
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							, lowercase		):



							def     A__ (     self							)						->     int:






								"""simple docstring"""



								UpperCAmelCase:					List[str] 						=     load_tool("translation"							)
								self.tool.setup()
								UpperCAmelCase:					str 						=     load_tool("translation"	,				remote=__snake_case							)



							def     A__ (     self							)						->     List[str]:






								"""simple docstring"""



								UpperCAmelCase:					Dict 						=     self.tool("Hey, what's up?"	,				src_lang="English"	,				tgt_lang="French"							)
								self.assertEqual(__snake_case	,				"- Hé, comment ça va?"							)



							def     A__ (     self							)						->     Tuple:






								"""simple docstring"""



								UpperCAmelCase:					Dict 						=     self.remote_tool("Hey, what's up?"	,				src_lang="English"	,				tgt_lang="French"							)
								self.assertEqual(__snake_case	,				"- Hé, comment ça va?"							)



							def     A__ (     self							)						->     int:






								"""simple docstring"""



								UpperCAmelCase:					Tuple 						=     self.tool(text="Hey, what's up?"	,				src_lang="English"	,				tgt_lang="French"							)
								self.assertEqual(__snake_case	,				"- Hé, comment ça va?"							)



							def     A__ (     self							)						->     List[Any]:






								"""simple docstring"""



								UpperCAmelCase:					Any 						=     self.remote_tool(text="Hey, what's up?"	,				src_lang="English"	,				tgt_lang="French"							)
								self.assertEqual(__snake_case	,				"- Hé, comment ça va?"							)



							def     A__ (     self							)						->     Any:






								"""simple docstring"""



								UpperCAmelCase:					str 						=     ["Hey, what's up?", "English", "Spanish"]
								UpperCAmelCase:					Union[str, Any] 						=     self.tool(*__snake_case							)

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

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



							def     A__ (     self							)						->     Optional[Any]:






								"""simple docstring"""



								UpperCAmelCase:					Tuple 						=     ["Hey, what's up?", "English", "Spanish"]
								UpperCAmelCase:					Any 						=     self.tool(*__snake_case							)

								if not isinstance(__snake_case	,				__snake_case							):
									UpperCAmelCase:					Optional[int] 						=     [outputs]

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

								for output, output_type in zip(__snake_case	,				self.tool.outputs							):
									UpperCAmelCase:					List[str] 						=     AGENT_TYPE_MAPPING[output_type]
									self.assertTrue(isinstance(__snake_case	,				__snake_case							)							)




							def     A__ (     self							)						->     List[str]:






								"""simple docstring"""



								UpperCAmelCase:					Dict 						=     ["Hey, what's up?", "English", "Spanish"]

								UpperCAmelCase:					Union[str, Any] 						=     []

								for _input, input_type in zip(__snake_case	,				self.tool.inputs							):
									if isinstance(__snake_case	,				__snake_case							):
										_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:					int 						=     self.tool(*__snake_case							)

								if not isinstance(__snake_case	,				__snake_case							):
									UpperCAmelCase:					str 						=     [outputs]

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


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


snake_case_      :					Optional[int]				      =     {
    'configuration_splinter': ['SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SplinterConfig'],
    'tokenization_splinter': ['SplinterTokenizer'],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	snake_case_      :					Dict				      =     ['SplinterTokenizerFast']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	snake_case_      :					Optional[Any]				      =     [
	    'SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'SplinterForQuestionAnswering',
	    'SplinterForPreTraining',
	    'SplinterLayer',
	    'SplinterModel',
	    'SplinterPreTrainedModel',
	]


if TYPE_CHECKING:
	from .configuration_splinter import SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP, SplinterConfig
	from .tokenization_splinter import SplinterTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_splinter_fast import SplinterTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_splinter import (
		    SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    SplinterForPreTraining,
		    SplinterForQuestionAnswering,
		    SplinterLayer,
		    SplinterModel,
		    SplinterPreTrainedModel,
		)


else:
	import sys

	snake_case_      :					Dict				      =     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
