
import unittest

from transformers import load_tool

from .test_tools_common import ToolTesterMixin


__lowerCamelCase							=       """
Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot app targeted at teenagers.[2] After open-sourcing the model behind the chatbot, the company pivoted to focus on being a platform for machine learning.

In March 2021, Hugging Face raised $40 million in a Series B funding round.[3]

On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model.[4] In 2022, the workshop concluded with the announcement of BLOOM, a multilingual large language model with 176 billion parameters.[5]
"""






class   UpperCAmelCase		(						unittest.TestCase       ,A_ ):



   def 				_SCREAMING_SNAKE_CASE   (self		:					Dict )		->	int:


          '''simple docstring'''


          snake_case       :   Optional[Any]							=      load_tool("text-question-answering" )
          self.tool.setup()
          snake_case       :   str							=      load_tool("text-question-answering"    ,						remote=snake_case__ )



   def 				_SCREAMING_SNAKE_CASE   (self		:					Optional[Any] )		->	int:


          '''simple docstring'''


          snake_case       :   Tuple							=      self.tool(snake_case__    ,						"What did Hugging Face do in April 2021?" )
          self.assertEqual(snake_case__    ,						"launched the BigScience Research Workshop" )



   def 				_SCREAMING_SNAKE_CASE   (self		:					Any )		->	Optional[int]:


          '''simple docstring'''


          snake_case       :   Optional[int]							=      self.remote_tool(snake_case__    ,						"What did Hugging Face do in April 2021?" )
          self.assertEqual(snake_case__    ,						"launched the BigScience Research Workshop" )



   def 				_SCREAMING_SNAKE_CASE   (self		:					int )		->	int:


          '''simple docstring'''


          snake_case       :   Dict							=      self.tool(text=snake_case__    ,						question="What did Hugging Face do in April 2021?" )
          self.assertEqual(snake_case__    ,						"launched the BigScience Research Workshop" )



   def 				_SCREAMING_SNAKE_CASE   (self		:					Optional[Any] )		->	int:


          '''simple docstring'''


          snake_case       :   List[Any]							=      self.remote_tool(text=snake_case__    ,						question="What did Hugging Face do in April 2021?" )
          self.assertEqual(snake_case__    ,						"launched the BigScience Research Workshop" )










'''simple docstring'''





from typing import TYPE_CHECKING

from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase_		       =  {"configuration_mmbt": ["MMBTConfig"]}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_		       =  ["MMBTForClassification", "MMBTModel", "ModalEmbeddings"]


if TYPE_CHECKING:
  from .configuration_mmbt import MMBTConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_mmbt import MMBTForClassification, MMBTModel, ModalEmbeddings

else:
  import sys

  lowercase_		       =  _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



