from datetime import datetime, timedelta from moto.core import BaseBackend, BackendDict, BaseModel from moto.moto_api import state_manager from moto.moto_api._internal import mock_random from moto.moto_api._internal.managed_state_model import ManagedState from .exceptions import ConflictException, BadRequestException class BaseObject(BaseModel): def camelCase(self, key): words = [] for word in key.split("_"): words.append(word.title()) return "".join(words) def gen_response_object(self): response_object = dict() for key, value in self.__dict__.items(): if "_" in key: response_object[self.camelCase(key)] = value else: response_object[key[0].upper() + key[1:]] = value return response_object @property def response_object(self): return self.gen_response_object() class FakeTranscriptionJob(BaseObject, ManagedState): def __init__( self, account_id, region_name, transcription_job_name, language_code, media_sample_rate_hertz, media_format, media, output_bucket_name, output_key, output_encryption_kms_key_id, settings, model_settings, job_execution_settings, content_redaction, identify_language, language_options, ): ManagedState.__init__( self, "transcribe::transcriptionjob", transitions=[ (None, "QUEUED"), ("QUEUED", "IN_PROGRESS"), ("IN_PROGRESS", "COMPLETED"), ], ) self._account_id = account_id self._region_name = region_name self.transcription_job_name = transcription_job_name self.language_code = language_code self.media_sample_rate_hertz = media_sample_rate_hertz self.media_format = media_format self.media = media self.transcript = None self.start_time = self.completion_time = None self.creation_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S") self.failure_reason = None self.settings = settings or { "ChannelIdentification": False, "ShowAlternatives": False, "ShowSpeakerLabels": False, } self.model_settings = model_settings or {"LanguageModelName": None} self.job_execution_settings = job_execution_settings or { "AllowDeferredExecution": False, "DataAccessRoleArn": None, } self.content_redaction = content_redaction or { "RedactionType": None, "RedactionOutput": None, } self.identify_language = identify_language self.language_options = language_options self.identified_language_score = (None,) self._output_bucket_name = output_bucket_name self.output_key = output_key self._output_encryption_kms_key_id = output_encryption_kms_key_id self.output_location_type = ( "CUSTOMER_BUCKET" if self._output_bucket_name else "SERVICE_BUCKET" ) def response_object(self, response_type): response_field_dict = { "CREATE": [ "TranscriptionJobName", "TranscriptionJobStatus", "LanguageCode", "MediaFormat", "Media", "Settings", "StartTime", "CreationTime", "IdentifyLanguage", "LanguageOptions", "JobExecutionSettings", ], "GET": [ "TranscriptionJobName", "TranscriptionJobStatus", "LanguageCode", "MediaSampleRateHertz", "MediaFormat", "Media", "Settings", "Transcript", "StartTime", "CreationTime", "CompletionTime", "IdentifyLanguage", "LanguageOptions", "IdentifiedLanguageScore", ], "LIST": [ "TranscriptionJobName", "CreationTime", "StartTime", "CompletionTime", "LanguageCode", "TranscriptionJobStatus", "FailureReason", "IdentifyLanguage", "IdentifiedLanguageScore", "OutputLocationType", ], } response_fields = response_field_dict[response_type] response_object = self.gen_response_object() response_object["TranscriptionJobStatus"] = self.status if response_type != "LIST": return { "TranscriptionJob": { k: v for k, v in response_object.items() if k in response_fields and v is not None and v != [None] } } else: return { k: v for k, v in response_object.items() if k in response_fields and v is not None and v != [None] } def advance(self): old_status = self.status super().advance() new_status = self.status if old_status == new_status: return if new_status == "IN_PROGRESS": self.start_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S") if not self.media_sample_rate_hertz: self.media_sample_rate_hertz = 44100 if not self.media_format: file_ext = self.media["MediaFileUri"].split(".")