code: def test_parse_with_intents_filter(self):
      # Given / When
      dataset_stream = io.StringIO(
          """
  ---
  type: intent
  name: MakeTea
  utterances:
    - make me a [beverage_temperature:Temperature](hot) cup of tea
    - make me [number_of_cups:snips/number](five) tea cups
  
  ---
  type: intent
  name: Make,Coffee
  utterances:
    - brew [number_of_cups:snips/number](one) cup of coffee please
    - make me [number_of_cups] cups of coffee"""
      )
      dataset = Dataset.from_yaml_files("en", [dataset_stream]).json
      nlu_engine = SnipsNLUEngine().fit(dataset)
      nlu_engine.persist(self.tmp_file_path)
  
      # When / Then
      output_target = io.StringIO()
      with self.fail_if_exception("Failed to parse using CLI script"):
          with redirect_stdout(output_target):
              parse(
                  str(self.tmp_file_path),
                  "Make me two cups of coffee",
                  False,
                  'MakeTea,"Make,Coffee"',
              )
      output = output_target.getvalue()
  
      # Then
      expected_output = """{
    "input": "Make me two cups of coffee",
    "intent": {
      "intentName": "Make,Coffee",
      "probability": 1.0
    },
    "slots": [
      {
        "entity": "snips/number",
        "range": {
          "end": 11,
          "start": 8
        },
        "rawValue": "two",
        "slotName": "number_of_cups",
        "value": {
          "kind": "Number",
          "value": 2.0
        }
      }
    ]
  }
  """
      self.assertEqual(expected_output, output)
  
imports: import io
  import shutil
  import sys
  import tempfile
  from mock import patch
  from snips_nlu.__about__ import __model_version__, __version__
  from snips_nlu.cli import get_arg_parser
  from snips_nlu.cli.generate_dataset import generate_dataset
  from snips_nlu.cli.inference import parse
  from snips_nlu.cli.metrics import cross_val_metrics, train_test_metrics
  from snips_nlu.cli.training import train
  from snips_nlu.common.utils import unicode_string, json_string
  from snips_nlu.dataset import Dataset
  from snips_nlu.nlu_engine import SnipsNLUEngine
  from snips_nlu.tests.utils import SnipsTest, TEST_PATH, redirect_stdout
label_desc: Use image node_id 5 for calling the TestCLI obj's underlying member method code with example usage: obj.test_parse_with_intents_filter() without return types