
import textwrap

import pyarrow as pa
import pytest

from datasets import Features, Image
from datasets.packaged_modules.text.text import Text

from ..utils import require_pil


@pytest.fixture
def     a__			(    snake_case    ) ->    Union[str, Any]:





  """simple docstring"""
  __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						tmp_path / """text.txt"""
  __SCREAMING_SNAKE_CASE     :					List[str]			=						textwrap.dedent(
      '''\
        Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
        Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.
        Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur.
        Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

        Second paragraph:
        Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
        Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.
        Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur.
        Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.
        '''    )
  with open(snake_case   ,	'''w'''   ,	encoding='''utf-8'''    ) as f:
    f.write(snake_case    )
  return str(snake_case    )


@pytest.fixture
def     a__			(    snake_case   ,	snake_case    ) ->    Dict:





  """simple docstring"""
  __SCREAMING_SNAKE_CASE     :					Dict			=						tmp_path / """text_with_image.txt"""
  with open(snake_case   ,	'''w'''   ,	encoding='''utf-8'''    ) as f:
    f.write(snake_case    )
  return str(snake_case    )


@pytest.mark.parametrize('''keep_linebreaks'''   ,	[True, False]    )
def     a__			(    snake_case   ,	snake_case    ) ->    int:





  """simple docstring"""
  with open(snake_case   ,	encoding='''utf-8'''    ) as f:
    __SCREAMING_SNAKE_CASE     :					Tuple			=						f.read().splitlines(keepends=snake_case    )
  __SCREAMING_SNAKE_CASE     :					List[str]			=						Text(keep_linebreaks=snake_case   ,	encoding='''utf-8'''    )
  __SCREAMING_SNAKE_CASE     :					Union[str, Any]			=						text._generate_tables([[text_file]]    )
  __SCREAMING_SNAKE_CASE     :					List[Any]			=						pa.concat_tables([table for _, table in generator]    ).to_pydict()["""text"""]
  assert generated_content == expected_content


@require_pil
def     a__			(    snake_case    ) ->    Dict:





  """simple docstring"""
  with open(snake_case   ,	encoding='''utf-8'''    ) as f:
    __SCREAMING_SNAKE_CASE     :					Optional[int]			=						f.read().splitlines()[0]
  __SCREAMING_SNAKE_CASE     :					Any			=						Text(encoding='''utf-8'''   ,	features=Features({'''image''': Image()}    )    )
  __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						text._generate_tables([[text_file_with_image]]    )
  __SCREAMING_SNAKE_CASE     :					Union[str, Any]			=						pa.concat_tables([table for _, table in generator]    )
  assert pa_table.schema.field('''image'''    ).type == Image()()
  __SCREAMING_SNAKE_CASE     :					Union[str, Any]			=						pa_table.to_pydict()["""image"""]
  assert generated_content == [{"path": image_file, "bytes": None}]


@pytest.mark.parametrize('''sample_by'''   ,	['''line''', '''paragraph''', '''document''']    )
def     a__			(    snake_case   ,	snake_case    ) ->    Union[str, Any]:





  """simple docstring"""
  with open(snake_case   ,	encoding='''utf-8'''    ) as f:
    __SCREAMING_SNAKE_CASE     :					Union[str, Any]			=						f.read()
  if sample_by == "line":
    __SCREAMING_SNAKE_CASE     :					List[str]			=						expected_content.splitlines()
  elif sample_by == "paragraph":
    __SCREAMING_SNAKE_CASE     :					Any			=						expected_content.split('''\n\n'''    )
  elif sample_by == "document":
    __SCREAMING_SNAKE_CASE     :					Any			=						[expected_content]
  __SCREAMING_SNAKE_CASE     :					str			=						Text(sample_by=snake_case   ,	encoding='''utf-8'''   ,	chunksize=100    )
  __SCREAMING_SNAKE_CASE     :					int			=						text._generate_tables([[text_file]]    )
  __SCREAMING_SNAKE_CASE     :					str			=						pa.concat_tables([table for _, table in generator]    ).to_pydict()["""text"""]
  assert generated_content == expected_content


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   __UpperCamelCase				(    unittest.TestCase				,		lowerCAmelCase__   ):






     """simple docstring"""







     def 				UpperCAmelCase__    (							self    :    Optional[Any]				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					str			=						load_tool('''translation'''				)
       self.tool.setup()
       __SCREAMING_SNAKE_CASE     :					List[Any]			=						load_tool('''translation'''      ,		remote=_A				)



     def 				UpperCAmelCase__    (							self    :    List[Any]				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					Any			=						self.tool('''Hey, what\'s up?'''      ,		src_lang='''English'''      ,		tgt_lang='''French'''				)
       self.assertEqual(_A      ,		'''- Hé, comment ça va?'''				)



     def 				UpperCAmelCase__    (							self    :    List[str]				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					List[str]			=						self.remote_tool('''Hey, what\'s up?'''      ,		src_lang='''English'''      ,		tgt_lang='''French'''				)
       self.assertEqual(_A      ,		'''- Hé, comment ça va?'''				)



     def 				UpperCAmelCase__    (							self    :    Optional[Any]				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					int			=						self.tool(text='''Hey, what\'s up?'''      ,		src_lang='''English'''      ,		tgt_lang='''French'''				)
       self.assertEqual(_A      ,		'''- Hé, comment ça va?'''				)



     def 				UpperCAmelCase__    (							self    :    int				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					List[Any]			=						self.remote_tool(text='''Hey, what\'s up?'''      ,		src_lang='''English'''      ,		tgt_lang='''French'''				)
       self.assertEqual(_A      ,		'''- Hé, comment ça va?'''				)



     def 				UpperCAmelCase__    (							self    :    Union[str, Any]				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					Optional[int]			=						['''Hey, what\'s up?''', '''English''', '''Spanish''']
       __SCREAMING_SNAKE_CASE     :					List[Any]			=						self.tool(*_A				)

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

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



     def 				UpperCAmelCase__    (							self    :    Union[str, Any]				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					int			=						['''Hey, what\'s up?''', '''English''', '''Spanish''']
       __SCREAMING_SNAKE_CASE     :					List[str]			=						self.tool(*_A				)

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

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

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




     def 				UpperCAmelCase__    (							self    :    List[str]				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					Dict			=						['''Hey, what\'s up?''', '''English''', '''Spanish''']

       __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						[]

       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
       __SCREAMING_SNAKE_CASE     :					Union[str, Any]			=						self.tool(*_A				)

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

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