批次要求 (進階)

批次翻譯可讓您翻譯大量文字 (每個批次的限制為 100 個檔案),並且以離線指令翻譯為最多 10 種不同的目標語言。總體內容大小不得超過 100M Unicode 碼點,且必須使用 UTF-8 編碼。

事前準備

如要開始使用 Cloud Translation API,您必須擁有已啟用 Cloud Translation API 的專案,並具備適當的憑證。您也可以安裝常用程式設計語言的用戶端程式庫,協助您呼叫 API。詳情請參閱「設定」頁面。

權限

如要進行批次翻譯,除了 Cloud Translation 權限,您也必須有權存取 Cloud Storage 值區。批次翻譯輸入檔案會從 Cloud Storage 值區讀取,輸出檔案則會寫入 Cloud Storage 值區。舉例來說,如要從值區讀取輸入檔案,您必須至少具備該值區的讀取物件權限 (由 roles/storage.objectViewer 角色提供)。如要進一步瞭解 Cloud Storage 角色,請參閱 Cloud Storage 說明文件

輸入檔案

僅支援以下兩種 MIME 類型:text/html (HTML) 和 text/plain (.tsv 和 .txt)。

使用 TSV 檔案

如果副檔名為 TSV,則檔案可以包含一或二個資料欄。第一個資料欄 (選用) 是文字要求的 ID。如果第一個資料欄遺失,Google 會使用輸入檔案中的資料列編號 (從 0 開始) 作為輸出檔案中的 ID。第二個資料欄是要翻譯的實際文字。為獲得最佳結果,每個資料列應小於或等於 10K Unicode 碼點,否則可能會傳回錯誤。

使用文字或 HTML

其他支援的副檔名為文字檔案 (.txt) 或 HTML,系統會將其視為一個大型文字區塊。

批次要求

發出批次翻譯要求時,您必須提供以下兩者的路徑:含有待翻譯內容的輸入設定檔 (InputConfig) 及最終翻譯的輸出位置 (OutputConfig)。您至少需要兩個不同的 Cloud Storage 值區。來源值區包含待翻譯的內容,目標值區則包含翻譯後產生的檔案。在翻譯程序開始之前,目標資料夾必須是空的。

處理要求時,我們會即時將結果寫入輸出位置。即使您在中途取消要求,系統仍會在 Cloud Storage 輸出位置產生輸入檔案層級的部分輸出內容。因此,您仍須支付已翻譯字元數的費用。

REST

以下範例顯示兩個送交翻譯的輸入檔案。

使用任何要求資料之前,請先替換以下項目:

  • PROJECT_NUMBER_OR_ID: Google Cloud 專案的數值或英數字元 ID

HTTP 方法和網址:

POST https://translation.googleapis.com/v3/projects/PROJECT_NUMBER_OR_ID/locations/us-central1:batchTranslateText

JSON 要求主體:

{
  "sourceLanguageCode": "en",
  "targetLanguageCodes": ["es", "fr"],
  "inputConfigs": [
   {
      "gcsSource": {
        "inputUri": "gs://bucket-name-source/input-file-name1"
      }
    },
    {
      "gcsSource": {
        "inputUri": "gs://bucket-name-source/input-file-name2"
      }
    }
  ],
  "outputConfig": {
      "gcsDestination": {
        "outputUriPrefix": "gs://bucket-name-destination/"
      }
   }
}

如要傳送要求,請展開以下其中一個選項:

您應該會收到如下的 JSON 回應:

{
  "name": "projects/project-number/locations/us-central1/operations/20191107-08251564068323-5d3895ce-0000-2067-864c-001a1136fb06",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.translation.v3.BatchTranslateMetadata",
    "state": "RUNNING"
  }
}
回應會包含一項長時間執行作業的 ID。

Go

在試用這個範例之前,請先按照Go使用用戶端程式庫的 Cloud Translation 快速入門導覽課程中的操作說明進行設定。詳情請參閱 Cloud Translation Go API 參考說明文件

