# 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 :     int          =  '''Here is a text containing a lot of information: \'\'\'{text}\'\'\'.

Can you answer this question about the text: \'{question}\''''






class 		a__						( A__ ):
					A     	=							'google/flan-t5-base'
					A     	=							(
					    '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.'
					)
					A     	=							'text_qa'
					A     	=							AutoTokenizer
					A     	=							AutoModelForSeqaSeqLM

					A     	=							['text', 'text']
					A     	=							['text']

					def     __UpperCamelCase       (   self				:	Any,_A				:	str,_A				:	str   ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		List[str]    				=   QA_PROMPT.format(text=_A,question=_A   )
							return self.pre_processor(_A,return_tensors="pt"   )

					def     __UpperCamelCase       (   self				:	Union[str, Any],_A				:	Tuple   ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		Optional[int]    				=   self.model.generate(**_A   )

							SCREAMING_SNAKE_CASE_				,   SCREAMING_SNAKE_CASE_  :		Optional[int]    				=   inputs["input_ids"].shape
							SCREAMING_SNAKE_CASE_  :		Union[str, Any]    				=   output_ids.shape[0]

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






					def     __UpperCamelCase       (   self				:	str,_A				:	Union[str, Any]   ):







							"""simple docstring"""






							return self.pre_processor.decode(_A,skip_special_tokens=_A,clean_up_tokenization_spaces=_A   )

from ..utils import DummyObject, requires_backends






class 		a__						( metaclass=A__ ):
					A     	=							['tensorflow_text']

					def __init__(   self				:	List[str],*_A				:	Optional[Any],**_A				:	int   ):







							"""simple docstring"""






							requires_backends(self,["tensorflow_text"]   )
