


import os
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple

import sentencepiece as spm

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


if TYPE_CHECKING:
       from transformers.pipelines.conversational import Conversation

__lowerCamelCase   	=  logging.get_logger(__name__)

__lowerCamelCase   	=  {'''vocab_file''': '''tokenizer.model'''}

__lowerCamelCase   	=  {
    '''vocab_file''': {
        '''hf-internal-testing/llama-tokenizer''': '''https://huggingface.co/hf-internal-testing/llama-tokenizer/resolve/main/tokenizer.model''',
    },
    '''tokenizer_file''': {
        '''hf-internal-testing/llama-tokenizer''': '''https://huggingface.co/hf-internal-testing/llama-tokenizer/resolve/main/tokenizer_config.json''',
    },
}
__lowerCamelCase   	=  {
    '''hf-internal-testing/llama-tokenizer''': 2048,
}
__lowerCamelCase   	=  '''▁'''

__lowerCamelCase	,							__lowerCamelCase   	=  '''[INST]''', '''[/INST]'''
__lowerCamelCase	,							__lowerCamelCase   	=  '''<<SYS>>\n''', '''\n<</SYS>>\n\n'''

# fmt: off
__lowerCamelCase   	=  '''You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your\
answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure\
that your responses are socially unbiased and positive in nature.

If a question does not make any sense, or is not factually coherent, explain why instead of answering something not\
correct. If you don\'t know the answer to a question, please don\'t share false information.'''


class 	a__						(    lowerCAmelCase_     ):
       lowerCamelCase__:  List[str]				     =  VOCAB_FILES_NAMES
       lowerCamelCase__:  List[str]				     =  PRETRAINED_VOCAB_FILES_MAP
       lowerCamelCase__:  int				     =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       lowerCamelCase__:  str				     =  ["""input_ids""", """attention_mask"""]

       def __init__( self   :  Union[str, Any]   ,				lowerCamelCase_   :  Tuple   ,				lowerCamelCase_   :  List[str]="<unk>"   ,				lowerCamelCase_   :  Optional[int]="<s>"   ,				lowerCamelCase_   :  Any="</s>"   ,				lowerCamelCase_   :  Any=None   ,				lowerCamelCase_   :  Optional[Dict[str, Any]] = None   ,				lowerCamelCase_   :  Any=True   ,				lowerCamelCase_   :  List[str]=False   ,				lowerCamelCase_   :  List[str]=False   ,				lowerCamelCase_   :  List[str]=True   ,				**lowerCamelCase_   :  Union[str, Any]   ,				):
            a_     :  str				      =     {} if sp_model_kwargs is None else sp_model_kwargs
            a_     :  Dict				      =     AddedToken(lowerCamelCase_   ,				lstrip=lowerCamelCase_   ,				rstrip=lowerCamelCase_     ) if isinstance(lowerCamelCase_   ,				lowerCamelCase_     ) else bos_token
            a_     :  List[Any]				      =     AddedToken(lowerCamelCase_   ,				lstrip=lowerCamelCase_   ,				rstrip=lowerCamelCase_     ) if isinstance(lowerCamelCase_   ,				lowerCamelCase_     ) else eos_token
            a_     :  Dict				      =     AddedToken(lowerCamelCase_   ,				lstrip=lowerCamelCase_   ,				rstrip=lowerCamelCase_     ) if isinstance(lowerCamelCase_   ,				lowerCamelCase_     ) else unk_token
            a_     :  Any				      =     AddedToken(lowerCamelCase_   ,				lstrip=lowerCamelCase_   ,				rstrip=lowerCamelCase_     ) if isinstance(lowerCamelCase_   ,				lowerCamelCase_     ) else pad_token
            super().__init__(
                bos_token=lowerCamelCase_   ,				eos_token=lowerCamelCase_   ,				unk_token=lowerCamelCase_   ,				pad_token=lowerCamelCase_   ,				add_bos_token=lowerCamelCase_   ,				add_eos_token=lowerCamelCase_   ,				sp_model_kwargs=self.sp_model_kwargs   ,				clean_up_tokenization_spaces=lowerCamelCase_   ,				legacy=lowerCamelCase_   ,				**lowerCamelCase_   ,				)
            if legacy:
                 logger.warning_once(
                     F'''You are using the legacy behaviour of the {self.__class__}. This means that tokens that come after special tokens will not be properly handled. We recommend you to'''
                     """ read the related pull request available at https://github.com/huggingface/transformers/pull/24565"""     )
            a_     :  Union[str, Any]				      =     legacy
            a_     :  Optional[Any]				      =     vocab_file
            a_     :  Dict				      =     add_bos_token
            a_     :  Tuple				      =     add_eos_token
            a_     :  Dict				      =     spm.SentencePieceProcessor(**self.sp_model_kwargs     )
            self.sp_model.Load(lowerCamelCase_     )

       def __getstate__( self   :  Union[str, Any]     ):
            a_     :  int				      =     self.__dict__.copy()
            a_     :  Optional[Any]				      =     None
            a_     :  List[str]				      =     self.sp_model.serialized_model_proto()
            return state

       def __setstate__( self   :  Any   ,				lowerCamelCase_   :  str     ):
            a_     :  Tuple				      =     d
            a_     :  int				      =     spm.SentencePieceProcessor(**self.sp_model_kwargs     )
            self.sp_model.LoadFromSerializedProto(self.sp_model_proto     )

