Halaman ini diterjemahkan oleh Cloud Translation API.

Menerjemahkan teks dengan model dalam batch (khusus edisi Advanced)

Terjemahkan teks dalam volume besar dengan model.

Jelajahi lebih lanjut

Untuk dokumentasi mendetail yang menyertakan contoh kode ini, lihat artikel berikut:

Permintaan batch (Advanced)

Contoh kode

Sebelum mencoba contoh ini, ikuti petunjuk penyiapan Go di panduan memulai Cloud Translation menggunakan library klien. Untuk mengetahui informasi selengkapnya, silakan melihat dokumentasi referensi API Go Cloud Translation.

Untuk melakukan autentikasi ke Cloud Translation, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal.

import (
	"context"
	"fmt"
	"io"

	translate "cloud.google.com/go/translate/apiv3"
	"cloud.google.com/go/translate/apiv3/translatepb"
)

// batchTranslateTextWithModel translates a large volume of text in asynchronous batch mode.
func batchTranslateTextWithModel(w io.Writer, projectID string, location string, inputURI string, outputURI string, sourceLang string, targetLang string, modelID string) error {
	// projectID := "my-project-id"
	// location := "us-central1"
	// inputURI := "gs://cloud-samples-data/text.txt"
	// outputURI := "gs://YOUR_BUCKET_ID/path_to_store_results/"
	// sourceLang := "en"
	// targetLang := "de"
	// modelID := "your-model-id"

	ctx := context.Background()
	client, err := translate.NewTranslationClient(ctx)
	if err != nil {
		return fmt.Errorf("NewTranslationClient: %w", err)
	}
	defer client.Close()

	req := &translatepb.BatchTranslateTextRequest{
		Parent:              fmt.Sprintf("projects/%s/locations/%s", projectID, location),
		SourceLanguageCode:  sourceLang,
		TargetLanguageCodes: []string{targetLang},
		InputConfigs: []*translatepb.InputConfig{
			{
				Source: &translatepb.InputConfig_GcsSource{
					GcsSource: &translatepb.GcsSource{InputUri: inputURI},
				},
				// Optional. Can be "text/plain" or "text/html".
				MimeType: "text/plain",
			},
		},
		OutputConfig: &translatepb.OutputConfig{
			Destination: &translatepb.OutputConfig_GcsDestination{
				GcsDestination: &translatepb.GcsDestination{
					OutputUriPrefix: outputURI,
				},
			},
		},
		Models: map[string]string{
			targetLang: fmt.Sprintf("projects/%s/locations/%s/models/%s", projectID, location, modelID),
		},
	}

	// The BatchTranslateText operation is async.
	op, err := client.BatchTranslateText(ctx, req)
	if err != nil {
		return fmt.Errorf("BatchTranslateText: %w", err)
	}
	fmt.Fprintf(w, "Processing operation name: %q\n", op.Name())

	resp, err := op.Wait(ctx)
	if err != nil {
		return fmt.Errorf("Wait: %w", err)
	}

	fmt.Fprintf(w, "Total characters: %v\n", resp.GetTotalCharacters())
	fmt.Fprintf(w, "Translated characters: %v\n", resp.GetTranslatedCharacters())

	return nil
}

Sebelum mencoba contoh ini, ikuti petunjuk penyiapan Java di panduan memulai Cloud Translation menggunakan library klien. Untuk mengetahui informasi selengkapnya, silakan melihat dokumentasi referensi API Java Cloud Translation.

Untuk melakukan autentikasi ke Cloud Translation, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal.

import com.google.api.gax.longrunning.OperationFuture;
import com.google.cloud.translate.v3.BatchTranslateMetadata;
import com.google.cloud.translate.v3.BatchTranslateResponse;
import com.google.cloud.translate.v3.BatchTranslateTextRequest;
import com.google.cloud.translate.v3.GcsDestination;
import com.google.cloud.translate.v3.GcsSource;
import com.google.cloud.translate.v3.InputConfig;
import com.google.cloud.translate.v3.LocationName;
import com.google.cloud.translate.v3.OutputConfig;
import com.google.cloud.translate.v3.TranslationServiceClient;
import java.io.IOException;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.ThreadLocalRandom;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.TimeoutException;

public class BatchTranslateTextWithModel {

  public static void batchTranslateTextWithModel()
      throws InterruptedException, ExecutionException, IOException, TimeoutException {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "YOUR-PROJECT-ID";
    // Supported Languages: https://cloud.google.com/translate/docs/languages
    String sourceLanguage = "your-source-language";
    String targetLanguage = "your-target-language";
    String inputUri = "gs://your-gcs-bucket/path/to/input/file.txt";
    String outputUri = "gs://your-gcs-bucket/path/to/results/";
    String modelId = "YOUR-MODEL-ID";
    batchTranslateTextWithModel(
        projectId, sourceLanguage, targetLanguage, inputUri, outputUri, modelId);
  }

