



import requests
from bsa import BeautifulSoup

def      lowerCAmelCase_					(  _lowercase    :       str						,       _lowercase    :       dict)							->	str:







			"""simple docstring"""
			a__       :						Optional[int]							=     BeautifulSoup(requests.get(_lowercase						,       params=_lowercase).content						,       """html.parser""")
			a__       :						Dict							=     soup.find("""div"""						,       attrs={"""class""": """gs_ri"""})
			a__       :						List[str]							=     div.find("""div"""						,       attrs={"""class""": """gs_fl"""}).find_all("""a""")
			return anchors[2].get_text()


if __name__ == "__main__":
		_lowercase		:				Any      		={
		    "title": (
		        "Precisely geometry controlled microsupercapacitors for ultrahigh areal "
		        "capacitance, volumetric capacitance, and energy density"
		    ),
		    "journal": "Chem. Mater.",
		    "volume": 30,
		    "pages": "3979-3990",
		    "year": 2018,
		    "hl": "en",
		}
		print(get_citation("https://scholar.google.com/scholar_lookup", params=params))









import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


if TYPE_CHECKING:
		from transformers.pipelines.conversational import Conversation

_lowercase		:				List[str]      		=logging.get_logger(__name__)


_lowercase		:				List[str]      		={
    "vocab_file": "vocab.json",
    "merges_file": "merges.txt",
    "tokenizer_config_file": "tokenizer_config.json",
}

_lowercase		:				Optional[Any]      		={
    "vocab_file": {"facebook/blenderbot-3B": "https://huggingface.co/facebook/blenderbot-3B/resolve/main/vocab.json"},
    "merges_file": {"facebook/blenderbot-3B": "https://huggingface.co/facebook/blenderbot-3B/resolve/main/merges.txt"},
    "tokenizer_config_file": {
        "facebook/blenderbot-3B": "https://huggingface.co/facebook/blenderbot-3B/resolve/main/tokenizer_config.json"
    },
}

_lowercase		:				int      		={"facebook/blenderbot-3B": 128}

@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def      lowerCAmelCase_					(  )							->	Optional[int]:







			"""simple docstring"""
			a__       :						List[str]							=  (
			    list(range(ord("""!""")						,       ord("""~""") + 1)) + list(range(ord("""¡""")						,       ord("""¬""") + 1)) + list(range(ord("""®""")						,       ord("""ÿ""") + 1))
			)
			a__       :						Optional[Any]							=  bs[:]
			a__       :						List[Any]							=  0
			for b in range(2**8):
						if b not in bs:
									bs.append(_lowercase)
									cs.append(2**8 + n)
									n += 1
			a__       :						Tuple							=  [chr(_lowercase) for n in cs]
			return dict(zip(_lowercase						,       _lowercase))

def      lowerCAmelCase_					(  _lowercase    :       Tuple)							->	List[str]:







			"""simple docstring"""
			a__       :						int							=  set()
			a__       :						Tuple							=  word[0]
			for char in word[1:]:
						pairs.add((prev_char, char))
						a__       :						Any							=  char
			return pairs





class        snake_case__    (A__		):







						"""simple docstring"""




						__lowerCAmelCase					:str      =					VOCAB_FILES_NAMES
						__lowerCAmelCase					:int      =					PRETRAINED_VOCAB_FILES_MAP
						__lowerCAmelCase					:int      =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						__lowerCAmelCase					:Optional[Any]      =					["input_ids", "attention_mask"]

						def __init__(       self ,       __lowercase ,       __lowercase ,       __lowercase="replace" ,       __lowercase="<s>" ,       __lowercase="</s>" ,       __lowercase="</s>" ,       __lowercase="<s>" ,       __lowercase="<unk>" ,       __lowercase="<pad>" ,       __lowercase="<mask>" ,       __lowercase=False ,       **__lowercase ,       ) ->				List[Any]:
									"""simple docstring"""




									a__       :						Any							=  AddedToken(__lowercase ,       lstrip=__lowercase ,       rstrip=__lowercase  ) if isinstance(__lowercase ,       __lowercase  ) else bos_token
									a__       :						Optional[Any]							=  AddedToken(__lowercase ,       lstrip=__lowercase ,       rstrip=__lowercase  ) if isinstance(__lowercase ,       __lowercase  ) else eos_token
									a__       :						Tuple							=  AddedToken(__lowercase ,       lstrip=__lowercase ,       rstrip=__lowercase  ) if isinstance(__lowercase ,       __lowercase  ) else sep_token
									a__       :						Any							=  AddedToken(__lowercase ,       lstrip=__lowercase ,       rstrip=__lowercase  ) if isinstance(__lowercase ,       __lowercase  ) else cls_token
									a__       :						List[Any]							=  AddedToken(__lowercase ,       lstrip=__lowercase ,       rstrip=__lowercase  ) if isinstance(__lowercase ,       __lowercase  ) else unk_token
									a__       :						str							=  AddedToken(__lowercase ,       lstrip=__lowercase ,       rstrip=__lowercase  ) if isinstance(__lowercase ,       __lowercase  ) else pad_token

