


'''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:
    lowerCAmelCase__   	=				None

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

lowerCAmelCase__   	=				'[INST]', '[/INST]'
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\\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   lowerCAmelCase__ (       lowercase_):




     '''simple docstring'''
     __SCREAMING_SNAKE_CASE						    =				VOCAB_FILES_NAMES
     __SCREAMING_SNAKE_CASE						    =				LlamaTokenizer
     __SCREAMING_SNAKE_CASE						    =				"""left"""
     __SCREAMING_SNAKE_CASE						    =				["""input_ids""", """attention_mask"""]


     def __init__(		self				,		__lowerCamelCase=None				,		__lowerCamelCase=None				,		__lowerCamelCase=False				,		__lowerCamelCase="<unk>"				,		__lowerCamelCase="<s>"				,		__lowerCamelCase="</s>"				,		__lowerCamelCase=True				,		__lowerCamelCase=False				,		**__lowerCamelCase				,		)    ->       Union[str, Any]:
            super().__init__(
                vocab_file=__lowerCamelCase				,		tokenizer_file=__lowerCamelCase				,		clean_up_tokenization_spaces=__lowerCamelCase				,		unk_token=__lowerCamelCase				,		bos_token=__lowerCamelCase				,		eos_token=__lowerCamelCase				,		**__lowerCamelCase				,		)
            _A   : Optional[int]       					=				add_bos_token
            _A   : str       					=				add_eos_token
            self.update_post_processor()

            _A   : Tuple       					=				vocab_file
            _A   : List[str]       					=				False if not self.vocab_file else True


     def 				_lowerCamelCase				(		self)    ->       Any:
            _A   : Tuple       					=				self.bos_token
            _A   : int       					=				self.bos_token_id

            _A   : Optional[int]       					=				self.eos_token
            _A   : Any       					=				self.eos_token_id

            _A   : Union[str, Any]       					=				F"{(bos+':0 ') * self.add_bos_token}$A:0{(' '+eos+':0') * self.add_eos_token}"
            _A   : Any       					=				F"{single}{(' '+bos+':1') * self.add_bos_token} $B:1{(' '+eos+':1') * self.add_eos_token}"

            _A   : Optional[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))
            _A   : List[str]       					=				processors.TemplateProcessing(
                single=__lowerCamelCase				,		pair=__lowerCamelCase				,		special_tokens=__lowerCamelCase)


     @property
     def 				_lowerCamelCase				(		self)    ->       List[str]:
            return self._add_eos_token


     @property
     def 				_lowerCamelCase				(		self)    ->       Any:
            return self._add_bos_token


     @add_eos_token.setter
     def 				_lowerCamelCase				(		self				,		__lowerCamelCase)    ->       Union[str, Any]:
            _A   : Dict       					=				value
            self.update_post_processor()


     @add_bos_token.setter
     def 				_lowerCamelCase				(		self				,		__lowerCamelCase)    ->       Any:
            _A   : Any       					=				value
            self.update_post_processor()


     def 				_lowerCamelCase				(		self				,		__lowerCamelCase				,		__lowerCamelCase = None)    ->       Tuple:







            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
            _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):
                   copyfile(self.vocab_file				,		__lowerCamelCase)

            return (out_vocab_file,)


     def 				_lowerCamelCase				(		self				,		__lowerCamelCase)    ->       Union[str, Any]:
            _A   : Optional[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...)")

            _A   : str       					=				[]
            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   : List[str]       					=				(
                              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   : int       					=				(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




lowerCAmelCase__   	=				'\n# Transformers installation\n! pip install transformers datasets evaluate\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'

lowerCAmelCase__   	=				[{'type': 'code', 'content': INSTALL_CONTENT}]
lowerCAmelCase__   	=				{
    '{processor_class}': 'FakeProcessorClass',
    '{model_class}': 'FakeModelClass',
    '{object_class}': 'FakeObjectClass',
}
