code: def setup_env():
      # Install licensed libraries on the fly into the current python environment
      # and make them available in the executing python process
      if "JSL_ACCESS_KEY" in os.environ:
          # via access_token
          from johnsnowlabs.py_models.jsl_secrets import JslSecrets
  
          # Download License & Install Licensed Libraries
          nlp.install(access_token=os.environ["JSL_ACCESS_KEY"])
          # Write json secret to env
          secrets = JslSecrets.from_jsl_home()
          os.environ[
              mlflow.johnsnowlabs._JOHNSNOWLABS_ENV_JSON_LICENSE_KEY
          ] = json.dumps(
              {
                  "SECRET": secrets.HC_SECRET,
                  "AWS_ACCESS_KEY_ID": secrets.AWS_ACCESS_KEY_ID,
                  "AWS_SECRET_ACCESS_KEY": secrets.AWS_SECRET_ACCESS_KEY,
                  "SPARK_NLP_LICENSE": secrets.HC_LICENSE,
              }
          )
      # mlflow.johnsnowlabs._JOHNSNOWLABS_JSON_VARS needs to be present now either from CI or from
      # JSL_ACCESS_KEY
      mlflow.johnsnowlabs._set_env_vars()
      nlp.install()
  
imports: import json
  import os
  from pathlib import Path
  from unittest import mock
  import pandas
  import pyspark
  import pytest
  from johnsnowlabs import nlp
  from packaging.version import Version
  import mlflow
  import mlflow.utils.file_utils
  from mlflow import pyfunc
  from mlflow.environment_variables import MLFLOW_DFS_TMP
  from mlflow.models import Model, infer_signature
  from mlflow.models.utils import _read_example
  from mlflow.pyfunc import spark_udf
  from mlflow.utils.environment import _mlflow_conda_env
  from mlflow.utils.file_utils import TempDir
  from tests.helper_functions import assert_register_model_called_with_local_model_path
label_desc: Use image node_id 1 for calling a global function with example usage: setup_env() without return types