deepl-node

Official Node.js Client Library for the DeepL API.

The DeepL API is a language translation API that allows other computer programs to send texts and documents to DeepL's servers and receive high-quality translations. This opens a whole universe of opportunities for developers: any translation product you can imagine can now be built on top of DeepL's best-in-class translation technology.

The DeepL Node.js library offers a convenient way for applications written for Node.js to interact with the DeepL API. We intend to support all API functions with the library, though support for new features may be added to the library after they’re added to the API.

Getting an authentication key

To use the package, you'll need an API authentication key. To get a key, please create an account here. With a DeepL API Free account you can translate up to 500,000 characters/month for free.

Installation

npm install deepl-node

Requirements

The package officially supports Node.js version 12, 14, 16, 17, and 18.

Starting in 2024, we will drop support for older Node versions that have reached official end-of-life. You can find the Node versions and support timelines here. To continue using this library, you should update to Node 18+.

Usage

Import the package and construct a Translator. The first argument is a string containing your API authentication key as found in your DeepL Pro Account.

Be careful not to expose your key, for example when sharing source code.

An example using async/await and ES Modules:

import * as deepl from 'deepl-node';

const authKey = "f63c02c5-f056-..."; // Replace with your key
const translator = new deepl.Translator(authKey);

(async () => {
    const result = await translator.translateText('Hello, world!', null, 'fr');
    console.log(result.text); // Bonjour, le monde !
})();

This example is for demonstration purposes only. In production code, the authentication key should not be hard-coded, but instead fetched from a configuration file or environment variable.

If you are using CommonJS, you should instead require the package:

const deepl = require('deepl-node');
const translator = new deepl.Translator(authKey);

Translator accepts options as the second argument, see Configuration for more information.

All Translator functions return promises, and for brevity the examples in this file use await and try/catch blocks, however Promise-chaining is also possible:

translator
    .translateText('Hello, world!', null, 'fr')
    .then((result) => {
        console.log(result.text); // Bonjour, le monde !
    })
    .catch((error) => {
        console.error(error);
    });

The package also supports TypeScript:

import * as deepl from 'deepl-node';

(async () => {
    const targetLang: deepl.TargetLanguageCode = 'fr';
    const results = await translator.translateText(
        ['Hello, world!', 'How are you?'],
        null,
        targetLang,
    );
    results.map((result: deepl.TextResult) => {
        console.log(result.text); // Bonjour, le monde !
    });
})();

Translating text

To translate text, call translateText(). The first argument is a string containing the text you want to translate, or an array of strings if you want to translate multiple texts.

The second and third arguments are the source and target language codes. Language codes are case-insensitive strings according to ISO 639-1, for example 'de', 'fr', 'ja''. Some target languages also include the regional variant according to ISO 3166-1, for example 'en-US', or 'pt-BR'. The source language also accepts null, to enable auto-detection of the source language.

The last argument to translateText() is optional, and specifies extra translation options, see Text translation options below.

translateText() returns a Promise that fulfills with a TextResult, or an array of TextResults corresponding to your input text(s). TextResult has the following properties:

• text is the translated text,
• detectedSourceLang is the detected source language code,
• billedCharacters is the number of characters billed for the text.
• modelTypeUsed indicates the translation model used, but is undefined unless the modelType option is specified.

// Translate text into a target language, in this case, French:
const translationResult = await translator.translateText('Hello, world!', 'en', 'fr');
console.log(translationResult.text); // 'Bonjour, le monde !'

// Translate multiple texts into British English:
const translations = await translator.translateText(
    ['お元気ですか？', '¿Cómo estás?'],
    null,
    'en-GB',
);
console.log(translations[0].text); // 'How are you?'
console.log(translations[0].detectedSourceLang); // 'ja'
console.log(translations[0].billedCharacters); // 7 - the number of characters in the source text "お元気ですか？"
console.log(translations[1].text); // 'How are you?'
console.log(translations[1].detectedSourceLang); // 'es'
console.log(translations[1].billedCharacters); // 12 - the number of characters in the source text "¿Cómo estás?"