  // Batch translate text using AutoML Translation model
  public static void batchTranslateTextWithModel(
      String projectId,
      String sourceLanguage,
      String targetLanguage,
      String inputUri,
      String outputUri,
      String modelId)
      throws IOException, ExecutionException, InterruptedException, TimeoutException {

    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (TranslationServiceClient client = TranslationServiceClient.create()) {
      // Supported Locations: `global`, [glossary location], or [model location]
      // Glossaries must be hosted in `us-central1`
      // Custom Models must use the same location as your model. (us-central1)
      String location = "us-central1";
      LocationName parent = LocationName.of(projectId, location);

      // Configure the source of the file from a GCS bucket
      GcsSource gcsSource = GcsSource.newBuilder().setInputUri(inputUri).build();
      // Supported Mime Types: https://cloud.google.com/translate/docs/supported-formats
      InputConfig inputConfig =
          InputConfig.newBuilder().setGcsSource(gcsSource).setMimeType("text/plain").build();

      // Configure where to store the output in a GCS bucket
      GcsDestination gcsDestination =
          GcsDestination.newBuilder().setOutputUriPrefix(outputUri).build();
      OutputConfig outputConfig =
          OutputConfig.newBuilder().setGcsDestination(gcsDestination).build();

      // Configure the model used in the request
      String modelPath =
          String.format("projects/%s/locations/%s/models/%s", projectId, location, modelId);

      // Build the request that will be sent to the API
      BatchTranslateTextRequest request =
          BatchTranslateTextRequest.newBuilder()
              .setParent(parent.toString())
              .setSourceLanguageCode(sourceLanguage)
              .addTargetLanguageCodes(targetLanguage)
              .addInputConfigs(inputConfig)
              .setOutputConfig(outputConfig)
              .putModels(targetLanguage, modelPath)
              .build();

      // Start an asynchronous request
      OperationFuture<BatchTranslateResponse, BatchTranslateMetadata> future =
          client.batchTranslateTextAsync(request);

      System.out.println("Waiting for operation to complete...");

      // random number between 300 - 450 (maximum allowed seconds)
      long randomNumber = ThreadLocalRandom.current().nextInt(450, 600);
      BatchTranslateResponse response = future.get(randomNumber, TimeUnit.SECONDS);

      // Display the translation for each input text provided
      System.out.printf("Total Characters: %s\n", response.getTotalCharacters());
      System.out.printf("Translated Characters: %s\n", response.getTranslatedCharacters());
    }
  }
}

Sebelum mencoba contoh ini, ikuti petunjuk penyiapan Node.js di panduan memulai Cloud Translation menggunakan library klien. Untuk mengetahui informasi selengkapnya, silakan melihat dokumentasi referensi API Node.js Cloud Translation.

Untuk melakukan autentikasi ke Cloud Translation, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal.

/**
 * TODO(developer): Uncomment these variables before running the sample.
 */
// const projectId = 'YOUR_PROJECT_ID';
// const location = 'us-central1';
// const inputUri = 'gs://cloud-samples-data/text.txt';
// const outputUri = 'gs://YOUR_BUCKET_ID/path_to_store_results/';
// const modelId = 'YOUR_MODEL_ID';

// Imports the Google Cloud Translation library
const {TranslationServiceClient} = require('@google-cloud/translate');

// Instantiates a client
const client = new TranslationServiceClient();
async function batchTranslateTextWithModel() {
  // Construct request
  const request = {
    parent: `projects/${projectId}/locations/${location}`,
    sourceLanguageCode: 'en',
    targetLanguageCodes: ['ja'],
    inputConfigs: [
      {
        mimeType: 'text/plain', // mime types: text/plain, text/html
        gcsSource: {
          inputUri: inputUri,
        },
      },
    ],
    outputConfig: {
      gcsDestination: {
        outputUriPrefix: outputUri,
      },
    },
    models: {
      ja: `projects/${projectId}/locations/${location}/models/${modelId}`,
    },
  };

  const options = {timeout: 240000};
  // Create a job using a long-running operation
  const [operation] = await client.batchTranslateText(request, options);

  // Wait for the operation to complete
  const [response] = await operation.promise();

  // Display the translation for each input text provided
  console.log(`Total Characters: ${response.totalCharacters}`);
  console.log(`Translated Characters: ${response.translatedCharacters}`);
}

batchTranslateTextWithModel();

Sebelum mencoba contoh ini, ikuti petunjuk penyiapan PHP di panduan memulai Cloud Translation menggunakan library klien. Untuk mengetahui informasi selengkapnya, silakan melihat dokumentasi referensi API PHP Cloud Translation.