如要向 Cloud Translation 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

import (
	"context"
	"fmt"
	"io"

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

// batchTranslateText translates a large volume of text in asynchronous batch mode.
func batchTranslateText(w io.Writer, projectID string, location string, inputURI string, outputURI string, sourceLang string, targetLang 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"

	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,
				},
			},
		},
	}

	// 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

在試用這個範例之前,請先按照Java使用用戶端程式庫的 Cloud Translation 快速入門導覽課程中的操作說明進行設定。詳情請參閱 Cloud Translation Java API 參考說明文件

如要向 Cloud Translation 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

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 BatchTranslateText {

  public static void batchTranslateText()
      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/";
    batchTranslateText(projectId, sourceLanguage, targetLanguage, inputUri, outputUri);
  }

  // Batch translate text
  public static void batchTranslateText(
      String projectId,
      String sourceLanguage,
      String targetLanguage,
      String inputUri,
      String outputUri)
      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: `us-central1`
      LocationName parent = LocationName.of(projectId, "us-central1");

      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();

      GcsDestination gcsDestination =
          GcsDestination.newBuilder().setOutputUriPrefix(outputUri).build();
      OutputConfig outputConfig =
          OutputConfig.newBuilder().setGcsDestination(gcsDestination).build();

      BatchTranslateTextRequest request =
          BatchTranslateTextRequest.newBuilder()
              .setParent(parent.toString())
              .setSourceLanguageCode(sourceLanguage)
              .addTargetLanguageCodes(targetLanguage)
              .addInputConfigs(inputConfig)
              .setOutputConfig(outputConfig)
              .build();

      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);

      System.out.printf("Total Characters: %s\n", response.getTotalCharacters());
      System.out.printf("Translated Characters: %s\n", response.getTranslatedCharacters());
    }
  }
}

Node.js

在試用這個範例之前,請先按照Node.js使用用戶端程式庫的 Cloud Translation 快速入門導覽課程中的操作說明進行設定。詳情請參閱 Cloud Translation Node.js API 參考說明文件

如要向 Cloud Translation 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

/**
 * 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/';

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

// Instantiates a client
const translationClient = new TranslationServiceClient();
async function batchTranslateText() {
  // 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,
      },
    },
  };

  // Setup timeout for long-running operation. Timeout specified in ms.
  const options = {timeout: 240000};
  // Batch translate text using a long-running operation with a timeout of 240000ms.
  const [operation] = await translationClient.batchTranslateText(
    request,
    options
  );

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

  console.log(`Total Characters: ${response.totalCharacters}`);
  console.log(`Translated Characters: ${response.translatedCharacters}`);
}

batchTranslateText();

Python

在試用這個範例之前,請先按照Python使用用戶端程式庫的 Cloud Translation 快速入門導覽課程中的操作說明進行設定。詳情請參閱 Cloud Translation Python API 參考說明文件

如要向 Cloud Translation 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

from google.cloud import translate


def batch_translate_text(
    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",
    timeout: int = 180,
) -> translate.TranslateTextResponse:
    """Translates a batch of texts on GCS and stores the result in a GCS location.

    Args:
        input_uri: The input URI of the texts to be translated.
        output_uri: The output URI of the translated texts.
        project_id: The ID of the project that owns the destination bucket.
        timeout: The timeout for this batch translation operation.

