






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


__UpperCAmelCase								=						{'configuration_opt': ['OPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'OPTConfig']}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__UpperCAmelCase								=						[
		    'OPT_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'OPTForCausalLM',
		    'OPTModel',
		    'OPTPreTrainedModel',
		    'OPTForSequenceClassification',
		    'OPTForQuestionAnswering',
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__UpperCAmelCase								=						['TFOPTForCausalLM', 'TFOPTModel', 'TFOPTPreTrainedModel']

try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__UpperCAmelCase								=						[
		    'FlaxOPTForCausalLM',
		    'FlaxOPTModel',
		    'FlaxOPTPreTrainedModel',
		]


if TYPE_CHECKING:
		from .configuration_opt import OPT_PRETRAINED_CONFIG_ARCHIVE_MAP, OPTConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_opt import (
				    OPT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    OPTForCausalLM,
				    OPTForQuestionAnswering,
				    OPTForSequenceClassification,
				    OPTModel,
				    OPTPreTrainedModel,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_opt import TFOPTForCausalLM, TFOPTModel, TFOPTPreTrainedModel

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_opt import FlaxOPTForCausalLM, FlaxOPTModel, FlaxOPTPreTrainedModel

else:
		import sys

		__UpperCAmelCase								=						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)








import pprint

import requests

UpperCAmelCase	      = '''https://zenquotes.io/api'''






def 							UpperCAmelCase_		(							):
	return requests.get(API_ENDPOINT_URL + '/today'							).json()






def 							UpperCAmelCase_		(							):
	return requests.get(API_ENDPOINT_URL + '/random'							).json()


if __name__ == "__main__":
	UpperCAmelCase	      = random_quotes()
	pprint.pprint(response)