       @property
       def     UpperCAmelCase( self   :  Dict     ):
            return self.sp_model.get_piece_size()

       def     UpperCAmelCase( self   :  Optional[Any]     ):
            a_     :  Union[str, Any]				      =     {self.convert_ids_to_tokens(lowerCamelCase_     ): i for i in range(self.vocab_size     )}
            vocab.update(self.added_tokens_encoder     )
            return vocab

       def     UpperCAmelCase( self   :  int   ,				lowerCamelCase_   :  Any   ,				**lowerCamelCase_   :  Dict     ):
            # Replace the SPIECE_UNDERLINE with a space to make sure SPIECE_UNDERLINE is only used at
            # the beginning of the text
            if not self.legacy:
                 a_     :  Union[str, Any]				      =     SPIECE_UNDERLINE + text.replace(lowerCamelCase_   ,				""" """     )
            return super().tokenize(lowerCamelCase_   ,				**lowerCamelCase_     )

       def     UpperCAmelCase( self   :  int   ,				lowerCamelCase_   :  List[Any]     ):
            if not self.legacy:
                 a_     :  List[Any]				      =     text.startswith(lowerCamelCase_     )
                 if is_first:
                      a_     :  Optional[int]				      =     text[1:]

            a_     :  Tuple				      =     self.sp_model.encode(lowerCamelCase_   ,				out_type=lowerCamelCase_     )

            if not self.legacy and not is_first and not text.startswith(""" """     ) and tokens[0].startswith(lowerCamelCase_     ):
                 a_     :  Tuple				      =     ([tokens[0][1:]] if len(tokens[0]     ) > 1 else []) + tokens[1:]
            return tokens

       def     UpperCAmelCase( self   :  int   ,				lowerCamelCase_   :  List[str]     ):
            return self.sp_model.piece_to_id(lowerCamelCase_     )

       def     UpperCAmelCase( self   :  Dict   ,				lowerCamelCase_   :  Tuple     ):
            a_     :  int				      =     self.sp_model.IdToPiece(lowerCamelCase_     )
            return token

       def     UpperCAmelCase( self   :  Dict   ,				lowerCamelCase_   :  List[str]     ):
            a_     :  Optional[int]				      =     []
            a_     :  str				      =     """"""
            a_     :  Dict				      =     False
            for i, token in enumerate(lowerCamelCase_     ):
                 # make sure that special tokens are not decoded using sentencepiece model
                 if token in self.all_special_tokens:
                      if not prev_is_special and i != 0:
                           out_string += " "
                      out_string += self.sp_model.decode(lowerCamelCase_     ) + token
                      a_     :  int				      =     True
                      a_     :  str				      =     []
                 else:
                      current_sub_tokens.append(lowerCamelCase_     )
                      a_     :  Tuple				      =     False
            out_string += self.sp_model.decode(lowerCamelCase_     )
            return out_string

       def     UpperCAmelCase( self   :  List[Any]   ,				lowerCamelCase_   :  str   ,				lowerCamelCase_   :  Optional[str] = None     ):
            if not os.path.isdir(lowerCamelCase_     ):
                 logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''     )
                 return
            a_     :  List[Any]				      =     os.path.join(
                lowerCamelCase_   ,				(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]     )

            if os.path.abspath(self.vocab_file     ) != os.path.abspath(lowerCamelCase_     ) and os.path.isfile(self.vocab_file     ):
                 copyfile(self.vocab_file   ,				lowerCamelCase_     )
            elif not os.path.isfile(self.vocab_file     ):
                 with open(lowerCamelCase_   ,				"""wb"""     ) as fi:
                      a_     :  Optional[Any]				      =     self.sp_model.serialized_model_proto()
                      fi.write(lowerCamelCase_     )

            return (out_vocab_file,)

       def     UpperCAmelCase( self   :  Tuple   ,				lowerCamelCase_   :  List[str]   ,				lowerCamelCase_   :  Optional[Any]=None     ):
            a_     :  Dict				      =     [self.bos_token_id] if self.add_bos_token else []
            a_     :  Any				      =     [self.eos_token_id] if self.add_eos_token else []

            a_     :  List[Any]				      =     bos_token_id + token_ids_a + eos_token_id

            if token_ids_a is not None:
                 a_     :  List[str]				      =     output + bos_token_id + token_ids_a + eos_token_id

