使用术语表和模型批量翻译文本（仅限高级版）

使用术语表和模型翻译大量文本。

深入探索

如需查看包含此代码示例的详细文档，请参阅以下内容：

• 批量请求（高级）

代码示例

Go

试用此示例之前，请按照 Cloud Translation 快速入门：使用客户端库中的 Go 设置说明进行操作。如需了解详情，请参阅 Cloud Translation Go API 参考文档。

如需向 Cloud Translation 进行身份验证，请设置应用默认凭据。如需了解详情，请参阅为本地开发环境设置身份验证。

在 GitHub 上查看 反馈

import (
	"context"
	"fmt"
	"io"

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

// batchTranslateTextWithGlossaryAndModel translates a large volume of text in asynchronous batch mode.
func batchTranslateTextWithGlossaryAndModel(w io.Writer, projectID string, location string, inputURI string, outputURI string, sourceLang string, targetLang string, glossaryID 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 := "ja"
	// glossaryID := "your-glossary-id"
	// 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",
			},
		},
		Glossaries: map[string]*translatepb.TranslateTextGlossaryConfig{
			targetLang: {
				Glossary: fmt.Sprintf("projects/%s/locations/%s/glossaries/%s", projectID, location, glossaryID),
			},
		},
		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
}

Java

试用此示例之前，请按照 Cloud Translation 快速入门：使用客户端库中的 Java 设置说明进行操作。如需了解详情，请参阅 Cloud Translation Java API 参考文档。

如需向 Cloud Translation 进行身份验证，请设置应用默认凭据。如需了解详情，请参阅为本地开发环境设置身份验证。

在 GitHub 上查看 反馈

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.GlossaryName;
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.TranslateTextGlossaryConfig;
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 BatchTranslateTextWithGlossaryAndModel {

  public static void batchTranslateTextWithGlossaryAndModel()
      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 glossaryId = "your-glossary-display-name";
    String modelId = "YOUR-MODEL-ID";
    batchTranslateTextWithGlossaryAndModel(
        projectId, sourceLanguage, targetLanguage, inputUri, outputUri, glossaryId, modelId);
  }

  // Batch translate text with Model and Glossary
  public static void batchTranslateTextWithGlossaryAndModel(
      String projectId,
      String sourceLanguage,
      String targetLanguage,
      String inputUri,
      String outputUri,
      String glossaryId,
      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 glossary used in the request
      GlossaryName glossaryName = GlossaryName.of(projectId, location, glossaryId);
      TranslateTextGlossaryConfig glossaryConfig =
          TranslateTextGlossaryConfig.newBuilder().setGlossary(glossaryName.toString()).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)
              .putGlossaries(targetLanguage, glossaryConfig)
              .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());
    }
  }
}

Node.js

试用此示例之前，请按照 Cloud Translation 快速入门：使用客户端库中的 Node.js 设置说明进行操作。如需了解详情，请参阅 Cloud Translation Node.js API 参考文档。

如需向 Cloud Translation 进行身份验证，请设置应用默认凭据。如需了解详情，请参阅为本地开发环境设置身份验证。

在 GitHub 上查看 反馈

/**
 * 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 glossaryId = 'YOUR_GLOSSARY_ID';
// 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 batchTranslateTextWithGlossaryAndModel() {
  // 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,
      },
    },
    glossaries: {
      ja: {
        glossary: `projects/${projectId}/locations/${location}/glossaries/${glossaryId}`,
      },
    },
    models: {
      ja: `projects/${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 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}`);
}

batchTranslateTextWithGlossaryAndModel();

PHP

试用此示例之前，请按照 Cloud Translation 快速入门：使用客户端库中的 PHP 设置说明进行操作。如需了解详情，请参阅 Cloud Translation PHP API 参考文档。

如需向 Cloud Translation 进行身份验证，请设置应用默认凭据。如需了解详情，请参阅为本地开发环境设置身份验证。

在 GitHub 上查看 反馈

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

/**
 * @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.
 * @param string $glossaryId    Your glossary ID.
 */
function v3_batch_translate_text_with_glossary_and_model(
    string $inputUri,
    string $outputUri,
    string $projectId,
    string $location,
    string $targetLanguage,
    string $sourceLanguage,
    string $modelId,
    string $glossaryId
): void {
    $translationServiceClient = new TranslationServiceClient();

    $glossaryPath = $translationServiceClient->glossaryName(
        $projectId,
        $location,
        $glossaryId
    );
    $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];
    $glossariesItem = (new TranslateTextGlossaryConfig())
        ->setGlossary($glossaryPath);
    $glossaries = ['ja' => $glossariesItem];

    try {
        $operationResponse = $translationServiceClient->batchTranslateText(
            $formattedParent,
            $sourceLanguage,
            $targetLanguageCodes,
            $inputConfigs,
            $outputConfig,
            [
                'models' => $models,
                'glossaries' => $glossaries
            ]
        );
        $operationResponse->pollUntilComplete();
        if ($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();
    }
}

Python

试用此示例之前，请按照 Cloud Translation 快速入门：使用客户端库中的 Python 设置说明进行操作。如需了解详情，请参阅 Cloud Translation Python API 参考文档。

如需向 Cloud Translation 进行身份验证，请设置应用默认凭据。如需了解详情，请参阅为本地开发环境设置身份验证。

在 GitHub 上查看 反馈

from google.cloud import translate

def batch_translate_text_with_glossary_and_model(
    input_uri: str,
    output_uri: str,
    project_id: str,
    model_id: str,
    glossary_id: str,
) -> translate.TranslateTextResponse:
    """Batch translate text with Glossary and Translation model.
    Args:
        input_uri: The input text to be translated.
        output_uri: The output text to be translated.
        project_id: The ID of the GCP project that owns the model.
        model_id: The ID of the model
        glossary_id: The ID of the glossary

    Returns:
        The translated text.
    """

    client = translate.TranslationServiceClient()

    # Supported language codes: https://cloud.google.com/translate/docs/languages
    location = "us-central1"

    target_language_codes = ["ja"]
    gcs_source = {"input_uri": input_uri}

    # Optional. Can be "text/plain" or "text/html".
    mime_type = "text/plain"
    input_configs_element = {"gcs_source": gcs_source, "mime_type": mime_type}
    input_configs = [input_configs_element]
    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, "us-central1", model_id
    )
    models = {"ja": model_path}

    glossary_path = client.glossary_path(
        project_id, "us-central1", glossary_id  # The location of the glossary
    )

    glossary_config = translate.TranslateTextGlossaryConfig(glossary=glossary_path)
    glossaries = {"ja": glossary_config}  # target lang as key

    operation = client.batch_translate_text(
        request={
            "parent": parent,
            "source_language_code": "en",
            "target_language_codes": target_language_codes,
            "input_configs": input_configs,
            "output_config": output_config,
            "models": models,
            "glossaries": glossaries,
        }
    )

    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

后续步骤

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