code: def test_condition(text_classification_string_class_dataset_mock):
      # Arrange
      check = SingleDatasetPerformance().add_condition_greater_than(0.7)
  
      # Act
      result = check.run(
          text_classification_string_class_dataset_mock,
          predictions=["wise", "wise", "meh"],
      )
      condition_result = check.conditions_decision(result)
  
      # Assert
      assert_that(
          condition_result,
          has_items(
              equal_condition_result(
                  is_pass=False,
                  details="Failed for metrics: ['F1', 'Precision', 'Recall']",
                  name="Selected metrics scores are greater than 0.7",
              )
          ),
      )
  
imports: import numpy
  from hamcrest import assert_that, calling, close_to, equal_to, has_items, raises
  from deepchecks.core.errors import DeepchecksValueError, ValidationError
  from deepchecks.nlp.checks.model_evaluation.single_dataset_performance import SingleDatasetPerformance
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 16 for calling a global function with example usage: test_condition(text_classification_string_class_dataset_mock) without return types