            return output

       def     UpperCAmelCase( self   :  Optional[int]   ,				lowerCamelCase_   :  List[int]   ,				lowerCamelCase_   :  Optional[List[int]] = None   ,				lowerCamelCase_   :  bool = False     ):
            if already_has_special_tokens:
                 return super().get_special_tokens_mask(
                     token_ids_a=lowerCamelCase_   ,				token_ids_a=lowerCamelCase_   ,				already_has_special_tokens=lowerCamelCase_     )

            a_     :  Any				      =     [1] if self.add_bos_token else []
            a_     :  Any				      =     [1] if self.add_eos_token else []

            if token_ids_a is None:
                 return bos_token_id + ([0] * len(lowerCamelCase_     )) + eos_token_id
            return (
                bos_token_id
                + ([0] * len(lowerCamelCase_     ))
                + eos_token_id
                + bos_token_id
                + ([0] * len(lowerCamelCase_     ))
                + eos_token_id
            )

       def     UpperCAmelCase( self   :  Optional[int]   ,				lowerCamelCase_   :  List[int]   ,				lowerCamelCase_   :  Optional[List[int]] = None     ):
            a_     :  str				      =     [self.bos_token_id] if self.add_bos_token else []
            a_     :  Dict				      =     [self.eos_token_id] if self.add_eos_token else []

            a_     :  List[Any]				      =     [0] * len(bos_token_id + token_ids_a + eos_token_id     )

            if token_ids_a is not None:
                 output += [1] * len(bos_token_id + token_ids_a + eos_token_id     )

            return output

       def     UpperCAmelCase( self   :  int   ,				lowerCamelCase_   :  "Conversation"     ):
            a_     :  int				      =     list(conversation.iter_texts()     )
            if not all([is_user for is_user, msg in dialogue[::2]]     ) or not all(
                [not is_user for is_user, msg in dialogue[1::2]]     ):
                 raise ValueError(
                     """The model only supports 'user' and 'assistant' roles, starting with user and alternating (u/a/u/a/u...)"""     )

            a_     :  List[int]				      =     []
            if len(conversation.past_user_inputs     ) > 0:
                 if not conversation.past_user_inputs[0].startswith(lowerCamelCase_     ) or E_SYS not in conversation.past_user_inputs[0]:
                      a_     :  Optional[int]				      =     (
                          B_SYS + DEFAULT_SYSTEM_PROMPT + E_SYS + conversation.past_user_inputs[0]
                      )
            elif not dialogue[0][1].startswith(lowerCamelCase_     ) or E_SYS not in dialogue[0][1]:
                 a_     :  Optional[Any]				      =     (dialogue[0][0], B_SYS + DEFAULT_SYSTEM_PROMPT + E_SYS + dialogue[0][1])

            dialog_tokens += sum(
                [
                    [self.bos_token_id]
                    + self.encode(
                        F'''{B_INST} {(prompt[1]).strip()} {E_INST} {(answer[1]).strip()} '''   ,				add_special_tokens=lowerCamelCase_     )
                    + [self.eos_token_id]
                    for prompt, answer in zip(dialogue[::2]   ,				dialogue[1::2]     )
                ]   ,				[]   ,				)
            if not (dialogue[-1][0]):
                 raise ValueError(F'''Last message must be from user, got {dialogue[-1]["role"]}'''     )
            dialog_tokens += [self.bos_token_id] + self.encode(
                F'''{B_INST} {(dialogue[-1][1]).strip()} {E_INST}'''   ,				add_special_tokens=lowerCamelCase_     )
            return dialog_tokens











"""simple docstring"""


import json

import requests

from .fetch_github_info import AUTHENTICATED_USER_ENDPOINT, fetch_github_info




def      snake_case    (A_ :Union[str, Any] ):







  '''simple docstring'''

  class 		snake_case    :





      def __init__(				self      :   Tuple							,						A      :   Dict     ):


        '''simple docstring'''




        assert isinstance(A							,						(bytes, str)     )
        a	:     Union[str, Any]							=  content





      def 							lowerCamelCase__ (				self      :   str     ):


        '''simple docstring'''




        return json.loads(self.content     )

  def mock_response(*A_ :Union[str, Any]      ,     **A_ :Tuple ):
    assert args[0] == AUTHENTICATED_USER_ENDPOINT
    assert "Authorization" in kwargs["headers"]
    assert kwargs["headers"]["Authorization"].startswith('token ' )
    assert "Accept" in kwargs["headers"]
    return FakeResponse(B'{"login":"test","id":1}' )

  monkeypatch.setattr(A_      ,     'get'      ,     A_ )
  a	:     List[str]							=  fetch_github_info('token' )
  assert result["login"] == "test"
  assert result["id"] == 1