    Returns:
        The translated texts.
    """

    client = translate.TranslationServiceClient()

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

    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}"

    # Supported language codes: https://cloud.google.com/translate/docs/languages
    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,
        }
    )

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

    print(f"Total Characters: {response.total_characters}")
    print(f"Translated Characters: {response.translated_characters}")

    return response

其他語言

C#: 請按照用戶端程式庫頁面的 C# 設定說明操作, 然後前往 .NET 適用的 Cloud Translation 參考說明文件

PHP: 請按照用戶端程式庫頁面的 PHP 設定說明 操作,然後前往 PHP 適用的 Cloud Translation 參考說明文件

Ruby: 請按照用戶端程式庫頁面的 Ruby 設定說明 操作,然後前往 Ruby 適用的 Cloud Translation 參考文件

使用 AutoML 模型發出批次要求

您可以在批次要求中使用自訂模型。如果涉及多種目標語言,可能會發生各種情況。

指定目標語言的 AutoML 模型

REST

這個範例說明如何為目標語言指定自訂模型。

使用任何要求資料之前,請先替換以下項目:

  • PROJECT_NUMBER_OR_ID: Google Cloud 專案的數值或英數字元 ID

HTTP 方法和網址:

POST https://translation.googleapis.com/v3/projects/PROJECT_NUMBER_OR_ID/locations/us-central1:batchTranslateText

JSON 要求主體:

{
  "models":{"es":"projects/PROJECT_NUMBER_OR_ID/locations/us-central1/models/model-id"},
  "sourceLanguageCode": "en",
  "targetLanguageCodes": ["es"],
  "inputConfigs": [
   {
      "gcsSource": {
        "inputUri": "gs://bucket-name-source/input-file-name1"
      }
    },
    {
      "gcsSource": {
        "inputUri": "gs://bucket-name-source/input-file-name2"
      }
    }
  ],
  "outputConfig": {
      "gcsDestination": {
        "outputUriPrefix": "gs://bucket-name-destination/"
      }
   }
}

如要傳送要求,請展開以下其中一個選項:

您應該會收到如下的 JSON 回應:

{
  "name": "projects/project-number/locations/us-central1/operations/20190725-08251564068323-5d3895ce-0000-2067-864c-001a1136fb06",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.translation.v3.BatchTranslateMetadata",
    "state": "RUNNING"
  }
}
回應會包含一項長時間執行作業的 ID。

Go

在試用這個範例之前,請先按照Go使用用戶端程式庫的 Cloud Translation 快速入門導覽課程中的操作說明進行設定。詳情請參閱 Cloud Translation Go API 參考說明文件

如要向 Cloud Translation 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

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
}

Java

在試用這個範例之前,請先按照Java使用用戶端程式庫的 Cloud Translation 快速入門導覽課程中的操作說明進行設定。詳情請參閱 Cloud Translation Java API 參考說明文件

如要向 Cloud Translation 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

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());
    }
  }
}

Node.js

在試用這個範例之前,請先按照Node.js使用用戶端程式庫的 Cloud Translation 快速入門導覽課程中的操作說明進行設定。詳情請參閱 Cloud Translation Node.js API 參考說明文件

如要向 Cloud Translation 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

/**
 * 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();

Python

在試用這個範例之前,請先按照Python使用用戶端程式庫的 Cloud Translation 快速入門導覽課程中的操作說明進行設定。詳情請參閱 Cloud Translation Python API 參考說明文件

如要向 Cloud Translation 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

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

其他語言

C#: 請按照用戶端程式庫頁面的 C# 設定說明操作, 然後前往 .NET 適用的 Cloud Translation 參考說明文件

PHP: 請按照用戶端程式庫頁面的 PHP 設定說明 操作,然後前往 PHP 適用的 Cloud Translation 參考說明文件

Ruby: 請按照用戶端程式庫頁面的 Ruby 設定說明 操作,然後前往 Ruby 適用的 Cloud Translation 參考文件

為多種目標語言指定 AutoML 模型

REST

如果有多種譯文語言,可以為每種譯文語言指定自訂模型。

使用任何要求資料之前,請先替換以下項目:

  • PROJECT_NUMBER_OR_ID: Google Cloud 專案的數值或英數字元 ID

HTTP 方法和網址:

POST https://translation.googleapis.com/v3/projects/PROJECT_NUMBER_OR_ID/locations/us-central1:batchTranslateText

JSON 要求主體:

