
'''simple docstring'''

from typing import TYPE_CHECKING

from ..utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


UpperCAmelCase__				:	List[str]					=						{
    "agents": ["Agent", "AzureOpenAiAgent", "HfAgent", "LocalAgent", "OpenAiAgent"],
    "base": ["PipelineTool", "RemoteTool", "Tool", "launch_gradio_demo", "load_tool"],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		UpperCAmelCase__				:	Dict					=						["DocumentQuestionAnsweringTool"]
		UpperCAmelCase__				:	str					=						["ImageCaptioningTool"]
		UpperCAmelCase__				:	Tuple					=						["ImageQuestionAnsweringTool"]
		UpperCAmelCase__				:	Optional[Any]					=						["ImageSegmentationTool"]
		UpperCAmelCase__				:	Any					=						["SpeechToTextTool"]
		UpperCAmelCase__				:	Any					=						["TextClassificationTool"]
		UpperCAmelCase__				:	Optional[int]					=						["TextQuestionAnsweringTool"]
		UpperCAmelCase__				:	List[str]					=						["TextSummarizationTool"]
		UpperCAmelCase__				:	Optional[int]					=						["TextToSpeechTool"]
		UpperCAmelCase__				:	str					=						["TranslationTool"]

if TYPE_CHECKING:
		from .agents import Agent, AzureOpenAiAgent, HfAgent, LocalAgent, OpenAiAgent
		from .base import PipelineTool, RemoteTool, Tool, launch_gradio_demo, load_tool

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .document_question_answering import DocumentQuestionAnsweringTool
				from .image_captioning import ImageCaptioningTool
				from .image_question_answering import ImageQuestionAnsweringTool
				from .image_segmentation import ImageSegmentationTool
				from .speech_to_text import SpeechToTextTool
				from .text_classification import TextClassificationTool
				from .text_question_answering import TextQuestionAnsweringTool
				from .text_summarization import TextSummarizationTool
				from .text_to_speech import TextToSpeechTool
				from .translation import TranslationTool
else:
		import sys

		UpperCAmelCase__				:	Union[str, Any]					=						_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)







'''simple docstring'''

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 				A       (		unittest.TestCase					, SCREAMING_SNAKE_CASE__      ):





	def 							__SCREAMING_SNAKE_CASE					(   self     :    List[Any]							):


				"""simple docstring"""

				lowerCAmelCase__									=							load_tool("translation"							)
				self.tool.setup()
				lowerCAmelCase__									=							load_tool("translation" ,							remote=__magic_name__							)





	def 							__SCREAMING_SNAKE_CASE					(   self     :    Tuple							):


				"""simple docstring"""

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





	def 							__SCREAMING_SNAKE_CASE					(   self     :    Optional[int]							):


				"""simple docstring"""

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





	def 							__SCREAMING_SNAKE_CASE					(   self     :    List[Any]							):


				"""simple docstring"""

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





	def 							__SCREAMING_SNAKE_CASE					(   self     :    int							):


				"""simple docstring"""

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





	def 							__SCREAMING_SNAKE_CASE					(   self     :    int							):


				"""simple docstring"""

				lowerCAmelCase__									=							["Hey, what's up?", "English", "Spanish"]
				lowerCAmelCase__									=							self.tool(*__magic_name__							)

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

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





	def 							__SCREAMING_SNAKE_CASE					(   self     :    str							):


				"""simple docstring"""

				lowerCAmelCase__									=							["Hey, what's up?", "English", "Spanish"]
				lowerCAmelCase__									=							self.tool(*__magic_name__							)

				if not isinstance(__magic_name__ ,							__magic_name__							):
							lowerCAmelCase__									=							[outputs]

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

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







	def 							__SCREAMING_SNAKE_CASE					(   self     :    int							):


				"""simple docstring"""

				lowerCAmelCase__									=							["Hey, what's up?", "English", "Spanish"]

				lowerCAmelCase__									=							[]

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

				if not isinstance(__magic_name__ ,							__magic_name__							):
							lowerCAmelCase__									=							[outputs]

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





