projects.get(project_name)
        test_dataset = self.project.datasets.get(dataset_id=test_dataset_id)
        maybe_download_pred_data(dataset_obj=test_dataset, val_query=query)

        # add gt annotations
        filters = dl.Filters()
        filters.custom_filter = query
        dataset_name = test_dataset.name
        path_to_dataset = os.path.join(os.getcwd(), dataset_name)
        # only download if doesnt exist
        if not os.path.exists(path_to_dataset):
            download_and_organize(path_to_dataset=path_to_dataset, dataset_obj=test_dataset, filters=filters)

        json_file_path = os.path.join(path_to_dataset, 'json')
        self.model_obj = self.project.models.get(model_name='retinanet')