class_docstr: Handles incoming messages with low NLU confidence.
class_docstr_tok: ["Handles","incoming","messages","with","low","NLU","confidence","."]
docstr: The component's default config (see parent class for full docstring).
docstr_tok: ["The","component","'s","default","config","(","see","parent","class","for","full","docstring",")","."]
code: def get_default_config() -> Dict[Text, Any]:
      """The component's default config (see parent class for full docstring)."""
      # please make sure to update the docs when changing a default parameter
      return {
          # If all intent confidence scores are beyond this threshold, set the current
          # intent to `FALLBACK_INTENT_NAME`
          THRESHOLD_KEY: DEFAULT_NLU_FALLBACK_THRESHOLD,
          # If the confidence scores for the top two intent predictions are closer
          # than `AMBIGUITY_THRESHOLD_KEY`,
          # then `FALLBACK_INTENT_NAME` is predicted.
          AMBIGUITY_THRESHOLD_KEY: DEFAULT_NLU_FALLBACK_AMBIGUITY_THRESHOLD,
      }
  
imports: from __future__ import annotations
  import copy
  import logging
  from typing import Any, List, Text, Dict, Type, Union, Tuple, Optional
  from rasa.engine.graph import GraphComponent, ExecutionContext
  from rasa.engine.recipes.default_recipe import DefaultV1Recipe
  from rasa.engine.storage.resource import Resource
  from rasa.engine.storage.storage import ModelStorage
  from rasa.shared.constants import DEFAULT_NLU_FALLBACK_INTENT_NAME
  from rasa.core.constants import DEFAULT_NLU_FALLBACK_THRESHOLD, DEFAULT_NLU_FALLBACK_AMBIGUITY_THRESHOLD
  from rasa.nlu.classifiers.classifier import IntentClassifier
  from rasa.shared.nlu.training_data.message import Message
  from rasa.shared.nlu.constants import INTENT, INTENT_NAME_KEY, INTENT_RANKING_KEY, PREDICTED_CONFIDENCE_KEY
label_desc: Use image node_id 2 for calling the FallbackClassifier obj's underlying member method code with example usage: obj.get_default_config() and returns: dict