// Translate into German with less and more Formality:
console.log(await translator.translateText('How are you?', null, 'de', { formality: 'less' })); // 'Wie geht es dir?'
console.log(await translator.translateText('How are you?', null, 'de', { formality: 'more' })); // 'Wie geht es Ihnen?'

Text translation options

• splitSentences: specify how input text should be split into sentences, default: 'on'.
  • 'on': input text will be split into sentences using both newlines and punctuation.
  • 'off': input text will not be split into sentences. Use this for applications where each input text contains only one sentence.
  • 'nonewlines': input text will be split into sentences using punctuation but not newlines.
• preserveFormatting: controls automatic-formatting-correction. Set to true to prevent automatic-correction of formatting, default: false.
• formality: controls whether translations should lean toward informal or formal language. This option is only available for some target languages, see Listing available languages. Use the prefer_* options to apply formality if it is available for the target
  language, or otherwise fallback to the default.
  • 'less': use informal language.
  • 'more': use formal, more polite language.
  • 'default': use default formality.
  • 'prefer_less': use informal language if available, otherwise default.
  • 'prefer_more': use formal, more polite language if available, otherwise default.
• glossary: specifies a glossary to use with translation, either as a string containing the glossary ID, or a GlossaryInfo as returned by getGlossary().
• context: specifies additional context to influence translations, that is not translated itself. Characters in the context parameter are not counted toward billing. See the API documentation for more information and example usage.
• modelType: specifies the type of translation model to use, options are:
  • 'quality_optimized': use a translation model that maximizes translation quality, at the cost of response time. This option may be unavailable for some language pairs.
  • 'prefer_quality_optimized': use the highest-quality translation model for the given language pair.
  • 'latency_optimized': use a translation model that minimizes response time, at the cost of translation quality.
• tagHandling: type of tags to parse before translation, options are 'html' and 'xml'.

The following options are only used if tagHandling is 'xml':

• outlineDetection: specify false to disable automatic tag detection, default is true.
• splittingTags: list of XML tags that should be used to split text into sentences. Tags may be specified as an array of strings (['tag1', 'tag2']), or a comma-separated list of strings ('tag1,tag2'). The default is an empty list.
• nonSplittingTags: list of XML tags that should not be used to split text into sentences. Format and default are the same as for splittingTags.
• ignoreTags: list of XML tags that containing content that should not be translated. Format and default are the same as for splittingTags.
• extraRequestParameters: Extra body parameters to be passed along with the HTTP request. Only string values are permitted. For example: {'param': 'value', 'param2': 'value2'}

Translating documents

To translate documents, call translateDocument(). The first and second arguments are the input and output files. These arguments accept strings containing file paths, or Streams or FileHandles opened for reading/writing. The input file may also be given as a Buffer containing the file data. Note that if the input file is not given as a file path, then the filename option is required.

The third and fourth arguments are the source and target language codes, and they work exactly the same as when translating text with translateText().

The last argument to translateDocument() is optional, and specifies extra translation options, see Document translation options below.

// Translate a formal document from English to German:
try {
    await translator.translateDocument(
        'Instruction Manual.docx',
        'Bedienungsanleitung.docx',
        'en',
        'de',
        { formality: 'more' },
    );
} catch (error) {
    // If the error occurs after the document was already uploaded,
    // documentHandle will contain the document ID and key
    if (error.documentHandle) {
        const handle = error.documentHandle;
        console.log(`Document ID: ${handle.documentId}, ` + `Document key: ${handle.documentKey}`);
    } else {
        console.log(`Error occurred during document upload: ${error}`);
    }
}

translateDocument() wraps multiple API calls: uploading, polling status until the translation is complete, and downloading. If your application needs to execute these steps individually, you can instead use the following functions directly:

• uploadDocument(),
• getDocumentStatus() (or isDocumentTranslationComplete()), and
• downloadDocument()

Document translation options

• formality: same as in Text translation options.
• glossary: same as in Text translation options.
• filename: if the input file is not provided as file path, this option is needed to specify the file extension.
• extraRequestParameters: same as in Text translation options.

