code: def test_process_does_not_do_anything(
      regex_message_handler: RegexMessageHandler, text: Text
  ):
      message = Message(
          data={TEXT: text, INTENT: "bla"},
          features=[
              Features(
                  features=np.zeros((1, 1)),
                  feature_type=FEATURE_TYPE_SENTENCE,
                  attribute=TEXT,
                  origin="nlu-pipeline",
              )
          ],
      )
  
      # construct domain from expected intent/entities
      domain = Domain(
          intents=["intent"],
          entities=["entity"],
          slots=[],
          responses={},
          action_names=[],
          forms={},
          data={},
      )
  
      parsed_messages = regex_message_handler.process([message], domain)
  
      assert parsed_messages[0] == message
  
file_path: rasa/tests/nlu/classifiers/test_regex_message_handler.py
imports: from rasa.nlu.constants import EXTRACTOR
  from rasa.shared.nlu.training_data.features import Features
  from typing import Text
  import numpy
  from rasa.shared.nlu.training_data.message import Message
  from rasa.shared.core.domain import Domain
  from rasa.engine.storage.resource import Resource
  from rasa.engine.graph import ExecutionContext
  from rasa.engine.storage.storage import ModelStorage
  from rasa.nlu.classifiers.regex_message_handler import RegexMessageHandler
  import pytest
  from rasa.shared.constants import INTENT_MESSAGE_PREFIX
  from rasa.shared.nlu.constants import FEATURE_TYPE_SENTENCE, INTENT, TEXT, ENTITIES
label_desc: Use image node_id 2 for calling a global function with example usage: test_process_does_not_do_anything(regex_message_handler, text) without return types