code: def test_generate_multiple_text_responses_with_valid_prompt_and_generation_parameters(
      self,
      mock_check_valid_model,
      mock_auto_tokenizer,
      mock_text_generation,
      chat_messages,
  ):
      model = "meta-llama/Llama-2-13b-chat-hf"
      token = None
      generation_kwargs = {"n": 3}
      stop_words = ["stop"]
      streaming_callback = None
  
      generator = HuggingFaceTGIChatGenerator(
          model=model,
          token=token,
          generation_kwargs=generation_kwargs,
          stop_words=stop_words,
          streaming_callback=streaming_callback,
      )
      generator.warm_up()
  
      response = generator.run(chat_messages)
  
      # check kwargs passed to text_generation
      _, kwargs = mock_text_generation.call_args
      assert kwargs == {"details": True, "stop_sequences": ["stop"]}
  
      # note how n caused n replies to be generated
      assert isinstance(response, dict)
      assert "replies" in response
      assert isinstance(response["replies"], list)
      assert len(response["replies"]) == 3
      assert [
          isinstance(reply, ChatMessage)
          for reply in response["replies"]
      ]
  
imports: from unittest.mock import patch, MagicMock, Mock
  import pytest
  from huggingface_hub.inference._text_generation import TextGenerationStreamResponse, Token, StreamDetails, FinishReason
  from huggingface_hub.utils import RepositoryNotFoundError
  from haystack.components.generators.chat import HuggingFaceTGIChatGenerator
  from haystack.dataclasses import StreamingChunk, ChatMessage
label_desc: Use image node_id 11 for calling the TestHuggingFaceTGIChatGenerator obj's underlying member method code with example usage: obj.test_generate_multiple_text_responses_with_valid_prompt_and_generation_parameters(mock_check_valid_model, mock_auto_tokenizer, mock_text_generation, chat_messages) without return types