


"""simple docstring"""


import unittest

from transformers import load_tool

from .test_tools_common import ToolTesterMixin


_snake_case          =							"\nHugging 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.\n\nIn March 2021, Hugging Face raised $40 million in a Series B funding round.[3]\n\nOn 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]\n"



class   _a      (      unittest.TestCase		,		SCREAMING_SNAKE_CASE_ ):
    def      _UpperCamelCase       ( self							:					Any				):
          lowerCamelCase__           =		load_tool('text-question-answering'				)
          self.tool.setup()
          lowerCamelCase__           =		load_tool('text-question-answering'							,					remote=SCREAMING_SNAKE_CASE__				)
    def      _UpperCamelCase       ( self							:					List[str]				):
          lowerCamelCase__           =		self.tool(SCREAMING_SNAKE_CASE__							,					'What did Hugging Face do in April 2021?'				)
          self.assertEqual(SCREAMING_SNAKE_CASE__							,					'launched the BigScience Research Workshop'				)
    def      _UpperCamelCase       ( self							:					Optional[int]				):
          lowerCamelCase__           =		self.remote_tool(SCREAMING_SNAKE_CASE__							,					'What did Hugging Face do in April 2021?'				)
          self.assertEqual(SCREAMING_SNAKE_CASE__							,					'launched the BigScience Research Workshop'				)
    def      _UpperCamelCase       ( self							:					List[str]				):
          lowerCamelCase__           =		self.tool(text=SCREAMING_SNAKE_CASE__							,					question='What did Hugging Face do in April 2021?'				)
          self.assertEqual(SCREAMING_SNAKE_CASE__							,					'launched the BigScience Research Workshop'				)


    def      _UpperCamelCase       ( self							:					Any				):
          lowerCamelCase__           =		self.remote_tool(text=SCREAMING_SNAKE_CASE__							,					question='What did Hugging Face do in April 2021?'				)
          self.assertEqual(SCREAMING_SNAKE_CASE__							,					'launched the BigScience Research Workshop'				)







"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


_snake_case          =							{
    "configuration_blenderbot": [
        "BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "BlenderbotConfig",
        "BlenderbotOnnxConfig",
    ],
    "tokenization_blenderbot": ["BlenderbotTokenizer"],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case          =							["BlenderbotTokenizerFast"]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case          =							[
       "BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST",
       "BlenderbotForCausalLM",
       "BlenderbotForConditionalGeneration",
       "BlenderbotModel",
       "BlenderbotPreTrainedModel",
   ]


try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case          =							[
       "TFBlenderbotForConditionalGeneration",
       "TFBlenderbotModel",
       "TFBlenderbotPreTrainedModel",
   ]


try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case          =							[
       "FlaxBlenderbotForConditionalGeneration",
       "FlaxBlenderbotModel",
       "FlaxBlenderbotPreTrainedModel",
   ]


if TYPE_CHECKING:
   from .configuration_blenderbot import (
       BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP,
       BlenderbotConfig,
       BlenderbotOnnxConfig,
   )
   from .tokenization_blenderbot import BlenderbotTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_blenderbot_fast import BlenderbotTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_blenderbot import (
          BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST,
          BlenderbotForCausalLM,
          BlenderbotForConditionalGeneration,
          BlenderbotModel,
          BlenderbotPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_blenderbot import (
          TFBlenderbotForConditionalGeneration,
          TFBlenderbotModel,
          TFBlenderbotPreTrainedModel,
      )

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_blenderbot import (
          FlaxBlenderbotForConditionalGeneration,
          FlaxBlenderbotModel,
          FlaxBlenderbotPreTrainedModel,
      )

else:
   import sys

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



