Source code for airflow.contrib.operators.gcp_translate_speech_operator

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from google.protobuf.json_format import MessageToDict

from airflow import AirflowException
from airflow.contrib.hooks.gcp_speech_to_text_hook import GCPSpeechToTextHook
from airflow.contrib.hooks.gcp_translate_hook import CloudTranslateHook
from airflow.models import BaseOperator
from airflow.utils.decorators import apply_defaults

[docs]class GcpTranslateSpeechOperator(BaseOperator): """ Recognizes speech in audio input and translates it. Note that it uses the first result from the recognition api response - the one with the highest confidence In order to see other possible results please use :ref:`howto/operator:GcpSpeechToTextRecognizeSpeechOperator` and :ref:`howto/operator:CloudTranslateTextOperator` separately .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:GcpTranslateSpeechOperator` See Execute method returns string object with the translation This is a list of dictionaries queried value. Dictionary typically contains three keys (though not all will be present in all cases). * ``detectedSourceLanguage``: The detected language (as an ISO 639-1 language code) of the text. * ``translatedText``: The translation of the text into the target language. * ``input``: The corresponding input value. * ``model``: The model used to translate the text. Dictionary is set as XCom return value. :param audio: audio data to be recognized. See more: :type audio: dict or :param config: information to the recognizer that specifies how to process the request. See more: :type config: dict or :param target_language: The language to translate results into. This is required by the API and defaults to the target language of the current instance. Check the list of available languages here: :type target_language: str :param format_: (Optional) One of ``text`` or ``html``, to specify if the input text is plain text or HTML. :type format_: str or None :param source_language: (Optional) The language of the text to be translated. :type source_language: str or None :param model: (Optional) The model used to translate the text, such as ``'base'`` or ``'nmt'``. :type model: str or None :param project_id: Optional, Google Cloud Platform Project ID where the Compute Engine Instance exists. If set to None or missing, the default project_id from the GCP connection is used. :type project_id: str :param gcp_conn_id: Optional, The connection ID used to connect to Google Cloud Platform. Defaults to 'google_cloud_default'. :type gcp_conn_id: str """ # [START translate_speech_template_fields]
[docs] template_fields = ('target_language', 'format_', 'source_language', 'model', 'project_id', 'gcp_conn_id')
# [END translate_speech_template_fields] @apply_defaults def __init__( self, audio, config, target_language, format_, source_language, model, project_id=None, gcp_conn_id='google_cloud_default', *args, **kwargs ): super(GcpTranslateSpeechOperator, self).__init__(*args, **kwargs) = audio self.config = config self.target_language = target_language self.format_ = format_ self.source_language = source_language self.model = model self.project_id = project_id self.gcp_conn_id = gcp_conn_id
[docs] def execute(self, context): _speech_to_text_hook = GCPSpeechToTextHook(gcp_conn_id=self.gcp_conn_id) _translate_hook = CloudTranslateHook(gcp_conn_id=self.gcp_conn_id) recognize_result = _speech_to_text_hook.recognize_speech( config=self.config, ) recognize_dict = MessageToDict(recognize_result)"Recognition operation finished") if len(recognize_dict['results']) == 0:"No recognition results") return {} self.log.debug("recognition result: %s", recognize_dict) try: transcript = recognize_dict['results'][0]['alternatives'][0]['transcript'] except KeyError as key: raise AirflowException("Wrong response '{}' returned - it should contain {} field" .format(recognize_dict, key)) try: translation = _translate_hook.translate( values=transcript, target_language=self.target_language, format_=self.format_, source_language=self.source_language, model=self.model )'translated output: %s', translation) return translation except ValueError as e: self.log.error('An error has been thrown from translate speech method:') self.log.error(e) raise AirflowException(e)

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