[-1].lower() self.media_format = ( file_ext if file_ext in ["mp3", "mp4", "wav", "flac"] else "mp3" ) if self.identify_language: self.identified_language_score = 0.999645948 # Simply identify first language passed in lanugage_options # If non is set default to "en-US" if self.language_options is not None and len(self.language_options) > 0: self.language_code = self.language_options[0] else: self.language_code = "en-US" elif new_status == "COMPLETED": self.completion_time = (datetime.now() + timedelta(seconds=10)).strftime( "%Y-%m-%d %H:%M:%S" ) if self._output_bucket_name: transcript_file_uri = f"https://s3.{self._region_name}.amazonaws.com/{self._output_bucket_name}/" if self.output_key is not None: transcript_file_uri += f"{self.output_key}/" transcript_file_uri += f"{self.transcription_job_name}.json" self.output_location_type = "CUSTOMER_BUCKET" else: transcript_file_uri = f"https://s3.{self._region_name}.amazonaws.com/aws-transcribe-{self._region_name}-prod/{self._account_id}/{self.transcription_job_name}/{mock_random.uuid4()}/asrOutput.json" self.output_location_type = "SERVICE_BUCKET" self.transcript = {"TranscriptFileUri": transcript_file_uri} class FakeVocabulary(BaseObject, ManagedState): def __init__( self, account_id, region_name, vocabulary_name, language_code, phrases, vocabulary_file_uri, ): # Configured ManagedState super().__init__( "transcribe::vocabulary", transitions=[(None, "PENDING"), ("PENDING", "READY")], ) # Configure internal properties self._region_name = region_name self.vocabulary_name = vocabulary_name self.language_code = language_code self.phrases = phrases self.vocabulary_file_uri = vocabulary_file_uri self.last_modified_time = None self.failure_reason = None self.download_uri = f"https://s3.{region_name}.amazonaws.com/aws-transcribe-dictionary-model-{region_name}-prod/{account_id}/{vocabulary_name}/{mock_random.uuid4()}/input.txt" def response_object(self, response_type): response_field_dict = { "CREATE": [ "VocabularyName", "LanguageCode", "VocabularyState", "LastModifiedTime", "FailureReason", ], "GET": [ "VocabularyName", "LanguageCode", "VocabularyState", "LastModifiedTime", "FailureReason", "DownloadUri", ], "LIST": [ "VocabularyName", "LanguageCode", "LastModifiedTime", "VocabularyState", ], } response_fields = response_field_dict[response_type] response_object = self.gen_response_object() response_object["VocabularyState"] = self.status return { k: v for k, v in response_object.items() if k in response_fields and v is not None and v != [None] } def advance(self): old_status = self.status super().advance() new_status = self.status if old_status != new_status: self.last_modified_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S") class FakeMedicalTranscriptionJob(BaseObject, ManagedState): def __init__( self, region_name, medical_transcription_job_name, language_code, media_sample_rate_hertz, media_format, media, output_bucket_name, output_encryption_kms_key_id, settings, specialty, job_type, ): ManagedState.__init__( self, "transcribe::medicaltranscriptionjob", transitions=[ (None, "QUEUED"), ("QUEUED", "IN_PROGRESS"), ("IN_PROGRESS", "COMPLETED"), ], ) self._region_name = region_name self.medical_transcription_job_name = medical_transcription_job_name self.language_code = language_code self.media_sample_rate_hertz = media_sample_rate_hertz self.media_format = media_format self.media = media self.transcript = None self.start_time = self.completion_time = None self.creation_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S") self.failure_reason = None self.settings = settings or { "ChannelIdentification": False, "ShowAlternatives": False, } self.specialty = specialty self.type = job_type self._output_bucket_name = output_bucket_name self._output_encryption_kms_key_id = output_encryption_kms_key_id self.output_location_type = "CUSTOMER_BUCKET" def response_object(self, response_type): response_field_dict = { "CREATE": [ "MedicalTranscriptionJobName", "TranscriptionJobStatus", "LanguageCode", "MediaFormat", "Media", "StartTime", "CreationTime", "Specialty", "Type", ], "GET": [ "MedicalTranscriptionJobName", "TranscriptionJobStatus", "LanguageCode", "MediaSampleRateHertz", "MediaFormat", "Media", "Transcript", "StartTime", "CreationTime", "CompletionTime", "Settings", "Specialty", "Type", ], "LIST": [ "MedicalTranscriptionJobName", "CreationTime", "StartTime", "CompletionTime", "LanguageCode", "TranscriptionJobStatus", "FailureReason", "OutputLocationType", "Specialty", "Type", ], } response_fields = response_field_dict[response_type] response_object = self.gen_response_object() response_object["TranscriptionJobStatus"] = self.status