class_docstr: Generate bot utterances by using a remote endpoint for the generation.
  
  The generator will call the endpoint for each message it wants to
  generate. The endpoint needs to respond with a properly formatted
  json. The generator will use this message to create a response for
  the bot.
class_docstr_tok: ["Generate","bot","utterances","by","using","a","remote","endpoint","for","the","generation",".","The","generator","will","call","the","endpoint","for","each","message","it","wants","to","generate",".","The","endpoint","needs","to","respond","with","a","properly","formatted","json",".","The","generator","will","use","this","message","to","create","a","response","for","the","bot","."]
code: def __init__(self, endpoint_config: EndpointConfig) -> None:
      self.nlg_endpoint = endpoint_config
  
file_path: rasa/rasa/core/nlg/callback.py
imports: import json
  import logging
  from typing import List, Text, Any, Dict, Optional
  from rasa.core.constants import DEFAULT_REQUEST_TIMEOUT
  from rasa.core.nlg.generator import NaturalLanguageGenerator, ResponseVariationFilter
  from rasa.shared.core.trackers import DialogueStateTracker, EventVerbosity
  from rasa.shared.exceptions import RasaException
  from rasa.utils.endpoints import EndpointConfig
label_desc: Use image node_id 1 to create a new CallbackNaturalLanguageGenerator object from inherited base classes: NaturalLanguageGenerator with example: obj = CallbackNaturalLanguageGenerator(endpoint_config)