

"""simple docstring"""




import os
from shutil import copyfile
from typing import TYPE_CHECKING, Optional, Tuple

from tokenizers import processors

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
from ...utils.versions import require_version


if TYPE_CHECKING:
 from transformers.pipelines.conversational import Conversation

require_version("tokenizers>=0.13.3")

if is_sentencepiece_available():
 from .tokenization_llama import LlamaTokenizer
else:
 _UpperCamelCase			      =		None

_UpperCamelCase			      =		logging.get_logger(__name__)
_UpperCamelCase			      =		{"vocab_file": "tokenizer.model", "tokenizer_file": "tokenizer.json"}

_UpperCamelCase      ,      _UpperCamelCase			      =		"[INST]", "[/INST]"
_UpperCamelCase      ,      _UpperCamelCase			      =		"<<SYS>>\n", "\n<</SYS>>\n\n"

# fmt: off
_UpperCamelCase			      =		"You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your\\nanswers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure\\nthat your responses are socially unbiased and positive in nature.\n\nIf a question does not make any sense, or is not factually coherent, explain why instead of answering something not\\ncorrect. If you don't know the answer to a question, please don't share false information."







class   __lowercase				(_UpperCAmelCase			):
 _UpperCamelCase        =  VOCAB_FILES_NAMES
 _UpperCamelCase        =  LlamaTokenizer
 _UpperCamelCase        =  """left"""
 _UpperCamelCase        =  ["""input_ids""", """attention_mask"""]
 def __init__(							self				,							A_=None				,							A_=None				,							A_=False				,							A_="<unk>"				,							A_="<s>"				,							A_="</s>"				,							A_=True				,							A_=False				,							**A_				,							) ->Any:



       '''simple docstring'''





       super().__init__(
           vocab_file=A_				,							tokenizer_file=A_				,							clean_up_tokenization_spaces=A_				,							unk_token=A_				,							bos_token=A_				,							eos_token=A_				,							**A_				,							)
       __lowerCAmelCase :						List[Any] = add_bos_token
       __lowerCAmelCase :						str = add_eos_token
       self.update_post_processor()

       __lowerCAmelCase :						Optional[int] = vocab_file
       __lowerCAmelCase :						Dict = False if not self.vocab_file else True
 def      UpperCamelCase__  (							self ) ->Dict:



       '''simple docstring'''





       __lowerCAmelCase :						Union[str, Any] = self.bos_token
       __lowerCAmelCase :						Union[str, Any] = self.bos_token_id

       __lowerCAmelCase :						Optional[Any] = self.eos_token
       __lowerCAmelCase :						Tuple = self.eos_token_id

       __lowerCAmelCase :						Optional[Any] = f"""{(bos+":0 ") * self.add_bos_token}$A:0{(" "+eos+":0") * self.add_eos_token}"""
       __lowerCAmelCase :						List[Any] = f"""{single}{(" "+bos+":1") * self.add_bos_token} $B:1{(" "+eos+":1") * self.add_eos_token}"""

       __lowerCAmelCase :						Dict = []
       if self.add_bos_token:
             special_tokens.append((bos, bos_token_id) )
       if self.add_eos_token:
             special_tokens.append((eos, eos_token_id) )
       __lowerCAmelCase :						Tuple = processors.TemplateProcessing(
           single=A_				,							pair=A_				,							special_tokens=A_ )
 @property
 def      UpperCamelCase__  (							self ) ->Union[str, Any]:



       '''simple docstring'''





       return self._add_eos_token
 @property
 def      UpperCamelCase__  (							self ) ->Dict:



       '''simple docstring'''





       return self._add_bos_token
 @add_eos_token.setter
 def      UpperCamelCase__  (							self				,							A_ ) ->Optional[int]:



       '''simple docstring'''





       __lowerCAmelCase :						str = value
       self.update_post_processor()
 @add_bos_token.setter
 def      UpperCamelCase__  (							self				,							A_ ) ->Optional[Any]:



       '''simple docstring'''





       __lowerCAmelCase :						List[Any] = value
       self.update_post_processor()
 def      UpperCamelCase__  (							self				,							A_				,							A_ = None ) ->Tuple[str]:



       '''simple docstring'''





       if not self.can_save_slow_tokenizer:
             raise ValueError(
                 '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
                 '''tokenizer.''' )

       if not os.path.isdir(A_ ):
             logger.error(f"""Vocabulary path ({save_directory}) should be a directory""" )
             return
       __lowerCAmelCase :						int = os.path.join(
           A_				,							(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file'''] )

       if os.path.abspath(self.vocab_file ) != os.path.abspath(A_ ):
             copyfile(self.vocab_file				,							A_ )

       return (out_vocab_file,)





 def      UpperCamelCase__  (							self				,							A_ ) ->str:



       '''simple docstring'''





       __lowerCAmelCase :						Any = 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...)''' )

       __lowerCAmelCase :						int = []
       if len(conversation.past_user_inputs ) > 0:
             if not conversation.past_user_inputs[0].startswith(A_ ) or E_SYS not in conversation.past_user_inputs[0]:
                   __lowerCAmelCase :						Dict = (
                       B_SYS + DEFAULT_SYSTEM_PROMPT + E_SYS + conversation.past_user_inputs[0]
                   )
       elif not dialogue[0][1].startswith(A_ ) or E_SYS not in dialogue[0][1]:
             __lowerCAmelCase :						str = (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=A_ )
               + [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=A_ )
       return dialog_tokens





def 		_lowercase			(					lowercase__						):
      return "".join(chr(ord(lowercase__						) + 3_2						) if '''A''' <= char <= '''Z''' else char for char in word						)


if __name__ == "__main__":
 from doctest import testmod

 testmod()


