



import json
import os
import shutil
import tempfile
from unittest import TestCase

from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES as DPR_VOCAB_FILES_NAMES
from transformers.models.dpr.configuration_dpr import DPRConfig
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES as BART_VOCAB_FILES_NAMES
from transformers.testing_utils import require_faiss, require_tokenizers, require_torch, slow
from transformers.utils import is_datasets_available, is_faiss_available, is_torch_available


if is_torch_available() and is_datasets_available() and is_faiss_available():
 from transformers.models.rag.configuration_rag import RagConfig
 from transformers.models.rag.tokenization_rag import RagTokenizer

@require_faiss
@require_torch
class     _A       (	__UpperCAmelCase    ):



       def 		_lowerCamelCase			(		self							:     Dict):


           '''simple docstring'''

           __a						       =				tempfile.mkdtemp()
           __a						       =				8

           # DPR tok
           __a						       =				[
               '''[UNK]''',
               '''[CLS]''',
               '''[SEP]''',
               '''[PAD]''',
               '''[MASK]''',
               '''want''',
               '''##want''',
               '''##ed''',
               '''wa''',
               '''un''',
               '''runn''',
               '''##ing''',
               ''',''',
               '''low''',
               '''lowest''',
           ]
           __a						       =				os.path.join(self.tmpdirname     ,		'''dpr_tokenizer''')
           os.makedirs(__SCREAMING_SNAKE_CASE     ,		exist_ok=__SCREAMING_SNAKE_CASE)
           __a						       =				os.path.join(__SCREAMING_SNAKE_CASE     ,		DPR_VOCAB_FILES_NAMES['''vocab_file'''])
           with open(self.vocab_file     ,		'''w'''     ,		encoding='''utf-8''') as vocab_writer:
               vocab_writer.write(''''''.join([x + '''\n''' for x in vocab_tokens]))

           # BART tok
           __a						       =				[
               '''l''',
               '''o''',
               '''w''',
               '''e''',
               '''r''',
               '''s''',
               '''t''',
               '''i''',
               '''d''',
               '''n''',
               '''\u0120''',
               '''\u0120l''',
               '''\u0120n''',
               '''\u0120lo''',
               '''\u0120low''',
               '''er''',
               '''\u0120lowest''',
               '''\u0120newer''',
               '''\u0120wider''',
               '''<unk>''',
           ]
           __a						       =				dict(zip(__SCREAMING_SNAKE_CASE     ,		range(len(__SCREAMING_SNAKE_CASE))))
           __a						       =				['''#version: 0.2''', '''\u0120 l''', '''\u0120l o''', '''\u0120lo w''', '''e r''', '''''']
           __a						       =				{'''unk_token''': '''<unk>'''}

           __a						       =				os.path.join(self.tmpdirname     ,		'''bart_tokenizer''')
           os.makedirs(__SCREAMING_SNAKE_CASE     ,		exist_ok=__SCREAMING_SNAKE_CASE)
           __a						       =				os.path.join(__SCREAMING_SNAKE_CASE     ,		BART_VOCAB_FILES_NAMES['''vocab_file'''])
           __a						       =				os.path.join(__SCREAMING_SNAKE_CASE     ,		BART_VOCAB_FILES_NAMES['''merges_file'''])
           with open(self.vocab_file     ,		'''w'''     ,		encoding='''utf-8''') as fp:
               fp.write(json.dumps(__SCREAMING_SNAKE_CASE) + '''\n''')
           with open(self.merges_file     ,		'''w'''     ,		encoding='''utf-8''') as fp:
               fp.write('''\n'''.join(__SCREAMING_SNAKE_CASE))



       def 		_lowerCamelCase			(		self							:     List[Any]):


           '''simple docstring'''

           return DPRQuestionEncoderTokenizer.from_pretrained(os.path.join(self.tmpdirname     ,		'''dpr_tokenizer'''))



       def 		_lowerCamelCase			(		self							:     Optional[int]):


           '''simple docstring'''

           return BartTokenizer.from_pretrained(os.path.join(self.tmpdirname     ,		'''bart_tokenizer'''))



       def 		_lowerCamelCase			(		self							:     List[Any]):


           '''simple docstring'''

           shutil.rmtree(self.tmpdirname)



       @require_tokenizers
       def 		_lowerCamelCase			(		self							:     List[Any]):


           '''simple docstring'''

           __a						       =				os.path.join(self.tmpdirname     ,		'''rag_tokenizer''')
           __a						       =				RagConfig(question_encoder=DPRConfig().to_dict()     ,		generator=BartConfig().to_dict())
           __a						       =				RagTokenizer(question_encoder=self.get_dpr_tokenizer()     ,		generator=self.get_bart_tokenizer())
           rag_config.save_pretrained(__SCREAMING_SNAKE_CASE)
           rag_tokenizer.save_pretrained(__SCREAMING_SNAKE_CASE)
           __a						       =				RagTokenizer.from_pretrained(__SCREAMING_SNAKE_CASE     ,		config=__SCREAMING_SNAKE_CASE)
           self.assertIsInstance(new_rag_tokenizer.question_encoder     ,		__SCREAMING_SNAKE_CASE)
           self.assertEqual(new_rag_tokenizer.question_encoder.get_vocab()     ,		rag_tokenizer.question_encoder.get_vocab())
           self.assertIsInstance(new_rag_tokenizer.generator     ,		__SCREAMING_SNAKE_CASE)
           self.assertEqual(new_rag_tokenizer.generator.get_vocab()     ,		rag_tokenizer.generator.get_vocab())



