






"""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:
						A_     =				None

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

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

# fmt: off
A_     =				'''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 				__SCREAMING_SNAKE_CASE    (					UpperCamelCase		):
							snake_case_  =				VOCAB_FILES_NAMES
							snake_case_  =				LlamaTokenizer
							snake_case_  =				'left'
							snake_case_  =				['input_ids', 'attention_mask']


							def __init__(      self   :    List[str]      ,     snake_case   :    Optional[int]=None      ,     snake_case   :    Dict=None      ,     snake_case   :    Optional[Any]=False      ,     snake_case   :    Dict="<unk>"      ,     snake_case   :    Union[str, Any]="<s>"      ,     snake_case   :    Any="</s>"      ,     snake_case   :    Optional[int]=True      ,     snake_case   :    Any=False      ,     **snake_case   :    List[str]      ,     ):
													'''simple docstring'''





													super().__init__(
													    vocab_file=snake_case      ,     tokenizer_file=snake_case      ,     clean_up_tokenization_spaces=snake_case      ,     unk_token=snake_case      ,     bos_token=snake_case      ,     eos_token=snake_case      ,     **snake_case      ,     )
													A__    :	Dict			=	add_bos_token
													A__    :	List[str]			=	add_eos_token
													self.update_post_processor()

													A__    :	str			=	vocab_file
													A__    :	int			=	False if not self.vocab_file else True


							def     _UpperCamelCase							(      self   :    Any				):
													'''simple docstring'''





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

													A__    :	int			=	self.eos_token
													A__    :	Union[str, Any]			=	self.eos_token_id

													A__    :	Any			=	F'{(bos+":0 ") * self.add_bos_token}$A:0{(" "+eos+":0") * self.add_eos_token}'
													A__    :	Tuple			=	F'{single}{(" "+bos+":1") * self.add_bos_token} $B:1{(" "+eos+":1") * self.add_eos_token}'

													A__    :	str			=	[]
													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__    :	Tuple			=	processors.TemplateProcessing(
													    single=snake_case      ,     pair=snake_case      ,     special_tokens=snake_case				)


							@property
							def     _UpperCamelCase							(      self   :    List[str]				):
													'''simple docstring'''





													return self._add_eos_token


							@property
							def     _UpperCamelCase							(      self   :    Any				):
													'''simple docstring'''





													return self._add_bos_token


							@add_eos_token.setter
							def     _UpperCamelCase							(      self   :    Dict      ,     snake_case   :    Tuple				):
													'''simple docstring'''





													A__    :	Union[str, Any]			=	value
													self.update_post_processor()


							@add_bos_token.setter
							def     _UpperCamelCase							(      self   :    str      ,     snake_case   :    List[Any]				):
													'''simple docstring'''





													A__    :	Dict			=	value
													self.update_post_processor()


							def     _UpperCamelCase							(      self   :    Optional[Any]      ,     snake_case   :    str      ,     snake_case   :    Optional[str] = None				):
													'''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(snake_case				):
																			logger.error(F'Vocabulary path ({save_directory}) should be a directory'				)
																			return
													A__    :	Dict			=	os.path.join(
													    snake_case      ,     (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]				)

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

													return (out_vocab_file,)


							def     _UpperCamelCase							(      self   :    Dict      ,     snake_case   :    "Conversation"				):
													'''simple docstring'''





													A__    :	Union[str, 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__    :	List[Any]			=	[]
													if len(conversation.past_user_inputs				) > 0:
																			if not conversation.past_user_inputs[0].startswith(snake_case				) 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(snake_case				) or E_SYS not in dialogue[0][1]:
																			A__    :	Optional[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=snake_case				)
													        + [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=snake_case				)
													return dialog_tokens














"""simple docstring"""



import unittest

from transformers import load_tool

from .test_tools_common import ToolTesterMixin


A_     =				'''
Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot app targeted at teenagers.[2] After open-sourcing the model behind the chatbot, the company pivoted to focus on being a platform for machine learning.

In March 2021, Hugging Face raised $40 million in a Series B funding round.[3]

On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model.[4] In 2022, the workshop concluded with the announcement of BLOOM, a multilingual large language model with 176 billion parameters.[5]
'''






class 				__SCREAMING_SNAKE_CASE    (					unittest.TestCase							,		UpperCamelCase		):


							def     _UpperCamelCase							(      self   :    int				):
													'''simple docstring'''





													A__    :	Any			=	load_tool("""summarization"""				)
													self.tool.setup()
													A__    :	List[Any]			=	load_tool("""summarization"""      ,     remote=snake_case				)


							def     _UpperCamelCase							(      self   :    Any				):
													'''simple docstring'''





													A__    :	List[Any]			=	self.tool(snake_case				)
													self.assertEqual(
													    snake_case      ,     """Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf. In March 2021, Hugging Face raised $40 million in a Series B funding round. On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model. In 2022, the workshop concluded with the announcement of BLOOM."""      ,     )


							def     _UpperCamelCase							(      self   :    Optional[int]				):
													'''simple docstring'''





													A__    :	List[str]			=	self.remote_tool(snake_case				)
													self.assertEqual(
													    snake_case      ,     """Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf. In March 2021, Hugging Face raised $40 million in a Series B funding round. On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model. In 2022, the workshop concluded with the announcement of BLOOM."""      ,     )


							def     _UpperCamelCase							(      self   :    Dict				):
													'''simple docstring'''





													A__    :	List[Any]			=	self.tool(text=snake_case				)
													self.assertEqual(
													    snake_case      ,     """Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf. In March 2021, Hugging Face raised $40 million in a Series B funding round. On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model. In 2022, the workshop concluded with the announcement of BLOOM."""      ,     )


							def     _UpperCamelCase							(      self   :    Union[str, Any]				):
													'''simple docstring'''





													A__    :	Optional[int]			=	self.remote_tool(text=snake_case				)
													self.assertEqual(
													    snake_case      ,     """Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf. In March 2021, Hugging Face raised $40 million in a Series B funding round. On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model. In 2022, the workshop concluded with the announcement of BLOOM."""      ,     )