{
  "models":{
    "es":"projects/PROJECT_NUMBER_OR_ID/locations/us-central1/models/model-id1",
    "fr":"projects/PROJECT_NUMBER_OR_ID/locations/us-central1/models/model-id2"},
  "sourceLanguageCode": "en",
  "targetLanguageCodes": ["es", "fr"],
  "inputConfigs": [
   {
      "gcsSource": {
        "inputUri": "gs://bucket-name-source/input-file-name1"
      }
    },
    {
      "gcsSource": {
        "inputUri": "gs://bucket-name-source/input-file-name2"
      }
    }
  ],
  "outputConfig": {
      "gcsDestination": {
        "outputUriPrefix": "gs://bucket-name-destination/"
      }
   }
 }

如要傳送要求,請展開以下其中一個選項:

您應該會收到如下的 JSON 回應:

{
  "name": "projects/project-number/locations/us-central1/operations/20191105-08251564068323-5d3895ce-0000-2067-864c-001a1136fb06",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.translation.v3.BatchTranslateMetadata",
    "state": "RUNNING"
  }
}
回應會包含一項長時間執行作業的 ID。

為目標語言指定 AutoML 模型,但未為其他語言指定

您可以為特定目標語言指定自訂模型,但不必為其他目標語言指定模型。使用「為多種目標語言指定自訂模型」的程式碼,修改 models 欄位,指定模型的目標語言 (本例為 es),並將 fr 留空:

  • "models": {'es':'projects/PROJECT_NUMBER_OR_ID/locations/us-central1/models/model-id'},

其中 PROJECT_NUMBER_OR_ID 是您的 Google Cloud 專案編號 或 ID,model-id 則是您為 AutoML 模型指定的名稱。

使用詞彙表翻譯文字

REST

這個範例說明如何指定目標語言的字彙表。

使用任何要求資料之前,請先替換以下項目:

  • PROJECT_NUMBER_OR_ID: Google Cloud 專案的數值或英數字元 ID
  • glossary-id:您的詞彙表 ID,例如「my-en-to-es-glossary」

HTTP 方法和網址:

POST https://translation.googleapis.com/v3/projects/PROJECT_NUMBER_OR_ID/locations/us-central1:batchTranslateText

JSON 要求主體:

{
  "sourceLanguageCode": "en",
  "targetLanguageCodes": ["es"],
  "glossaries": {
    "es": {
      "glossary": "projects/PROJECT_NUMBER_OR_ID/locations/us-central1/glossaries/glossary-id"
    }
  },
  "inputConfigs": [{
      "gcsSource": {
        "inputUri": "gs://bucket-name-source/input-file-name1"
      }
    },
    {
      "gcsSource": {
        "inputUri": "gs://bucket-name-source/input-file-name2"
      }
    }
  ],
  "outputConfig": {
    "gcsDestination": {
      "outputUriPrefix": "gs://bucket-name-destination/"
    }
  }
}

如要傳送要求,請選擇以下其中一個選項:

curl

將要求主體儲存在名為 request.json 的檔案中,然後執行下列指令:

curl -X POST \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "x-goog-user-project: PROJECT_NUMBER_OR_ID" \
-H "Content-Type: application/json; charset=utf-8" \
-d @request.json \
"https://translation.googleapis.com/v3/projects/PROJECT_NUMBER_OR_ID/locations/us-central1:batchTranslateText"

PowerShell

將要求主體儲存在名為 request.json 的檔案中,然後執行下列指令:

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred"; "x-goog-user-project" = "PROJECT_NUMBER_OR_ID" }

Invoke-WebRequest `
-Method POST `
-Headers $headers `
-ContentType: "application/json; charset=utf-8" `
-InFile request.json `
-Uri "https://translation.googleapis.com/v3/projects/PROJECT_NUMBER_OR_ID/locations/us-central1:batchTranslateText" | Select-Object -Expand Content

您應該會收到如下的 JSON 回應:

{
  "name": "projects/project-number/locations/us-central1/operations/operation-id",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.translation.v3.BatchTranslateMetadata",
    "state": "RUNNING"
  }
}

