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:
     __snake_case         =     None

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

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

# fmt: off
__snake_case         =     '''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       __snake_case (  lowerCamelCase__ ):
 __lowerCamelCase     : Optional[int] 	=   VOCAB_FILES_NAMES
 __lowerCamelCase     : List[Any] 	=   LlamaTokenizer
 __lowerCamelCase     : List[Any] 	=   """left"""
 __lowerCamelCase     : Optional[int] 	=   ["""input_ids""", """attention_mask"""]
 def __init__(	self		, snake_case__=None		, snake_case__=None		, snake_case__=False		, snake_case__="<unk>"		, snake_case__="<s>"		, snake_case__="</s>"		, snake_case__=True		, snake_case__=False		, **snake_case__		, )						->				Union[str, Any]:
       '''simple docstring'''





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

       UpperCAmelCase     :			Any     	=vocab_file
       UpperCAmelCase     :			Optional[int]     	=False if not self.vocab_file else True
 def 						UpperCAmelCase__							(	self    )						->				Any:
       '''simple docstring'''





       UpperCAmelCase     :			Optional[Any]     	=self.bos_token
       UpperCAmelCase     :			Dict     	=self.bos_token_id

       UpperCAmelCase     :			Optional[Any]     	=self.eos_token
       UpperCAmelCase     :			Any     	=self.eos_token_id

       UpperCAmelCase     :			Optional[int]     	=f'''{(bos+':0 ') * self.add_bos_token}$A:0{(' '+eos+':0') * self.add_eos_token}'''
       UpperCAmelCase     :			str     	=f'''{single}{(' '+bos+':1') * self.add_bos_token} $B:1{(' '+eos+':1') * self.add_eos_token}'''

       UpperCAmelCase     :			Union[str, Any]     	=[]
       if self.add_bos_token:
             special_tokens.append((bos, bos_token_id)    )
       if self.add_eos_token:
             special_tokens.append((eos, eos_token_id)    )
       UpperCAmelCase     :			Union[str, Any]     	=processors.TemplateProcessing(
           single=lowerCamelCase__		, pair=lowerCamelCase__		, special_tokens=lowerCamelCase__    )
 @property
 def 						UpperCAmelCase__							(	self    )						->				Optional[Any]:
       '''simple docstring'''





       return self._add_eos_token
 @property
 def 						UpperCAmelCase__							(	self    )						->				Optional[Any]:
       '''simple docstring'''





       return self._add_bos_token
 @add_eos_token.setter
 def 						UpperCAmelCase__							(	self		, snake_case__    )						->				List[Any]:
       '''simple docstring'''





       UpperCAmelCase     :			int     	=value
       self.update_post_processor()
 @add_bos_token.setter
 def 						UpperCAmelCase__							(	self		, snake_case__    )						->				int:
       '''simple docstring'''





       UpperCAmelCase     :			List[Any]     	=value
       self.update_post_processor()
 def 						UpperCAmelCase__							(	self		, snake_case__		, snake_case__ = None    )						->				List[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(lowerCamelCase__    ):
             logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''    )
             return
       UpperCAmelCase     :			str     	=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__    ):
             copyfile(self.vocab_file		, lowerCamelCase__    )

       return (out_vocab_file,)






 def 						UpperCAmelCase__							(	self		, snake_case__    )						->				Optional[Any]:
       '''simple docstring'''





       UpperCAmelCase     :			Tuple     	=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...)'''    )

       UpperCAmelCase     :			Dict     	=[]
       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]:
                   UpperCAmelCase     :			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]:
             UpperCAmelCase     :			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








from typing import Callable






def 				A	(			a_   )	->		List[str]:

					def wrapper(a_   ):
										__UpperCamelCase :   Dict									=function_with_docstring.__doc__
										return target_function

					return wrapper

