

# 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


a_         =      'Here is a text containing a lot of information: \'\'\'{text}\'\'\'.\n\nCan you answer this question about the text: \'{question}\''






class _UpperCamelCase							(							__A				):
			'''simple docstring'''







			lowerCamelCase__          ='google/flan-t5-base'
			lowerCamelCase__          =(
			    '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.'
			)
			lowerCamelCase__          ='text_qa'
			lowerCamelCase__          =AutoTokenizer
			lowerCamelCase__          =AutoModelForSeqaSeqLM

			lowerCamelCase__          =['text', 'text']
			lowerCamelCase__          =['text']
			def 							__UpperCamelCase	(     self							:	List[Any] , a							:	str , a							:	str		)							->    Union[str, Any]:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE				: Dict			       =    QA_PROMPT.format(text=a , question=a		)
				return self.pre_processor(a , return_tensors="pt"		)
			def 							__UpperCamelCase	(     self							:	Optional[Any] , a							:	Tuple		)							->    str:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE				: List[str]			       =    self.model.generate(**a		)

				SCREAMING_SNAKE_CASE       ,SCREAMING_SNAKE_CASE				: Dict			       =    inputs["input_ids"].shape
				SCREAMING_SNAKE_CASE				: Optional[Any]			       =    output_ids.shape[0]

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






			def 							__UpperCamelCase	(     self							:	List[Any] , a							:	Optional[int]		)							->    Optional[int]:

				"""simple docstring"""

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


from __future__ import annotations

def 	lowerCamelCase__	(   _a							,     _a							,     _a):
	if len(_a) == 0:
		raise ValueError("find_min() arg is an empty sequence")
	if (
	    left >= len(_a)
	    or left < -len(_a)
	    or right >= len(_a)
	    or right < -len(_a)
	):
		raise IndexError("list index out of range")
	if left == right:
		return nums[left]
	SCREAMING_SNAKE_CASE				: List[str]			       =    (left + right) >> 1  # the middle
	SCREAMING_SNAKE_CASE				: Tuple			       =    find_min(_a							,     _a							,     _a)  # find min in range[left, mid]
	SCREAMING_SNAKE_CASE				: Optional[Any]			       =    find_min(_a							,     mid + 1							,     _a)  # find min in range[mid + 1, right]

	return left_min if left_min <= right_min else right_min


if __name__ == "__main__":
			import doctest

			doctest.testmod(verbose=True)