Go

在試用這個範例之前,請先按照Go使用用戶端程式庫的 Cloud Translation 快速入門導覽課程中的操作說明進行設定。詳情請參閱 Cloud Translation Go API 參考說明文件

如要向 Cloud Translation 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

import (
	"context"
	"fmt"
	"io"

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

// batchTranslateTextWithGlossary translates a large volume of text in asynchronous batch mode.
func batchTranslateTextWithGlossary(w io.Writer, projectID string, location string, inputURI string, outputURI string, sourceLang string, targetLang string, glossaryID 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"

	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,
				},
			},
		},
	}

	// 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

在試用這個範例之前,請先按照Java使用用戶端程式庫的 Cloud Translation 快速入門導覽課程中的操作說明進行設定。詳情請參閱 Cloud Translation Java API 參考說明文件

如要向 Cloud Translation 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

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 BatchTranslateTextWithGlossary {

  public static void batchTranslateTextWithGlossary()
      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";
    batchTranslateTextWithGlossary(
        projectId, sourceLanguage, targetLanguage, inputUri, outputUri, glossaryId);
  }

  // Batch Translate Text with a Glossary.
  public static void batchTranslateTextWithGlossary(
      String projectId,
      String sourceLanguage,
      String targetLanguage,
      String inputUri,
      String outputUri,
      String glossaryId)
      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();

      // 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)
              .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

在試用這個範例之前,請先按照Node.js使用用戶端程式庫的 Cloud Translation 快速入門導覽課程中的操作說明進行設定。詳情請參閱 Cloud Translation Node.js API 參考說明文件

如要向 Cloud Translation 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

/**
 * 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';

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

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

  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}`);
}

batchTranslateTextWithGlossary();

Python

在試用這個範例之前,請先按照Python使用用戶端程式庫的 Cloud Translation 快速入門導覽課程中的操作說明進行設定。詳情請參閱 Cloud Translation Python API 參考說明文件

如要向 Cloud Translation 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

from google.cloud import translate


def batch_translate_text_with_glossary(
    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",
    glossary_id: str = "YOUR_GLOSSARY_ID",
    timeout: int = 320,
) -> translate.TranslateTextResponse:
    """Translates a batch of texts on GCS and stores the result in a GCS location.
    Glossary is applied for translation.

    Args:
        input_uri (str): The input file to translate.
        output_uri (str): The output file to save the translations to.
        project_id (str): The ID of the GCP project that owns the location.
        glossary_id (str): The ID of the glossary to use.
        timeout (int): The amount of time, in seconds, to wait for the operation to complete.

    Returns:
        The response from the batch.
    """

    client = translate.TranslationServiceClient()

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

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

    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}"

    # glossary is a custom dictionary Translation API uses
    # to translate the domain-specific terminology.
    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": ["ja"],  # Up to 10 language codes here.
            "input_configs": [input_configs_element],
            "glossaries": glossaries,
            "output_config": output_config,
        }
    )

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

    print(f"Total Characters: {response.total_characters}")
    print(f"Translated Characters: {response.translated_characters}")

    return response

其他語言

C#: 請按照用戶端程式庫頁面的 C# 設定說明操作, 然後前往 .NET 適用的 Cloud Translation 參考說明文件

PHP: 請按照用戶端程式庫頁面的 PHP 設定說明 操作,然後前往 PHP 適用的 Cloud Translation 參考說明文件

Ruby: 請按照用戶端程式庫頁面的 Ruby 設定說明 操作,然後前往 Ruby 適用的 Cloud Translation 參考文件

使用 AutoML Translation 自訂模型和詞彙翻譯文字

REST

這個範例說明如何為目標語言指定自訂模型和詞彙表。

使用任何要求資料之前,請先替換以下項目:

  • PROJECT_NUMBER_OR_ID: Google Cloud 專案的數值或英數字元 ID

HTTP 方法和網址:

