





import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if TYPE_CHECKING:
						from transformers.pipelines.conversational import Conversation


_SCREAMING_SNAKE_CASE      	=		logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE      	=		{"""tokenizer_file""": """tokenizer.json"""}

_SCREAMING_SNAKE_CASE      	=		{
    """tokenizer_file""": {
        """bigscience/tokenizer""": """https://huggingface.co/bigscience/tokenizer/blob/main/tokenizer.json""",
        """bigscience/bloom-560m""": """https://huggingface.co/bigscience/bloom-560m/blob/main/tokenizer.json""",
        """bigscience/bloom-1b1""": """https://huggingface.co/bigscience/bloom-1b1/blob/main/tokenizer.json""",
        """bigscience/bloom-1b7""": """https://huggingface.co/bigscience/bloom-1b7/blob/main/tokenizer.json""",
        """bigscience/bloom-3b""": """https://huggingface.co/bigscience/bloom-3b/blob/main/tokenizer.json""",
        """bigscience/bloom-7b1""": """https://huggingface.co/bigscience/bloom-7b1/blob/main/tokenizer.json""",
        """bigscience/bloom""": """https://huggingface.co/bigscience/bloom/blob/main/tokenizer.json""",
    },
}
class SCREAMING_SNAKE_CASE_						(					snake_case_					):
						__magic_name__:			str       =       VOCAB_FILES_NAMES
						__magic_name__:			Any       =       PRETRAINED_VOCAB_FILES_MAP
						__magic_name__:			Dict       =       ["input_ids", "attention_mask"]
						__magic_name__:			Tuple       =       None






						def __init__(      self      :      Tuple		,   _A      :      Tuple=None		,   _A      :      Optional[int]=None		,   _A      :      Optional[int]=None		,   _A      :      Optional[Any]="<unk>"		,   _A      :      Optional[int]="<s>"		,   _A      :      int="</s>"		,   _A      :      str="<pad>"		,   _A      :      Union[str, Any]=False		,   _A      :      Optional[Any]=False		,   **_A      :      Any		,   )							->    List[Any]:







							"""simple docstring"""


							super().__init__(
							    _A		,   _A		,   tokenizer_file=_A		,   unk_token=_A		,   bos_token=_A		,   eos_token=_A		,   pad_token=_A		,   add_prefix_space=_A		,   clean_up_tokenization_spaces=_A		,   **_A		,   )
							snake_case_		:			List[Any]											=	json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()	)
							if pre_tok_state.get('add_prefix_space'		,   _A	) != add_prefix_space:
								snake_case_		:			Any											=	getattr(_A		,   pre_tok_state.pop('type'	)	)
								snake_case_		:			Tuple											=	add_prefix_space
								snake_case_		:			Tuple											=	pre_tok_class(**_A	)

							snake_case_		:			Tuple											=	add_prefix_space






						def UpperCAmelCase_				(      self      :      str		,   *_A      :      Union[str, Any]		,   **_A      :      Optional[int]	)							->    BatchEncoding:







							"""simple docstring"""


							snake_case_		:			List[Any]											=	kwargs.get('is_split_into_words'		,   _A	)
							if not (self.add_prefix_space or not is_split_into_words):
								raise Exception(
								    F"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with"""
								    ' pretokenized inputs.'	)

							return super()._batch_encode_plus(*_A		,   **_A	)






						def UpperCAmelCase_				(      self      :      Dict		,   *_A      :      int		,   **_A      :      Optional[Any]	)							->    BatchEncoding:







							"""simple docstring"""


							snake_case_		:			int											=	kwargs.get('is_split_into_words'		,   _A	)

							if not (self.add_prefix_space or not is_split_into_words):
								raise Exception(
								    F"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with"""
								    ' pretokenized inputs.'	)

							return super()._encode_plus(*_A		,   **_A	)






						def UpperCAmelCase_				(      self      :      List[Any]		,   _A      :      str		,   _A      :      Optional[str] = None	)							->    Tuple[str]:







							"""simple docstring"""


							snake_case_		:			Dict											=	self._tokenizer.model.save(_A		,   name=_A	)
							return tuple(_A	)






						def UpperCAmelCase_				(      self      :      Dict		,   _A      :      "Conversation"	)							->    List[int]:







							"""simple docstring"""


							snake_case_		:			int											=	[]
							for is_user, text in conversation.iter_texts():
								input_ids.extend(self.encode(_A		,   add_special_tokens=_A	) + [self.eos_token_id]	)

							if len(_A	) > self.model_max_length:
								snake_case_		:			Dict											=	input_ids[-self.model_max_length :]
							return input_ids








import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

if __name__ == "__main__":
						_SCREAMING_SNAKE_CASE      	=		"""%20""".join(argv[1:]) if len(argv) > 1 else quote(str(input("""Search: """)))

						print("""Googling.....""")

						_SCREAMING_SNAKE_CASE      	=		F'''https://www.google.com/search?q={query}&num=100'''

						_SCREAMING_SNAKE_CASE      	=		requests.get(
						    url,
						    headers={"""User-Agent""": str(UserAgent().random)},
						)

						try:
												_SCREAMING_SNAKE_CASE      	=		(
												    BeautifulSoup(res.text, """html.parser""")
												    .find("""div""", attrs={"""class""": """yuRUbf"""})
												    .find("""a""")
												    .get("""href""")
												)

						except AttributeError:
												_SCREAMING_SNAKE_CASE      	=		parse_qs(
												    BeautifulSoup(res.text, """html.parser""")
												    .find("""div""", attrs={"""class""": """kCrYT"""})
												    .find("""a""")
												    .get("""href""")
												)["""url"""][0]

						webbrowser.open(link)

