How to use list_language_models method in localstack

Best Python code snippet using localstack_python

aws_transcribe_info.py

Source:aws_transcribe_info.py Github

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...105 StatusEquals=module.params['status'],106 NameContains=module.params['name_contains'],107 ), True108 else:109 return client.list_language_models(110 StatusEquals=module.params['status'],111 NameContains=module.params['name_contains'],112 ), False113 elif module.params['list_medical_transcription_jobs']:114 if client.can_paginate('list_medical_transcription_jobs'):115 paginator = client.get_paginator('list_medical_transcription_jobs')116 return paginator.paginate(117 Status=module.params['status'],118 JobNameContains=module.params['name_contains'],119 ), True120 else:121 return client.list_medical_transcription_jobs(122 Status=module.params['status'],123 JobNameContains=module.params['name_contains'],...

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test_speech_to_text_v1.py

Source:test_speech_to_text_v1.py Github

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...15 '1',16 'X-Watson-Test':17 '1'18 })19 self.custom_models = self.speech_to_text.list_language_models()20 self.create_custom_model = self.speech_to_text.create_language_model(21 name="integration_test_model",22 base_model_name="en-US_BroadbandModel")23 self.customization_id = self.create_custom_model['customization_id']24 def tearDown(self):25 self.speech_to_text.delete_language_model(26 customization_id=self.create_custom_model['customization_id'])27 def test_models(self):28 output = self.speech_to_text.list_models()29 assert output is not None30 model = self.speech_to_text.get_model('ko-KR_BroadbandModel')31 assert model is not None32 try:33 self.speech_to_text.get_model('bogus')34 except Exception as e:35 assert 'X-global-transaction-id:' in str(e)36 def test_create_custom_model(self):37 current_custom_models = self.speech_to_text.list_language_models()38 assert len(current_custom_models['customizations']) - len(39 self.custom_models['customizations']) >= 140 def test_recognize(self):41 with open(os.path.join(os.path.dirname(__file__), '../../resources/speech.wav'), 'rb') as audio_file:42 output = self.speech_to_text.recognize(43 audio=audio_file, content_type='audio/l16; rate=44100')44 assert output['results'][0]['alternatives'][0][45 'transcript'] == 'thunderstorms could produce large hail isolated tornadoes and heavy rain '46 def test_recognitions(self):47 output = self.speech_to_text.check_jobs()48 assert output is not None49 def test_custom_corpora(self):50 output = self.speech_to_text.list_corpora(self.customization_id)51 assert len(output['corpora']) == 0 # pylint: disable=len-as-condition...

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