POST https://translation.googleapis.com/v3/projects/PROJECT_NUMBER_OR_ID/locations/us-central1:batchTranslateText

JSON 要求主體:

{
  "models": {
    "es": "projects/project_number_or_id/locations/us-central1/models/model-id"
  },
  "sourceLanguageCode": "en",
  "targetLanguageCodes": ["es"],
  "glossaries": {
    "es": {
      "glossary": "projects/project_number_or_id/locations/us-central1/glossaries/glossary-id"
    }
  },
  "inputConfigs": [{
      "gcsSource": {
        "inputUri": "gs://bucket-name-source/input-file-name"
      }
    },
    {
      "gcsSource": {
      "inputUri": "gs://bucket-name-source/input-file-name2"
      }
    }
  ],
  "outputConfig": {
    "gcsDestination": {
      "outputUriPrefix": "gs://bucket-name-destination/"
    }
  }
}

如要傳送要求,請選擇以下其中一個選項:

curl

將要求主體儲存在名為 request.json 的檔案中,然後執行下列指令:

curl -X POST \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "x-goog-user-project: PROJECT_NUMBER_OR_ID" \
-H "Content-Type: application/json; charset=utf-8" \
-d @request.json \
"https://translation.googleapis.com/v3/projects/PROJECT_NUMBER_OR_ID/locations/us-central1:batchTranslateText"

PowerShell

將要求主體儲存在名為 request.json 的檔案中,然後執行下列指令:

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred"; "x-goog-user-project" = "PROJECT_NUMBER_OR_ID" }

Invoke-WebRequest `
-Method POST `
-Headers $headers `
-ContentType: "application/json; charset=utf-8" `
-InFile request.json `
-Uri "https://translation.googleapis.com/v3/projects/PROJECT_NUMBER_OR_ID/locations/us-central1:batchTranslateText" | Select-Object -Expand Content

您應該會收到如下的 JSON 回應:

{
  "name": "projects/project-number/locations/us-central1/operations/operation-id",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.translation.v3.BatchTranslateMetadata",
    "state": "RUNNING"
  }
}

Go

在試用這個範例之前,請先按照Go使用用戶端程式庫的 Cloud Translation 快速入門導覽課程中的操作說明進行設定。詳情請參閱 Cloud Translation Go API 參考說明文件

如要向 Cloud Translation 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

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

在試用這個範例之前,請先按照Java使用用戶端程式庫的 Cloud Translation 快速入門導覽課程中的操作說明進行設定。詳情請參閱 Cloud Translation Java API 參考說明文件

如要向 Cloud Translation 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

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

在試用這個範例之前,請先按照Node.js使用用戶端程式庫的 Cloud Translation 快速入門導覽課程中的操作說明進行設定。詳情請參閱 Cloud Translation Node.js API 參考說明文件

如要向 Cloud Translation 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

/**
 * 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();

Python

在試用這個範例之前,請先按照Python使用用戶端程式庫的 Cloud Translation 快速入門導覽課程中的操作說明進行設定。詳情請參閱 Cloud Translation Python API 參考說明文件

如要向 Cloud Translation 進行驗證,請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

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

其他語言

C#: 請按照用戶端程式庫頁面的 C# 設定說明操作, 然後前往 .NET 適用的 Cloud Translation 參考說明文件

PHP: 請按照用戶端程式庫頁面的 PHP 設定說明 操作,然後前往 PHP 適用的 Cloud Translation 參考說明文件

Ruby: 請按照用戶端程式庫頁面的 Ruby 設定說明 操作,然後前往 Ruby 適用的 Cloud Translation 參考文件

作業狀態

批次要求是一項長時間執行的作業,可能需要相當長的時間才能完成。您可以輪詢這項作業的狀態來查看作業是否已完成,也可以取消該項作業。

詳情請參閱長時間執行的作業一文。

其他資源

  • 如需解決常見問題或錯誤的說明,請參閱「疑難排解」頁面。