if response_type != "LIST": return { "MedicalTranscriptionJob": { k: v for k, v in response_object.items() if k in response_fields and v is not None and v != [None] } } else: return { k: v for k, v in response_object.items() if k in response_fields and v is not None and v != [None] } def advance(self): old_status = self.status super().advance() new_status = self.status if old_status == new_status: return if new_status == "IN_PROGRESS": self.start_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S") if not self.media_sample_rate_hertz: self.media_sample_rate_hertz = 44100 if not self.media_format: file_ext = self.media["MediaFileUri"].split(".")[-1].lower() self.media_format = ( file_ext if file_ext in ["mp3", "mp4", "wav", "flac"] else "mp3" ) elif new_status == "COMPLETED": self.completion_time = (datetime.now() + timedelta(seconds=10)).strftime( "%Y-%m-%d %H:%M:%S" ) self.transcript = { "TranscriptFileUri": f"https://s3.{self._region_name}.amazonaws.com/{self._output_bucket_name}/medical/{self.medical_transcription_job_name}.json" } class FakeMedicalVocabulary(FakeVocabulary): def __init__( self, account_id, region_name, vocabulary_name, language_code, vocabulary_file_uri, ): super().__init__( account_id, region_name, vocabulary_name, language_code=language_code, phrases=None, vocabulary_file_uri=vocabulary_file_uri, ) self.model_name = "transcribe::medicalvocabulary" self._region_name = region_name self.vocabulary_name = vocabulary_name self.language_code = language_code self.vocabulary_file_uri = vocabulary_file_uri self.last_modified_time = None self.failure_reason = None self.download_uri = f"https://s3.us-east-1.amazonaws.com/aws-transcribe-dictionary-model-{region_name}-prod/{account_id}/medical/{self.vocabulary_name}/{mock_random.uuid4()}/input.txt" class TranscribeBackend(BaseBackend): def __init__(self, region_name, account_id): super().__init__(region_name, account_id) self.medical_transcriptions = {} self.transcriptions = {} self.medical_vocabularies = {} self.vocabularies = {} state_manager.register_default_transition( "transcribe::vocabulary", transition={"progression": "manual", "times": 1} ) state_manager.register_default_transition( "transcribe::medicalvocabulary", transition={"progression": "manual", "times": 1}, ) state_manager.register_default_transition( "transcribe::transcriptionjob", transition={"progression": "manual", "times": 1}, ) state_manager.register_default_transition( "transcribe::medicaltranscriptionjob", transition={"progression": "manual", "times": 1}, ) @staticmethod def default_vpc_endpoint_service(service_region, zones): """Default VPC endpoint services.""" return BaseBackend.default_vpc_endpoint_service_factory( service_region, zones, "transcribe" ) + BaseBackend.default_vpc_endpoint_service_factory( service_region, zones, "transcribestreaming" ) def start_transcription_job(self, **kwargs): name = kwargs.get("transcription_job_name") if name in self.transcriptions: raise ConflictException( message="The requested job name already exists. Use a different job name." ) settings = kwargs.get("settings") vocabulary_name = settings.get("VocabularyName") if settings else None if vocabulary_name and vocabulary_name not in self.vocabularies: raise BadRequestException( message="The requested vocabulary couldn't be found. " "Check the vocabulary name and try your request again." ) transcription_job_object = FakeTranscriptionJob( account_id=self.account_id, region_name=self.region_name, transcription_job_name=name, language_code=kwargs.get("language_code"), media_sample_rate_hertz=kwargs.get("media_sample_rate_hertz"), media_format=kwargs.get("media_format"), media=kwargs.get("media"), output_bucket_name=kwargs.get("output_bucket_name"), output_key=kwargs.get("output_key"), output_encryption_kms_key_id=kwargs.get("output_encryption_kms_key_id"), settings=settings, model_settings=kwargs.get("model_settings"), job_execution_settings=kwargs.get("job_execution_settings"), content_redaction=kwargs.get("content_redaction"), identify_language=kwargs.get("identify_language"), language_options=kwargs.get("language_options"), ) self.transcriptions[name] = transcription_job_object return transcription_job_object.response_object("CREATE") def start_medical_transcription_job(self, **kwargs): name = kwargs.get("medical_transcription_job_name") if name in self.medical_transcriptions: raise ConflictException( message="The requested job name already exists. Use a different job name." ) settings = kwargs.get("settings") vocabulary_name = settings.get("VocabularyName") if settings else None if vocabulary_name and vocabulary_name not in self.medical_vocabularies: raise BadRequestException( message="The requested vocabulary couldn't be found. " "Check the vocabulary name and try your request again." ) transcription_job_object = FakeMedicalTranscriptionJob( region_name=self.region_name, medical_transcription_job_name=name, language_code=kwargs.get("language_code"), media_sample_rate_hertz=kwargs.get("media_sample_rate_hertz"), media_format=kwargs.get("media_format"), media=kwargs.get("media"), output_bucket_name=kwargs.get("output_bucket_name"), output_encryption_kms_key_id=kwargs.get("output_encryption_kms_key_id"), settings=settings, specialty=kwargs.get("specialty"), job_type=kwargs.get("type"), ) self.medical_transcriptions[name] = transcription_job_object return transcription_job_object.response_object("CREATE") def get_transcription_job(self, transcription_job_name): try: job = self.transcriptions[transcription_job_name] job.advance() # Fakes advancement through statuses. return job.response_object("GET") except KeyError: raise BadRequestException( message="The requested job couldn't be found. " "Check the job name and try your request again." ) def get_medical_transcription_job(self, medical_transcription_job_name): try: job = self.medical_transcriptions[medical_transcription_job_name] job.advance() # Fakes advancement through statuses. return job.response_object("GET") except KeyError: raise BadRequestException( message="The requested job couldn't be found. " "Check the job name and try your request again." ) def delete_transcription_job(self, transcription_job_name): try: del self.transcriptions[transcription_job_name] except KeyError: raise BadRequestException( message="The requested job couldn't be found. " "Check the job name and try your request again." ) def delete_medical_transcription_job(self, medical_transcription_job_name): try: del self.medical_transcriptions[medical_transcription_job_name] except KeyError: raise BadRequestException( message="The requested job couldn't be found. " "Check the job name and try your request again." ) def list_transcription_jobs( self, state_equals, job_name_contains, next_token, max_results ): jobs = list(self.transcriptions.values()) if state_equals: jobs = [job for job in jobs if job.status == state_equals] if job_name_contains: jobs = [ job for job in jobs if job_name_contains in job.transcription_job_name ] start_offset = int(next_token) if next_token else 0 end_offset = start_offset + ( max_results if max_results else 100 ) # Arbitrarily selected... jobs_paginated = jobs[start_offset:end_offset] response = { "TranscriptionJobSummaries": [ job.response_object("LIST") for job in jobs_paginated ] } if end_offset < len(jobs): response["NextToken"] = str(end_offset) if state_equals: response["Status"] = state_equals return response def list_medical_transcription_jobs( self, status, job_name_contains, next_token, max_results ): jobs = list(self.medical_transcriptions.values()) if status: jobs = [job for job in jobs if job.status == status] if job_name_contains: jobs = [ job for job in jobs if job_name_contains in job.medical_transcription_job_name ] start_offset = int(next_token) if next_token else 0 end_offset = start_offset + ( max_results if max_results else 100 ) # Arbitrarily selected... jobs_paginated = jobs[start_offset:end_offset] response = { "MedicalTranscriptionJobSummaries": [ job.response_object("LIST") for job in jobs_paginated ] } if end_offset < len(jobs): response["NextToken"] = str(end_offset) if status: response["Status"] = status return response def create_vocabulary(self, **kwargs): vocabulary_name = kwargs.get("vocabulary_name") language_code = kwargs.get("language_code") phrases = kwargs.get("phrases") vocabulary_file_uri = kwargs.get("vocabulary_file_uri") if ( phrases is not None and vocabulary_file_uri is not None or phrases is None and vocabulary_file_uri is None ): raise BadRequestException( message="Either Phrases or VocabularyFileUri field should be provided." ) if phrases is not