Untuk melakukan autentikasi ke Cloud Translation, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal.

use Google\Cloud\Translate\V3\BatchTranslateTextRequest;
use Google\Cloud\Translate\V3\Client\TranslationServiceClient;
use Google\Cloud\Translate\V3\GcsDestination;
use Google\Cloud\Translate\V3\GcsSource;
use Google\Cloud\Translate\V3\InputConfig;
use Google\Cloud\Translate\V3\OutputConfig;

/**
 * @param string $inputUri      Path to to source input (e.g. "gs://cloud-samples-data/text.txt").
 * @param string $outputUri     Path to store results (e.g. "gs://YOUR_BUCKET_ID/results/").
 * @param string $projectId     Your Google Cloud project ID.
 * @param string $location      Project location (e.g. us-central1)
 * @param string $targetLanguage    Language to translate to.
 * @param string $sourceLanguage    Language of the source.
 * @param string $modelId       Your model ID.
 */
function v3_batch_translate_text_with_model(
    string $inputUri,
    string $outputUri,
    string $projectId,
    string $location,
    string $targetLanguage,
    string $sourceLanguage,
    string $modelId
): void {
    $translationServiceClient = new TranslationServiceClient();

    $modelPath = sprintf(
        'projects/%s/locations/%s/models/%s',
        $projectId,
        $location,
        $modelId
    );
    $targetLanguageCodes = [$targetLanguage];
    $gcsSource = (new GcsSource())
        ->setInputUri($inputUri);

    // Optional. Can be "text/plain" or "text/html".
    $mimeType = 'text/plain';
    $inputConfigsElement = (new InputConfig())
        ->setGcsSource($gcsSource)
        ->setMimeType($mimeType);
    $inputConfigs = [$inputConfigsElement];
    $gcsDestination = (new GcsDestination())
        ->setOutputUriPrefix($outputUri);
    $outputConfig = (new OutputConfig())
        ->setGcsDestination($gcsDestination);
    $formattedParent = $translationServiceClient->locationName($projectId, $location);
    $models = ['ja' => $modelPath];

    try {
        $request = (new BatchTranslateTextRequest())
            ->setParent($formattedParent)
            ->setSourceLanguageCode($sourceLanguage)
            ->setTargetLanguageCodes($targetLanguageCodes)
            ->setInputConfigs($inputConfigs)
            ->setOutputConfig($outputConfig)
            ->setModels($models);
        $operationResponse = $translationServiceClient->batchTranslateText($request);
        $operationResponse->pollUntilComplete();
        if ($operationResponse->operationSucceeded()) {
            $response = $operationResponse->getResult();
            // Display the translation for each input text provided
            printf('Total Characters: %s' . PHP_EOL, $response->getTotalCharacters());
            printf('Translated Characters: %s' . PHP_EOL, $response->getTranslatedCharacters());
        } else {
            $error = $operationResponse->getError();
            print($error->getMessage());
        }
    } finally {
        $translationServiceClient->close();
    }
}

Sebelum mencoba contoh ini, ikuti petunjuk penyiapan Python di panduan memulai Cloud Translation menggunakan library klien. Untuk mengetahui informasi selengkapnya, silakan melihat dokumentasi referensi API Python Cloud Translation.

Untuk melakukan autentikasi ke Cloud Translation, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal.

from google.cloud import translate


def batch_translate_text_with_model(
    input_uri: str = "gs://YOUR_BUCKET_ID/path/to/your/file.txt",
    output_uri: str = "gs://YOUR_BUCKET_ID/path/to/save/results/",
    project_id: str = "YOUR_PROJECT_ID",
    model_id: str = "YOUR_MODEL_ID",
) -> translate.TranslationServiceClient:
    """Batch translate text using Translation model.
    Model can be AutoML or General[built-in] model.

    Args:
        input_uri: The input file to translate.
        output_uri: The output file to save the translation results.
        project_id: The ID of the GCP project that owns the model.
        model_id: The model ID.

    Returns:
        The response from the batch translation API.
    """

    client = translate.TranslationServiceClient()

    # Supported file types: https://cloud.google.com/translate/docs/supported-formats
    gcs_source = {"input_uri": input_uri}
    location = "us-central1"

    input_configs_element = {
        "gcs_source": gcs_source,
        "mime_type": "text/plain",  # Can be "text/plain" or "text/html".
    }
    gcs_destination = {"output_uri_prefix": output_uri}
    output_config = {"gcs_destination": gcs_destination}
    parent = f"projects/{project_id}/locations/{location}"

    model_path = "projects/{}/locations/{}/models/{}".format(
        project_id, location, model_id  # The location of AutoML model.
    )

    # Supported language codes: https://cloud.google.com/translate/docs/languages
    models = {"ja": model_path}  # takes a target lang as key.

    operation = client.batch_translate_text(
        request={
            "parent": parent,
            "source_language_code": "en",
            "target_language_codes": ["ja"],  # Up to 10 language codes here.
            "input_configs": [input_configs_element],
            "output_config": output_config,
            "models": models,
        }
    )

    print("Waiting for operation to complete...")
    response = operation.result()

    # Display the translation for each input text provided.
    print(f"Total Characters: {response.total_characters}")
    print(f"Translated Characters: {response.translated_characters}")

    return response

Langkah berikutnya

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