       @slow
       def 		_lowerCamelCase			(		self							:     Optional[int]):


           '''simple docstring'''

           __a						       =				RagTokenizer.from_pretrained('''facebook/rag-token-nq''')
           __a						       =				[
               '''who got the first nobel prize in physics''',
               '''when is the next deadpool movie being released''',
               '''which mode is used for short wave broadcast service''',
               '''who is the owner of reading football club''',
               '''when is the next scandal episode coming out''',
               '''when is the last time the philadelphia won the superbowl''',
               '''what is the most current adobe flash player version''',
               '''how many episodes are there in dragon ball z''',
               '''what is the first step in the evolution of the eye''',
               '''where is gall bladder situated in human body''',
               '''what is the main mineral in lithium batteries''',
               '''who is the president of usa right now''',
               '''where do the greasers live in the outsiders''',
               '''panda is a national animal of which country''',
               '''what is the name of manchester united stadium''',
           ]
           __a						       =				tokenizer(__SCREAMING_SNAKE_CASE)
           self.assertIsNotNone(__SCREAMING_SNAKE_CASE)





       @slow
       def 		_lowerCamelCase			(		self							:     List[Any]):


           '''simple docstring'''

           __a						       =				RagTokenizer.from_pretrained('''facebook/rag-sequence-nq''')
           __a						       =				[
               '''who got the first nobel prize in physics''',
               '''when is the next deadpool movie being released''',
               '''which mode is used for short wave broadcast service''',
               '''who is the owner of reading football club''',
               '''when is the next scandal episode coming out''',
               '''when is the last time the philadelphia won the superbowl''',
               '''what is the most current adobe flash player version''',
               '''how many episodes are there in dragon ball z''',
               '''what is the first step in the evolution of the eye''',
               '''where is gall bladder situated in human body''',
               '''what is the main mineral in lithium batteries''',
               '''who is the president of usa right now''',
               '''where do the greasers live in the outsiders''',
               '''panda is a national animal of which country''',
               '''what is the name of manchester united stadium''',
           ]
           __a						       =				tokenizer(__SCREAMING_SNAKE_CASE)
           self.assertIsNotNone(__SCREAMING_SNAKE_CASE)










from json import JSONDecodeError  # Workaround for requests.exceptions.JSONDecodeError

import requests





def      __snake_case	(			_UpperCAmelCase = "isbn/0140328726"				):
    __a						       =				olid.strip().strip('''/'''				)  # Remove leading/trailing whitespace & slashes
    if new_olid.count('''/'''				) != 1:
        __a						       =				f'{olid} is not a valid Open Library olid'
        raise ValueError(_UpperCAmelCase				)
    return requests.get(f'https://openlibrary.org/{new_olid}.json'				).json()





def      __snake_case	(			_UpperCAmelCase				):
    __a						       =				{
        '''title''': '''Title''',
        '''publish_date''': '''Publish date''',
        '''authors''': '''Authors''',
        '''number_of_pages''': '''Number of pages:''',
        '''first_sentence''': '''First sentence''',
        '''isbn_10''': '''ISBN (10)''',
        '''isbn_13''': '''ISBN (13)''',
    }
    __a						       =				{better_key: ol_book_data[key] for key, better_key in desired_keys.items()}
    __a						       =				[
        get_openlibrary_data(author['''key''']				)['''name'''] for author in data['''Authors''']
    ]
    __a						       =				data['''First sentence''']['''value''']
    for key, value in data.items():
        if isinstance(_UpperCAmelCase   , _UpperCAmelCase				):
            __a						       =				''', '''.join(_UpperCAmelCase				)
    return data


if __name__ == "__main__":
 import doctest

 doctest.testmod()

 while True:
  __snake_case						:List[Any]      		=     input('''\nEnter the ISBN code to search (or \'quit\' to stop): ''').strip()
  if isbn.lower() in ("", "q", "quit", "exit", "stop"):
   break

  if len(isbn) not in (10, 13) or not isbn.isdigit():
   print(f'Sorry, {isbn} is not a valid ISBN.  Please, input a valid ISBN.')
   continue

  print(f'\nSearching Open Library for ISBN: {isbn}...\n')

  try:
   __snake_case						:Optional[Any]      		=     summarize_book(get_openlibrary_data(f'isbn/{isbn}'))
   print('''\n'''.join(f'{key}: {value}' for key, value in book_summary.items()))
  except JSONDecodeError:  # Workaround for requests.exceptions.RequestException:
   print(f'Sorry, there are no results for ISBN: {isbn}.')





