code: def test_explainer_manager_request_local_explanations(self):
      (
          X_train,
          X_test,
          y_train,
          y_test,
          feature_names,
          _,
      ) = create_iris_data()
  
      model = create_lightgbm_classifier(X_train, y_train)
      X_train["target"] = y_train
      X_test["target"] = y_test
  
      rai_insights = RAIInsights(
          model=model,
          train=X_train,
          test=X_test.iloc[0:10],
          target_column="target",
          task_type="classification",
      )
      rai_insights.explainer.add()
      rai_insights.compute()
  
      local_explanations = rai_insights.explainer.request_explanations(
          local=True, data=X_test.drop(["target"], axis=1).iloc[0:1]
      )
      self.verify_explanations(local_explanations, is_global=False)
  
      with pytest.raises(
          UserConfigValidationException,
          match="Only one row of data is allowed for "
          "local explanation generation.",
      ):
          rai_insights.explainer.request_explanations(
              local=True, data=X_test.drop(["target"], axis=1)
          )
  
      with pytest.raises(
          UserConfigValidationException,
          match="Data is of type <class 'numpy.ndarray'>"
          " but it must be a pandas DataFrame.",
      ):
          rai_insights.explainer.request_explanations(
              local=True, data=X_test.drop(["target"], axis=1).values
          )
  
file_path: responsible-ai-toolbox/responsibleai/tests/explainer/test_explainer_manager.py
imports: import pandas
  import pytest
  from rai_test_utils.models.lightgbm import create_lightgbm_classifier
  from rai_test_utils.models.sklearn import create_complex_classification_pipeline
  from raiutils.exceptions import UserConfigValidationException
  from responsibleai._interfaces import ModelExplanationData
  from responsibleai.feature_metadata import FeatureMetadata
  from responsibleai.rai_insights import RAIInsights
  from ..common_utils import ADULT_CATEGORICAL_FEATURES_AFTER_DROP, ADULT_DROPPED_FEATURES, create_adult_income_dataset, create_iris_data
label_desc: Use image node_id 3 for calling the TestExplainerManager obj's underlying member method code with example usage: obj.test_explainer_manager_request_local_explanations() without return types