


from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE__				:    int         =    {
    """configuration_xlm_prophetnet""": ["""XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """XLMProphetNetConfig"""],
}

try:
   if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE__				:    List[str]         =    ["""XLMProphetNetTokenizer"""]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE__				:    List[Any]         =    [
       """XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """XLMProphetNetDecoder""",
       """XLMProphetNetEncoder""",
       """XLMProphetNetForCausalLM""",
       """XLMProphetNetForConditionalGeneration""",
       """XLMProphetNetModel""",
       """XLMProphetNetPreTrainedModel""",
   ]


if TYPE_CHECKING:
   from .configuration_xlm_prophetnet import XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMProphetNetConfig

   try:
      if not is_sentencepiece_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_xlm_prophetnet import XLMProphetNetTokenizer

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_xlm_prophetnet import (
          XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST,
          XLMProphetNetDecoder,
          XLMProphetNetEncoder,
          XLMProphetNetForCausalLM,
          XLMProphetNetForConditionalGeneration,
          XLMProphetNetModel,
          XLMProphetNetPreTrainedModel,
      )

else:
   import sys

   SCREAMING_SNAKE_CASE__				:    Dict         =    _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)









import os

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

SCREAMING_SNAKE_CASE__				:    int         =    {'UserAgent': UserAgent().random}
SCREAMING_SNAKE_CASE__				:    Tuple         =    'https://www.mywaifulist.moe/random'




def       a__						(		snake_case__				:       str	,      snake_case__				:       str    ):
  _UpperCAmelCase		:       Any       =    requests.get(snake_case__	,      headers=snake_case__    )
  with open(snake_case__	,      """wb"""    ) as file:
    file.write(image.content    )




def       a__						(		):
  _UpperCAmelCase		:       List[Any]       =    BeautifulSoup(requests.get(snake_case__	,      headers=snake_case__    ).text	,      """html.parser"""    )
  _UpperCAmelCase		:       Optional[int]       =    soup.find("""meta"""	,      attrs={"""property""": """og:title"""}    ).attrs["""content"""]
  _UpperCAmelCase		:       int       =    soup.find("""meta"""	,      attrs={"""property""": """og:image"""}    ).attrs["""content"""]
  _UpperCAmelCase		:       Any       =    soup.find("""p"""	,      id="""description"""    ).get_text()
  _UpperCAmelCase,_UpperCAmelCase		:       Dict       =    os.path.splitext(os.path.basename(snake_case__    )    )
  _UpperCAmelCase		:       Tuple       =    title.strip().replace(""" """	,      """_"""    )
  _UpperCAmelCase		:       Optional[Any]       =    f'''{image_title}{image_extension}'''
  save_image(snake_case__	,      snake_case__    )
  return (title, description, image_title)


if __name__ == "__main__":
 SCREAMING_SNAKE_CASE__     ,				SCREAMING_SNAKE_CASE__     ,				SCREAMING_SNAKE_CASE__				:    Optional[int]         =    random_anime_character()
 print(F'{title}\n\n{desc}\n\nImage saved : {image_title}')





