'''simple docstring'''

# 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 :				Dict														= """Here is a text containing a lot of information: '''{text}'''.

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




class    lowerCamelCase__  (   __snake_case     ):
   __UpperCAmelCase           =						"""google/flan-t5-base"""
   __UpperCAmelCase           =						(
       """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           =						"""text_qa"""
   __UpperCAmelCase           =						AutoTokenizer
   __UpperCAmelCase           =						AutoModelForSeqaSeqLM

   __UpperCAmelCase           =						["""text""", """text"""]
   __UpperCAmelCase           =						["""text"""]



   def  _UpperCamelCase		(    self					,      lowerCAmelCase__					,      lowerCAmelCase__     )				->     Optional[int]:
        """simple docstring"""





        _UpperCamelCase  :str       =QA_PROMPT.format(text=lowerCAmelCase__					,      question=lowerCAmelCase__     )
        return self.pre_processor(lowerCAmelCase__					,      return_tensors="""pt"""     )



   def  _UpperCamelCase		(    self					,      lowerCAmelCase__     )				->     Optional[Any]:
        """simple docstring"""





        _UpperCamelCase  :str       =self.model.generate(**lowerCAmelCase__     )

        _UpperCamelCase       ,      _UpperCamelCase  :List[str]       =inputs["""input_ids"""].shape
        _UpperCamelCase  :List[str]       =output_ids.shape[0]

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




   def  _UpperCamelCase		(    self					,      lowerCAmelCase__     )				->     Any:
        """simple docstring"""





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

import unittest

from transformers import load_tool
from transformers.tools.agent_types import AGENT_TYPE_MAPPING

from .test_tools_common import ToolTesterMixin, output_types







class 	lowerCamelCase						(    unittest.TestCase				,					A_    ):





     def 						UpperCAmelCase(self :       Any  )		->		int:
         snake_case						=   load_tool("translation"  )
         self.tool.setup()
         snake_case						=   load_tool("translation"							,       remote=_A  )





     def 						UpperCAmelCase(self :       Optional[Any]  )		->		Optional[int]:
         snake_case						=   self.tool("Hey, what's up?"							,       src_lang="English"							,       tgt_lang="French"  )
         self.assertEqual(_A							,       "- Hé, comment ça va?"  )





     def 						UpperCAmelCase(self :       str  )		->		int:
         snake_case						=   self.remote_tool("Hey, what's up?"							,       src_lang="English"							,       tgt_lang="French"  )
         self.assertEqual(_A							,       "- Hé, comment ça va?"  )





     def 						UpperCAmelCase(self :       str  )		->		List[str]:
         snake_case						=   self.tool(text="Hey, what's up?"							,       src_lang="English"							,       tgt_lang="French"  )
         self.assertEqual(_A							,       "- Hé, comment ça va?"  )





     def 						UpperCAmelCase(self :       Optional[Any]  )		->		str:
         snake_case						=   self.remote_tool(text="Hey, what's up?"							,       src_lang="English"							,       tgt_lang="French"  )
         self.assertEqual(_A							,       "- Hé, comment ça va?"  )





     def 						UpperCAmelCase(self :       Any  )		->		Tuple:
         snake_case						=   ["Hey, what's up?", "English", "Spanish"]
         snake_case						=   self.tool(*_A  )

         # There is a single output
         if len(self.tool.outputs  ) == 1:
             snake_case						=   [outputs]

         self.assertListEqual(output_types(_A  )							,       self.tool.outputs  )





     def 						UpperCAmelCase(self :       List[str]  )		->		List[Any]:
         snake_case						=   ["Hey, what's up?", "English", "Spanish"]
         snake_case						=   self.tool(*_A  )

         if not isinstance(_A							,       _A  ):
             snake_case						=   [outputs]

         self.assertEqual(len(_A  )							,       len(self.tool.outputs  )  )

         for output, output_type in zip(_A							,       self.tool.outputs  ):
             snake_case						=   AGENT_TYPE_MAPPING[output_type]
             self.assertTrue(isinstance(_A							,       _A  )  )





     def 						UpperCAmelCase(self :       int  )		->		Any:
         snake_case						=   ["Hey, what's up?", "English", "Spanish"]

         snake_case						=   []

         for _input, input_type in zip(_A							,       self.tool.inputs  ):
             if isinstance(_A							,       _A  ):
                 _inputs.append([AGENT_TYPE_MAPPING[_input_type](_input  ) for _input_type in input_type]  )
             else:
                 _inputs.append(AGENT_TYPE_MAPPING[input_type](_input  )  )

        # Should not raise an error
         snake_case						=   self.tool(*_A  )

         if not isinstance(_A							,       _A  ):
             snake_case						=   [outputs]

         self.assertEqual(len(_A  )							,       len(self.tool.outputs  )  )

