code: def on_predict(self, data):
      try:
          data = pd.DataFrame(
              data, columns=self.dashboard_input.dataset.feature_names
          )
          data = self._analysis.get_test_data(test_data=data)
          if self._is_classifier:
              prediction = convert_to_list(
                  self._analysis.model.predict_proba(data),
                  EXP_VIZ_ERR_MSG,
              )
          else:
              prediction = convert_to_list(
                  self._analysis.model.predict(data), EXP_VIZ_ERR_MSG
              )
          return {WidgetRequestResponseConstants.data: prediction}
      except Exception as e:
          print(e)
          traceback.print_exc()
          e_str = _format_exception(e)
          return {
              WidgetRequestResponseConstants.error: "Model threw exception"
              " while predicting..."
              "inner error: {}".format(e_str),
              WidgetRequestResponseConstants.data: [],
          }
  
imports: import traceback
  from typing import List, Optional
  import numpy
  import pandas
  from erroranalysis._internal.constants import display_name_to_metric
  from raiutils.cohort import Cohort, CohortFilter, CohortFilterMethods
  from raiutils.data_processing import convert_to_list, serialize_json_safe
  from raiutils.exceptions import UserConfigValidationException
  from raiutils.models import ModelTask, is_classifier
  from raiwidgets.constants import ErrorMessages
  from raiwidgets.error_handling import _format_exception
  from raiwidgets.interfaces import WidgetRequestResponseConstants
  from responsibleai import RAIInsights
  from responsibleai._internal.constants import ManagerNames
label_desc: Use image node_id 4 for calling the ResponsibleAIDashboardInput obj's underlying member method code with example usage: obj.on_predict(data) and returns: dict, dict