									# Mask token behave like a normal word, i.e. include the space before it
									a__       :						List[str]							=  AddedToken(__lowercase ,       lstrip=__lowercase ,       rstrip=__lowercase  ) if isinstance(__lowercase ,       __lowercase  ) else mask_token

									super().__init__(
									    errors=__lowercase ,       bos_token=__lowercase ,       eos_token=__lowercase ,       unk_token=__lowercase ,       sep_token=__lowercase ,       cls_token=__lowercase ,       pad_token=__lowercase ,       mask_token=__lowercase ,       add_prefix_space=__lowercase ,       **__lowercase ,       )

									with open(__lowercase ,       encoding="""utf-8"""  ) as vocab_handle:
												a__       :						str							=  json.load(__lowercase  )
									a__       :						Dict							=  {v: k for k, v in self.encoder.items()}
									a__       :						Any							=  errors  # how to handle errors in decoding
									a__       :						Union[str, Any]							=  bytes_to_unicode()
									a__       :						Optional[Any]							=  {v: k for k, v in self.byte_encoder.items()}
									with open(__lowercase ,       encoding="""utf-8"""  ) as merges_handle:
												a__       :						List[Any]							=  merges_handle.read().split("""\n"""  )[1:-1]
									a__       :						Union[str, Any]							=  [tuple(merge.split()  ) for merge in bpe_merges]
									a__       :						str							=  dict(zip(__lowercase ,       range(len(__lowercase  )  )  )  )
									a__       :						Optional[Any]							=  {}
									a__       :						Optional[Any]							=  add_prefix_space

									# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
									a__       :						Union[str, Any]							=  re.compile(r"""'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"""  )

						@property
						# Copied from transformers.models.roberta.tokenization_roberta.RobertaTokenizer.vocab_size with Roberta->Blenderbot, RoBERTa->Blenderbot
						def 							SCREAMING_SNAKE_CASE__(       self  ) ->				Any:
									"""simple docstring"""




									return len(self.encoder  )

						def 							SCREAMING_SNAKE_CASE__(       self  ) ->				Dict:
									"""simple docstring"""




									return dict(self.encoder ,       **self.added_tokens_encoder  )

						def 							SCREAMING_SNAKE_CASE__(       self ,       __lowercase  ) ->				Tuple:
									"""simple docstring"""




									if token in self.cache:
												return self.cache[token]
									a__       :						List[Any]							=  tuple(__lowercase  )
									a__       :						Optional[int]							=  get_pairs(__lowercase  )

									if not pairs:
												return token

									while True:
												a__       :						List[Any]							=  min(__lowercase ,       key=lambda __lowercase  : self.bpe_ranks.get(__lowercase ,       float("""inf"""  )  )  )
												if bigram not in self.bpe_ranks:
															break
												a__	,						a__       :						Dict							=  bigram
												a__       :						List[Any]							=  []
												a__       :						int							=  0
												while i < len(__lowercase  ):
															try:
																		a__       :						str							=  word.index(__lowercase ,       __lowercase  )
															except ValueError:
																		new_word.extend(word[i:]  )
																		break
															else:
																		new_word.extend(word[i:j]  )
																		a__       :						Optional[int]							=  j

															if word[i] == first and i < len(__lowercase  ) - 1 and word[i + 1] == second:
																		new_word.append(first + second  )
																		i += 2
															else:
																		new_word.append(word[i]  )
																		i += 1
												a__       :						List[Any]							=  tuple(__lowercase  )
												a__       :						Any							=  new_word
												if len(__lowercase  ) == 1:
															break
												else:
															a__       :						List[Any]							=  get_pairs(__lowercase  )
									a__       :						Optional[Any]							=  """ """.join(__lowercase  )
									a__       :						Tuple							=  word
									return word

						def 							SCREAMING_SNAKE_CASE__(       self ,       __lowercase  ) ->				Union[str, Any]:
									"""simple docstring"""




									a__       :						int							=  []
									for token in re.findall(self.pat ,       __lowercase  ):
												a__       :						List[Any]							=  """""".join(
												    self.byte_encoder[b] for b in token.encode("""utf-8"""  )  )  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
												bpe_tokens.extend(bpe_token for bpe_token in self.bpe(__lowercase  ).split(""" """  )  )
									return bpe_tokens