None and len(phrases) < 1: raise BadRequestException( message="1 validation error detected: Value '[]' at 'phrases' failed to " "satisfy constraint: Member must have length greater than or " "equal to 1" ) if vocabulary_name in self.vocabularies: raise ConflictException( message="The requested vocabulary name already exists. " "Use a different vocabulary name." ) vocabulary_object = FakeVocabulary( account_id=self.account_id, region_name=self.region_name, vocabulary_name=vocabulary_name, language_code=language_code, phrases=phrases, vocabulary_file_uri=vocabulary_file_uri, ) self.vocabularies[vocabulary_name] = vocabulary_object return vocabulary_object.response_object("CREATE") def create_medical_vocabulary(self, **kwargs): vocabulary_name = kwargs.get("vocabulary_name") language_code = kwargs.get("language_code") vocabulary_file_uri = kwargs.get("vocabulary_file_uri") if vocabulary_name in self.medical_vocabularies: raise ConflictException( message="The requested vocabulary name already exists. " "Use a different vocabulary name." ) medical_vocabulary_object = FakeMedicalVocabulary( account_id=self.account_id, region_name=self.region_name, vocabulary_name=vocabulary_name, language_code=language_code, vocabulary_file_uri=vocabulary_file_uri, ) self.medical_vocabularies[vocabulary_name] = medical_vocabulary_object return medical_vocabulary_object.response_object("CREATE") def get_vocabulary(self, vocabulary_name): try: job = self.vocabularies[vocabulary_name] job.advance() # Fakes advancement through statuses. return job.response_object("GET") except KeyError: raise BadRequestException( message="The requested vocabulary couldn't be found. " "Check the vocabulary name and try your request again." ) def get_medical_vocabulary(self, vocabulary_name): try: job = self.medical_vocabularies[vocabulary_name] job.advance() # Fakes advancement through statuses. return job.response_object("GET") except KeyError: raise BadRequestException( message="The requested vocabulary couldn't be found. " "Check the vocabulary name and try your request again." ) def delete_vocabulary(self, vocabulary_name): try: del self.vocabularies[vocabulary_name] except KeyError: raise BadRequestException( message="The requested vocabulary couldn't be found. Check the vocabulary name and try your request again." ) def delete_medical_vocabulary(self, vocabulary_name): try: del self.medical_vocabularies[vocabulary_name] except KeyError: raise BadRequestException( message="The requested vocabulary couldn't be found. Check the vocabulary name and try your request again." ) def list_vocabularies(self, state_equals, name_contains, next_token, max_results): vocabularies = list(self.vocabularies.values()) if state_equals: vocabularies = [ vocabulary for vocabulary in vocabularies if vocabulary.status == state_equals ] if name_contains: vocabularies = [ vocabulary for vocabulary in vocabularies if name_contains in vocabulary.vocabulary_name ] start_offset = int(next_token) if next_token else 0 end_offset = start_offset + ( max_results if max_results else 100 ) # Arbitrarily selected... vocabularies_paginated = vocabularies[start_offset:end_offset] response = { "Vocabularies": [ vocabulary.response_object("LIST") for vocabulary in vocabularies_paginated ] } if end_offset < len(vocabularies): response["NextToken"] = str(end_offset) if state_equals: response["Status"] = state_equals return response def list_medical_vocabularies( self, state_equals, name_contains, next_token, max_results ): vocabularies = list(self.medical_vocabularies.values()) if state_equals: vocabularies = [ vocabulary for vocabulary in vocabularies if vocabulary.status == state_equals ] if name_contains: vocabularies = [ vocabulary for vocabulary in vocabularies if name_contains in vocabulary.vocabulary_name ] start_offset = int(next_token) if next_token else 0 end_offset = start_offset + ( max_results if max_results else 100 ) # Arbitrarily selected... vocabularies_paginated = vocabularies[start_offset:end_offset] response = { "Vocabularies": [ vocabulary.response_object("LIST") for vocabulary in vocabularies_paginated ] } if end_offset < len(vocabularies): response["NextToken"] = str(end_offset) if state_equals: response["Status"] = state_equals return response transcribe_backends = BackendDict(TranscribeBackend, "transcribe")