






# 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 typing import TYPE_CHECKING

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


A__     :      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:
							A__     :      List[str]             =			['DocumentQuestionAnsweringTool']
							A__     :      Any             =			['ImageCaptioningTool']
							A__     :      Union[str, Any]             =			['ImageQuestionAnsweringTool']
							A__     :      Any             =			['ImageSegmentationTool']
							A__     :      str             =			['SpeechToTextTool']
							A__     :      Tuple             =			['TextClassificationTool']
							A__     :      List[Any]             =			['TextQuestionAnsweringTool']
							A__     :      Any             =			['TextSummarizationTool']
							A__     :      str             =			['TextToSpeechTool']
							A__     :      Any             =			['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

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












import unittest

from datasets import load_dataset

from transformers import load_tool

from .test_tools_common import ToolTesterMixin
class 				_UpperCAmelCase (	unittest.TestCase		,A__     ):

				"""simple docstring"""




				def     lowercase__       (					self						:   str  ):

								'''simple docstring'''
								lowercase__       			=      load_tool('''document-question-answering'''  )
								self.tool.setup()
								lowercase__       			=      load_tool('''document-question-answering''',  remote=lowerCamelCase  )




				def     lowercase__       (					self						:   List[Any]  ):

								'''simple docstring'''
								lowercase__       			=      load_dataset('''hf-internal-testing/example-documents''',  split='''test'''  )
								lowercase__       			=      dataset[0]['''image''']

								lowercase__       			=      self.tool(lowerCamelCase,  '''When is the coffee break?'''  )
								self.assertEqual(lowerCamelCase,  '''11-14 to 11:39 a.m.'''  )




				def     lowercase__       (					self						:   Optional[Any]  ):

								'''simple docstring'''
								lowercase__       			=      load_dataset('''hf-internal-testing/example-documents''',  split='''test'''  )
								lowercase__       			=      dataset[0]['''image''']

								lowercase__       			=      self.remote_tool(lowerCamelCase,  '''When is the coffee break?'''  )
								self.assertEqual(lowerCamelCase,  '''11-14 to 11:39 a.m.'''  )




				def     lowercase__       (					self						:   Any  ):

								'''simple docstring'''
								lowercase__       			=      load_dataset('''hf-internal-testing/example-documents''',  split='''test'''  )
								lowercase__       			=      dataset[0]['''image''']

								self.tool(document=lowerCamelCase,  question='''When is the coffee break?'''  )




				def     lowercase__       (					self						:   Tuple  ):

								'''simple docstring'''
								lowercase__       			=      load_dataset('''hf-internal-testing/example-documents''',  split='''test'''  )
								lowercase__       			=      dataset[0]['''image''']

								lowercase__       			=      self.remote_tool(document=lowerCamelCase,  question='''When is the coffee break?'''  )
								self.assertEqual(lowerCamelCase,  '''11-14 to 11:39 a.m.'''  )




