





"""simple docstring"""




# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ..models.auto import AutoModelForVisionaSeq
from ..utils import requires_backends
from .base import PipelineTool


if TYPE_CHECKING:
		from PIL import Image


class        __UpperCamelCase				(						UpperCAmelCase__						):
							lowerCamelCase   :					int      					="""Salesforce/blip-image-captioning-base"""
							lowerCamelCase   :					Dict      					=(
							    """This is a tool that generates a description of an image. It takes an input named `image` which should be the """
							    """image to caption, and returns a text that contains the description in English."""
							)
							lowerCamelCase   :					Optional[int]      					="""image_captioner"""
							lowerCamelCase   :					Optional[Any]      					=AutoModelForVisionaSeq

							lowerCamelCase   :					Optional[Any]      					=["""image"""]
							lowerCamelCase   :					str      					=["""text"""]






							def __init__(   self      ,					*lowerCAmelCase__      ,					**lowerCAmelCase__      )	-> Union[str, Any]:
								requires_backends(self      ,					["vision"]      )
								super().__init__(*__lowercase      ,					**__lowercase      )






							def     __a   (   self      ,					lowerCAmelCase__      )	-> Optional[int]:
								return self.pre_processor(images=__lowercase      ,					return_tensors="pt"      )






							def     __a   (   self      ,					lowerCAmelCase__      )	-> Optional[int]:
								return self.model.generate(**__lowercase      )






							def     __a   (   self      ,					lowerCAmelCase__      )	-> str:
								return self.pre_processor.batch_decode(__lowercase      ,					skip_special_tokens=__lowercase      )[0].strip()






from __future__ import annotations

import requests



def 	lowerCAmelCase       (						lowerCAmelCase_       )->       dict:
				lowerCAmelCase_       :					List[Any]			 = f"""https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"""
				return requests.get(lowerCAmelCase_       ).json()



def 	lowerCAmelCase       (						lowerCAmelCase_ = 10       )->       list[dict]:
				lowerCAmelCase_       :					List[Any]			 = '''https://hacker-news.firebaseio.com/v0/topstories.json?print=pretty'''
				lowerCAmelCase_       :					Tuple			 = requests.get(lowerCAmelCase_       ).json()[:max_stories]
				return [get_hackernews_story(lowerCAmelCase_       ) for story_id in story_ids]



def 	lowerCAmelCase       (						lowerCAmelCase_ = 10       )->       str:
				lowerCAmelCase_       :					Optional[Any]			 = hackernews_top_stories(lowerCAmelCase_       )
				return "\n".join('''* [{title}]({url})'''.format(**lowerCAmelCase_       ) for story in stories       )


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