code: def test_generate_text_response_with_valid_prompt_and_generation_parameters(
      self,
      mock_check_valid_model,
      mock_auto_tokenizer,
      mock_text_generation,
  ):
      model = "mistralai/Mistral-7B-v0.1"
  
      generation_kwargs = {"n": 1}
      stop_words = ["stop"]
      streaming_callback = None
  
      generator = HuggingFaceTGIGenerator(
          model=model,
          generation_kwargs=generation_kwargs,
          stop_words=stop_words,
          streaming_callback=streaming_callback,
      )
      generator.warm_up()
  
      prompt = "Hello, how are you?"
      response = generator.run(prompt)
  
      # check kwargs passed to text_generation
      # note how n was not passed to text_generation
      _, kwargs = mock_text_generation.call_args
      assert kwargs == {"details": True, "stop_sequences": ["stop"]}
  
      assert isinstance(response, dict)
      assert "replies" in response
      assert "meta" in response
      assert isinstance(response["replies"], list)
      assert isinstance(response["meta"], list)
      assert len(response["replies"]) == 1
      assert len(response["meta"]) == 1
      assert [isinstance(reply, str) 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 import HuggingFaceTGIGenerator
  from haystack.dataclasses import StreamingChunk
label_desc: Use image node_id 6 for calling the TestHuggingFaceTGIGenerator obj's underlying member method code with example usage: obj.test_generate_text_response_with_valid_prompt_and_generation_parameters(mock_check_valid_model, mock_auto_tokenizer, mock_text_generation) without return types