class_docstr: Natural language generator that generates messages based on responses.
  
  The responses can use variables to customize the utterances based on the
  state of the dialogue.
class_docstr_tok: ["Natural","language","generator","that","generates","messages","based","on","responses",".","The","responses","can","use","variables","to","customize","the","utterances","based","on","the","state","of","the","dialogue","."]
docstr: Creates a Template Natural Language Generator.
  
  Args:
      responses: responses that will be used to generate messages.
docstr_tok: ["Creates","a","Template","Natural","Language","Generator",".","Args",":","responses",":","responses","that","will","be","used","to","generate","messages","."]
code: def __init__(
      self, responses: Dict[Text, List[Dict[Text, Any]]]
  ) -> None:
      """Creates a Template Natural Language Generator.
  
      Args:
          responses: responses that will be used to generate messages.
      """
      self.responses = responses
  
file_path: rasa/rasa/core/nlg/response.py
imports: import copy
  import logging
  from rasa.shared.core.trackers import DialogueStateTracker
  from typing import Text, Any, Dict, Optional, List
  from rasa.core.nlg import interpolator
  from rasa.core.nlg.generator import NaturalLanguageGenerator, ResponseVariationFilter
  from rasa.shared.constants import RESPONSE_CONDITION
label_desc: Use image node_id 1 to create a new TemplatedNaturalLanguageGenerator object from inherited base classes: NaturalLanguageGenerator with example: obj = TemplatedNaturalLanguageGenerator(responses)