

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						:   List[Any]										=    None

lowerCAmelCase						:   Dict										=    logging.get_logger(__name__)
lowerCAmelCase						:   List[str]										=    {'''vocab_file''': '''tokenizer.model''', '''tokenizer_file''': '''tokenizer.json'''}

lowerCAmelCase					,  lowerCAmelCase						:   int										=    '''[INST]''', '''[/INST]'''
lowerCAmelCase					,  lowerCAmelCase						:   int										=    '''<<SYS>>\n''', '''\n<</SYS>>\n\n'''

# fmt: off
lowerCAmelCase						:   Any										=    '''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__     (						__a		):





       '''simple docstring'''




       UpperCamelCase__ :     str				    =       VOCAB_FILES_NAMES
       UpperCamelCase__ :     List[str]				    =       LlamaTokenizer
       UpperCamelCase__ :     Optional[Any]				    =       '''left'''
       UpperCamelCase__ :     Optional[Any]				    =       ['''input_ids''', '''attention_mask''']

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

             snake_case__					=   vocab_file
             snake_case__					=   False if not self.vocab_file else True

       def UpperCAmelCase_						(						self       :						Union[str, Any]							)			->    Dict:
             snake_case__					=   self.bos_token
             snake_case__					=   self.bos_token_id

             snake_case__					=   self.eos_token
             snake_case__					=   self.eos_token_id

             snake_case__					=   f'''{(bos+':0 ') * self.add_bos_token}$A:0{(' '+eos+':0') * self.add_eos_token}'''
             snake_case__					=   f'''{single}{(' '+bos+':1') * self.add_bos_token} $B:1{(' '+eos+':1') * self.add_eos_token}'''

             snake_case__					=   []
             if self.add_bos_token:
                   special_tokens.append((bos, bos_token_id)							)
             if self.add_eos_token:
                   special_tokens.append((eos, eos_token_id)							)
             snake_case__					=   processors.TemplateProcessing(
                 single=lowerCAmelCase__    ,		pair=lowerCAmelCase__    ,		special_tokens=lowerCAmelCase__							)

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

       @property
       def UpperCAmelCase_						(						self       :						str							)			->    Optional[int]:
             return self._add_bos_token

       @add_eos_token.setter
       def UpperCAmelCase_						(						self       :						List[str]    ,		lowerCAmelCase__       :						int							)			->    Optional[int]:
             snake_case__					=   value
             self.update_post_processor()

       @add_bos_token.setter
       def UpperCAmelCase_						(						self       :						Optional[Any]    ,		lowerCAmelCase__       :						Any							)			->    str:
             snake_case__					=   value
             self.update_post_processor()

       def UpperCAmelCase_						(						self       :						Optional[Any]    ,		lowerCAmelCase__       :						str    ,		lowerCAmelCase__       :						Optional[str] = None							)			->    Tuple[str]:
             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
             snake_case__					=   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       :						Tuple    ,		lowerCAmelCase__       :						"Conversation"							)			->    Dict:
             snake_case__					=   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...)"""							)

             snake_case__					=   []
             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]:
                         snake_case__					=   (
                             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]:
                   snake_case__					=   (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









# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool


lowerCAmelCase						:   List[Any]										=    '''Here is a text containing a lot of information: \'\'\'{text}\'\'\'.

Can you answer this question about the text: \'{question}\''''
class     SCREAMING_SNAKE_CASE__     (						__a		):





       '''simple docstring'''




       UpperCamelCase__ :     int				    =       '''google/flan-t5-base'''
       UpperCamelCase__ :     int				    =       (
           '''This is a tool that answers questions related to a text. It takes two arguments named `text`, which is the '''
           '''text where to find the answer, and `question`, which is the question, and returns the answer to the question.'''
       )
       UpperCamelCase__ :     Tuple				    =       '''text_qa'''
       UpperCamelCase__ :     Tuple				    =       AutoTokenizer
       UpperCamelCase__ :     List[Any]				    =       AutoModelForSeqaSeqLM

       UpperCamelCase__ :     Optional[Any]				    =       ['''text''', '''text''']
       UpperCamelCase__ :     Any				    =       ['''text''']

       def UpperCAmelCase_						(						self       :						Tuple    ,		lowerCAmelCase__       :						str    ,		lowerCAmelCase__       :						str							)			->    List[Any]:
             snake_case__					=   QA_PROMPT.format(text=lowerCAmelCase__    ,		question=lowerCAmelCase__							)
             return self.pre_processor(lowerCAmelCase__    ,		return_tensors="""pt"""							)

       def UpperCAmelCase_						(						self       :						Optional[Any]    ,		lowerCAmelCase__       :						Dict							)			->    List[Any]:
             snake_case__					=   self.model.generate(**lowerCAmelCase__							)

             snake_case__	,			snake_case__					=   inputs["""input_ids"""].shape
             snake_case__					=   output_ids.shape[0]

             return output_ids.reshape(lowerCAmelCase__    ,		out_b // in_b    ,		*output_ids.shape[1:]							)[0][0]

       def UpperCAmelCase_						(						self       :						Union[str, Any]    ,		lowerCAmelCase__       :						Dict							)			->    List[Any]:
             return self.pre_processor.decode(lowerCAmelCase__    ,		skip_special_tokens=lowerCAmelCase__    ,		clean_up_tokenization_spaces=lowerCAmelCase__							)