						def 							SCREAMING_SNAKE_CASE__(       self ,       __lowercase  ) ->				List[Any]:
									"""simple docstring"""




									return self.encoder.get(__lowercase ,       self.encoder.get(self.unk_token  )  )

						def 							SCREAMING_SNAKE_CASE__(       self ,       __lowercase  ) ->				Tuple:
									"""simple docstring"""




									return self.decoder.get(__lowercase  )

						def 							SCREAMING_SNAKE_CASE__(       self ,       __lowercase  ) ->				int:
									"""simple docstring"""




									a__       :						Union[str, Any]							=  """""".join(__lowercase  )
									a__       :						Tuple							=  bytearray([self.byte_decoder[c] for c in text]  ).decode("""utf-8""" ,       errors=self.errors  )
									return text

						def 							SCREAMING_SNAKE_CASE__(       self ,       __lowercase ,       __lowercase = None  ) ->				Tuple[str]:
									"""simple docstring"""




									if not os.path.isdir(__lowercase  ):
												logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''  )
												return
									a__       :						int							=  os.path.join(
									    __lowercase ,       (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]  )
									a__       :						Optional[Any]							=  os.path.join(
									    __lowercase ,       (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""merges_file"""]  )

									with open(__lowercase ,       """w""" ,       encoding="""utf-8"""  ) as f:
												f.write(json.dumps(self.encoder ,       indent=2 ,       sort_keys=__lowercase ,       ensure_ascii=__lowercase  ) + """\n"""  )

									a__       :						str							=  0
									with open(__lowercase ,       """w""" ,       encoding="""utf-8"""  ) as writer:
												writer.write("""#version: 0.2\n"""  )
												for bpe_tokens, token_index in sorted(self.bpe_ranks.items() ,       key=lambda __lowercase  : kv[1]  ):
															if index != token_index:
																		logger.warning(
																		    F'''Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'''
																		    """ Please check that the tokenizer is not corrupted!"""  )
																		a__       :						Tuple							=  token_index
															writer.write(""" """.join(__lowercase  ) + """\n"""  )
															index += 1

									return vocab_file, merge_file

						def 							SCREAMING_SNAKE_CASE__(       self ,       __lowercase ,       __lowercase = None ,       __lowercase = False  ) ->				List[int]:
									"""simple docstring"""




									if already_has_special_tokens:
												return super().get_special_tokens_mask(
												    token_ids_a=__lowercase ,       token_ids_a=__lowercase ,       already_has_special_tokens=__lowercase  )

									if token_ids_a is None:
												return [1] + ([0] * len(__lowercase  )) + [1]
									return [1] + ([0] * len(__lowercase  )) + [1, 1] + ([0] * len(__lowercase  )) + [1]

						def 							SCREAMING_SNAKE_CASE__(       self ,       __lowercase ,       __lowercase = None  ) ->				List[int]:
									"""simple docstring"""




									a__       :						Any							=  [self.sep_token_id]
									a__       :						List[Any]							=  [self.cls_token_id]

									if token_ids_a is None:
												return len(cls + token_ids_a + sep  ) * [0]
									return len(cls + token_ids_a + sep + sep + token_ids_a + sep  ) * [0]

						def 							SCREAMING_SNAKE_CASE__(       self ,       __lowercase ,       __lowercase=False ,       **__lowercase  ) ->				int:
									"""simple docstring"""




									a__       :						Tuple							=  kwargs.pop("""add_prefix_space""" ,       self.add_prefix_space  )
									if (is_split_into_words or add_prefix_space) and (len(__lowercase  ) > 0 and not text[0].isspace()):
												a__       :						Union[str, Any]							=  """ """ + text
									return (text, kwargs)

						def 							SCREAMING_SNAKE_CASE__(       self ,       __lowercase ,       __lowercase = None  ) ->				List[str]:
									"""simple docstring"""




									return token_ids_a + [self.eos_token_id]

						def 							SCREAMING_SNAKE_CASE__(       self ,       __lowercase  ) ->				List[int]:
									"""simple docstring"""




									a__       :						List[Any]							=  []
									for is_user, text in conversation.iter_texts():
												if is_user:
															# We need to space prefix as it's being done within blenderbot
															inputs.append(""" """ + text  )
												else:
															# Generated responses should contain them already.
															inputs.append(__lowercase  )

									a__       :						Optional[int]							=  """  """.join(__lowercase  )
									a__       :						Any							=  self.encode(__lowercase  )
									if len(__lowercase  ) > self.model_max_length:
												a__       :						List[str]							=  input_ids[-self.model_max_length :]
												logger.warning(F'''Trimmed input from conversation as it was longer than {self.model_max_length} tokens.'''  )
									return input_ids




