






from pathlib import Path
from typing import List

from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText


if is_torch_available():
       import torch

if is_vision_available():
       from PIL import Image


UpperCamelCase    							=      ['text', 'image', 'audio']


def 				__lowerCamelCase     (							__lowerCAmelCase							:					List[str]							)     ->  List[str]:
   __UpperCamelCase	:			Dict					=					[]

   for input_type in input_types:
      if input_type == "text":
         inputs.append("""Text input"""							)
      elif input_type == "image":
         inputs.append(
             Image.open(Path(get_tests_dir("""fixtures/tests_samples/COCO"""							)							) / """000000039769.png"""							).resize((512, 512)							)							)
      elif input_type == "audio":
         inputs.append(torch.ones(3000							)							)
      elif isinstance(__lowerCAmelCase					,							__lowerCAmelCase							):
         inputs.append(create_inputs(__lowerCAmelCase							)							)
      else:
         raise ValueError(f'Invalid type requested: {input_type}'							)

   return inputs


def 				__lowerCamelCase     (							__lowerCAmelCase							:					List							)     ->  Any:
   __UpperCamelCase	:			Optional[Any]					=					[]

   for output in outputs:
      if isinstance(__lowerCAmelCase					,							(str, AgentText)							):
         output_types.append("""text"""							)
      elif isinstance(__lowerCAmelCase					,							(Image.Image, AgentImage)							):
         output_types.append("""image"""							)
      elif isinstance(__lowerCAmelCase					,							(torch.Tensor, AgentAudio)							):
         output_types.append("""audio"""							)
      else:
         raise ValueError(f'Invalid output: {output}'							)

   return output_types







@is_tool_test
class 		_A						:

  def    a					(    self						:	Dict			):
     """simple docstring"""

     self.assertTrue(hasattr(self.tool   ,				"""inputs"""			)			)
     self.assertTrue(hasattr(self.tool   ,				"""outputs"""			)			)

     __UpperCamelCase	:			Any					=					self.tool.inputs
     for _input in inputs:
        if isinstance(_input   ,				lowerCamelCase__			):
           for __input in _input:
              self.assertTrue(__input in authorized_types			)
        else:
           self.assertTrue(_input in authorized_types			)

     __UpperCamelCase	:			List[str]					=					self.tool.outputs
     for _output in outputs:
        self.assertTrue(_output in authorized_types			)

  def    a					(    self						:	Tuple			):
     """simple docstring"""

     __UpperCamelCase	:			Dict					=					create_inputs(self.tool.inputs			)
     __UpperCamelCase	:			str					=					self.tool(*lowerCamelCase__			)

     # There is a single output
     if len(self.tool.outputs			) == 1:
        __UpperCamelCase	:			Union[str, Any]					=					[outputs]

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

  def    a					(    self						:	Dict			):
     """simple docstring"""

     self.assertTrue(hasattr(self.tool   ,				"""description"""			)			)
     self.assertTrue(hasattr(self.tool   ,				"""default_checkpoint"""			)			)
     self.assertTrue(self.tool.description.startswith("""This is a tool that"""			)			)

  def    a					(    self						:	str			):
     """simple docstring"""

     __UpperCamelCase	:			Tuple					=					create_inputs(self.tool.inputs			)
     __UpperCamelCase	:			Tuple					=					self.tool(*lowerCamelCase__			)

     if not isinstance(lowerCamelCase__   ,				lowerCamelCase__			):
        __UpperCamelCase	:			Dict					=					[outputs]

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

     for output, output_type in zip(lowerCamelCase__   ,				self.tool.outputs			):
        __UpperCamelCase	:			Tuple					=					AGENT_TYPE_MAPPING[output_type]
        self.assertTrue(isinstance(lowerCamelCase__   ,				lowerCamelCase__			)			)

  def    a					(    self						:	str			):
     """simple docstring"""

     __UpperCamelCase	:			int					=					create_inputs(self.tool.inputs			)

     __UpperCamelCase	:			Optional[Any]					=					[]

     for _input, input_type in zip(lowerCamelCase__   ,				self.tool.inputs			):
        if isinstance(lowerCamelCase__   ,				lowerCamelCase__			):
           _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
     __UpperCamelCase	:			Tuple					=					self.tool(*lowerCamelCase__			)

     if not isinstance(lowerCamelCase__   ,				lowerCamelCase__			):
        __UpperCamelCase	:			List[str]					=					[outputs]

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











def 				__lowerCamelCase     (							__lowerCAmelCase							:					str							)     ->  bool:
   if not all(x.isalpha() for x in string							):
      raise ValueError("""String must only contain alphabetic characters."""							)

   __UpperCamelCase	:			List[str]					=					sorted(string.lower()							)
   return len(__lowerCAmelCase							) == len(set(__lowerCAmelCase							)							)


if __name__ == "__main__":
       UpperCamelCase    							=      input('Enter a string ').strip()

       UpperCamelCase    							=      is_isogram(input_str)
       print(F"""{input_str} is {'an' if isogram else 'not an'} isogram.""")



