Run a batch translation using the Cloud Translation connector

This tutorial shows you how to create a workflow that uses the Cloud Translation API connector to translate files to other languages in asynchronous batch mode. This provides real-time output as the inputs are being processed.

Create an input Cloud Storage bucket and files

You can use Cloud Storage to store objects. Objects are immutable pieces of data consisting of a file of any format, and are stored in containers called buckets.

1. Create a Cloud Storage bucket to hold the files to translate:

   BUCKET_INPUT=${GOOGLE_CLOUD_PROJECT}-input-files
   gcloud storage buckets create gs://${BUCKET_INPUT}

2. Create two files in English and upload them to the input bucket:

   echo "Hello World!" > file1.txt
   gcloud storage cp file1.txt gs://${BUCKET_INPUT}
   echo "Workflows connectors simplify calling services." > file2.txt
   gcloud storage cp file2.txt gs://${BUCKET_INPUT}

Deploy and execute the workflow

A workflow is made up of a series of steps described using the Workflows syntax, which can be written in either YAML or JSON format. This is the workflow's definition. After creating a workflow, you deploy it to make it available for execution.

1. Create a text file with the filename workflow.yaml and with the following content:

   main:
     steps:
     - init:
         assign:
         - projectId: ${sys.get_env("GOOGLE_CLOUD_PROJECT_ID")}
         - location: ${sys.get_env("GOOGLE_CLOUD_LOCATION")}
         - inputBucketName: ${projectId + "-input-files"}
         - outputBucketName: ${projectId + "-output-files-" + string(int(sys.now()))}
     - createOutputBucket:
           call: googleapis.storage.v1.buckets.insert
           args:
             project: ${projectId}
             body:
               name: ${outputBucketName}
     - batchTranslateText:
         call: googleapis.translate.v3beta1.projects.locations.batchTranslateText
         args:
             parent: ${"projects/" + projectId + "/locations/" + location}
             body:
                 inputConfigs:
                   gcsSource:
                     inputUri: ${"gs://" + inputBucketName + "/*"}
                 outputConfig:
                     gcsDestination:
                       outputUriPrefix: ${"gs://" + outputBucketName + "/"}
                 sourceLanguageCode: "en"
                 targetLanguageCodes: ["es", "fr"]
         result: batchTranslateTextResult

   The workflow assigns variables, creates an output bucket, and initiates the translation of the files, saving the results to the output bucket.

2. After creating the workflow, deploy it:

   gcloud workflows deploy batch-translation --source=workflow.yaml

3. Execute the workflow:

   gcloud workflows execute batch-translation

4. To view the workflow status, you can run the returned command. For example:

   gcloud workflows executions describe eb4a6239-cffa-4672-81d8-d4caef7d8424 /
     --workflow batch-translation /
     --location us-central1

   The workflow should be ACTIVE. After a few minutes, the translated files (in French and Spanish) are uploaded to the output bucket.

List objects in the output bucket

You can confirm that the workflow worked as expected by listing the objects in your output bucket.

1. Retrieve your output bucket name:

   gcloud storage ls

   The output is similar to the following:

   gs://PROJECT_ID-input-files/
   gs://PROJECT_ID-output-files-TIMESTAMP/

2. List the objects in your output bucket:

   gcloud storage ls gs://PROJECT_ID-output-files-TIMESTAMP/** --recursive

   After a few minutes, the translated files, two of each in French and Spanish, are listed.