Glossaries

Glossaries allow you to customize your translations using defined terms. Multiple glossaries can be stored with your account, each with a user-specified name and a uniquely-assigned ID.

You can create a glossary with your desired terms and name using createGlossary(). Each glossary applies to a single source-target language pair. Note: glossaries are only supported for some language pairs, check the DeepL API documentation for more information.

// Create an English to German glossary with two terms:
const entries = new deepl.GlossaryEntries({ entries: { artist: 'Maler', prize: 'Gewinn' } });
const glossaryEnToDe = await translator.createGlossary('My glossary', 'en', 'de', entries);

You can also upload a glossary downloaded from the DeepL website using createGlossaryWithCsv(). Instead of supplying the entries as a dictionary, provide the CSV file as a string containing the file path, or a Stream, Buffer, or FileHandle containing the CSV file content:

const csvFilePath = '/path/to/glossary_file.csv';
const glossaryEnToDe = await translator.createGlossaryWithCsv(
    'My glossary',
    'en',
    'de',
    csvFilePath);

The API documentation explains the expected CSV format in detail.

Functions to get, list, and delete stored glossaries are also provided.

// Find details about the glossary named 'My glossary'
const glossaries = await translator.listGlossaries();
const glossary = glossaries.find((glossary) => glossary.name == 'My glossary');
console.log(
    `Glossary ID: ${glossary.glossaryId}, source: ${glossary.sourceLang}, ` +
        `target: ${glossary.targetLang}, contains ${glossary.entryCount} entries.`,
);

To use a glossary when translating text and documents, include the ID (or Glossary object returned by listGlossaries() or createGlossary()) in the function call. The source and target languages must match the glossary.

const resultWithGlossary = await translator.translateText(
    'The artist was awarded a prize.',
    'en',
    'de',
    { glossary },
);
console.log(resultWithGlossary.text); // 'Der Maler wurde mit einem Gewinn ausgezeichnet.'
// Without using a glossary would give:  'Der Künstler wurde mit einem Preis ausgezeichnet.'

Checking account usage

To check account usage, use the getUsage() function.

The returned Usage object contains up to three usage subtypes, depending on your account type: character, document and teamDocument. For API accounts character will be defined, the others undefined.

Each usage subtypes (if defined) have count and limit properties giving the amount used and maximum amount respectively, and the limitReached() function that checks if the usage has reached the limit. The top level Usage object has the anyLimitReached() function to check all usage subtypes.

const usage = await translator.getUsage();
if (usage.anyLimitReached()) {
    console.log('Translation limit exceeded.');
}
if (usage.character) {
    console.log(`Characters: ${usage.character.count} of ${usage.character.limit}`);
}
if (usage.document) {
    console.log(`Documents: ${usage.document.count} of ${usage.document.limit}`);
}

Listing available languages

You can request the list of languages supported by DeepL Translator for text and documents using the getSourceLanguages() and getTargetLanguages() functions. They both return an array of Language objects.

The name property gives the name of the language in English, and the code property gives the language code. The supportsFormality property only appears for target languages, and is a Boolean indicating whether the target language supports the optional formality parameter.

const sourceLanguages = await translator.getSourceLanguages();
for (let i = 0; i < sourceLanguages.length; i++) {
    const lang = sourceLanguages[i];
    console.log(`${lang.name} (${lang.code})`); // Example: 'English (en)'
}

const targetLanguages = await translator.getTargetLanguages();
for (let i = 0; i < targetLanguages.length; i++) {
    const lang = targetLanguages[i];
    if (lang.supportsFormality) {
        console.log(`${lang.name} (${lang.code}) supports formality`);
        // Example: 'German (DE) supports formality'
    }
}

