


'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


A__:    List[str]					    =       {
    '''configuration_blip''': [
        '''BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''BlipConfig''',
        '''BlipTextConfig''',
        '''BlipVisionConfig''',
    ],
    '''processing_blip''': ['''BlipProcessor'''],
}

try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   A__:    List[Any]					    =       ['''BlipImageProcessor''']


try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   A__:    Optional[int]					    =       [
       '''BLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''BlipModel''',
       '''BlipPreTrainedModel''',
       '''BlipForConditionalGeneration''',
       '''BlipForQuestionAnswering''',
       '''BlipVisionModel''',
       '''BlipTextModel''',
       '''BlipForImageTextRetrieval''',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   A__:    Tuple					    =       [
       '''TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''TFBlipModel''',
       '''TFBlipPreTrainedModel''',
       '''TFBlipForConditionalGeneration''',
       '''TFBlipForQuestionAnswering''',
       '''TFBlipVisionModel''',
       '''TFBlipTextModel''',
       '''TFBlipForImageTextRetrieval''',
   ]

if TYPE_CHECKING:
   from .configuration_blip import BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP, BlipConfig, BlipTextConfig, BlipVisionConfig
   from .processing_blip import BlipProcessor

   try:
      if not is_vision_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .image_processing_blip import BlipImageProcessor

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_blip import (
          BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
          BlipForConditionalGeneration,
          BlipForImageTextRetrieval,
          BlipForQuestionAnswering,
          BlipModel,
          BlipPreTrainedModel,
          BlipTextModel,
          BlipVisionModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_blip import (
          TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFBlipForConditionalGeneration,
          TFBlipForImageTextRetrieval,
          TFBlipForQuestionAnswering,
          TFBlipModel,
          TFBlipPreTrainedModel,
          TFBlipTextModel,
          TFBlipVisionModel,
      )

else:
   import sys

   A__:    Union[str, Any]					    =       _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






'''simple docstring'''







from __future__ import annotations

import requests


def 	SCREAMING_SNAKE_CASE_					(  _UpperCAmelCase	:	str  )  ->			dict:
       _a    : Any     					=F"https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"
       return requests.get(_UpperCAmelCase  ).json()


def 	SCREAMING_SNAKE_CASE_					(  _UpperCAmelCase	:	int = 10  )  ->			list[dict]:
       _a    : Union[str, Any]     					="""https://hacker-news.firebaseio.com/v0/topstories.json?print=pretty"""
       _a    : int     					=requests.get(_UpperCAmelCase  ).json()[:max_stories]
       return [get_hackernews_story(_UpperCAmelCase  ) for story_id in story_ids]


def 	SCREAMING_SNAKE_CASE_					(  _UpperCAmelCase	:	int = 10  )  ->			str:
       _a    : Union[str, Any]     					=hackernews_top_stories(_UpperCAmelCase  )
       return "\n".join("""* [{title}]({url})""".format(**_UpperCAmelCase  ) for story in stories  )


if __name__ == "__main__":
   print(hackernews_top_stories_as_markdown())