Glossaries are supported for a subset of language pairs. To retrieve those languages use the getGlossaryLanguagePairs() function, which returns an array of GlossaryLanguagePair objects. Each has sourceLang and targetLang properties indicating that that pair of language codes is supported for glossaries.

const glossaryLanguages = await translator.getGlossaryLanguagePairs();
for (let i = 0; i < glossaryLanguages.length; i++) {
    const languagePair = glossaryLanguages[i];
    console.log(`${languagePair.sourceLang} to ${languagePair.targetLang}`);
    // Example: 'en to de', 'de to en', etc.
}

Writing a Plugin

If you use this library in an application, please identify the application with the appInfo field in the TranslatorOptions, which takes the name and version of the app:

const options = {appInfo: { appName: 'sampleNodeTranslationApp', appVersion: '1.2.3' },};
const deepl = new deepl.Translator('YOUR_AUTH_KEY', options);

This information is passed along when the library makes calls to the DeepL API. Both name and version are required.

Configuration

The Translator constructor accepts configuration options as a second argument, for example:

const options = { maxRetries: 5, minTimeout: 10000 };
const deepl = new deepl.Translator('YOUR_AUTH_KEY', options);

The available options are:

• maxRetries: the maximum Number of failed HTTP requests to retry, per function call. By default, 5 retries are made. See Request retries.
• minTimeout: the Number of milliseconds used as connection timeout for each HTTP request retry. The default value is 10000 (10 seconds).
• serverUrl: string containing the URL of the DeepL API, can be overridden for example for testing purposes. By default, the URL is selected based on the user account type (free or paid).
• headers: extra HTTP headers attached to every HTTP request. By default, no extra headers are used. Note that Authorization and User-Agent headers are added automatically but may be overridden by this option.
• proxy: define the hostname, and port of the proxy server, and optionally the protocol, and authorization (as an auth object with username and password fields).

Logging

deepl-node logs debug and info messages for every HTTP request and response using the loglevel module, to the 'deepl' logger. You can reconfigure the log level as follows:

import log from 'loglevel';

log.getLogger('deepl').setLevel('debug'); // Or 'info'

The loglevel package also supports plugins, see the documentation.

Proxy configuration

You can configure a proxy by specifying the proxy argument when constructing a deepl.Translator:

const options = {proxy: {host: 'localhost', port: 3000}};
const deepl = new deepl.Translator('YOUR_AUTH_KEY', options);

The proxy argument is passed to the underlying axios request, see the documentation for axios.

Anonymous platform information

By default, we send some basic information about the platform the client library is running on with each request, see here for an explanation. This data is completely anonymous and only used to improve our product, not track any individual users. If you do not wish to send this data, you can opt-out when creating your Translator object by setting the sendPlatformInfo flag in the TranslatorOptions to false like so:

const options = {sendPlatformInfo: false};
const deepl = new deepl.Translator('YOUR_AUTH_KEY', options);

Request retries

Requests to the DeepL API that fail due to transient conditions (for example, network timeouts or high server-load) will be retried. The maximum number of retries can be configured when constructing the Translator object using the maxRetries option. The timeout for each request attempt may be controlled using the minTimeout option. An exponential-backoff strategy is used, so requests that fail multiple times will incur delays.

Issues

If you experience problems using the library, or would like to request a new feature, please open an issue.

Development

We welcome Pull Requests, please read the contributing guidelines.

Tests

Execute the tests using npm test. The tests communicate with the DeepL API using the authentication key defined by the DEEPL_AUTH_KEY environment variable.

Be aware that the tests make DeepL API requests that contribute toward your API usage.

The test suite may instead be configured to communicate with the mock-server provided by deepl-mock. Although most test cases work for either, some test cases work only with the DeepL API or the mock-server and will be otherwise skipped. The test cases that require the mock-server trigger server errors and test the client error-handling. To execute the tests using deepl-mock, run it in another terminal while executing the tests. Execute the tests using npm test with the DEEPL_MOCK_SERVER_PORT and DEEPL_SERVER_URL environment variables defined referring to the mock-server.