Bot Framework v4 multilingual bot sample
This sample will present the user with a set of cards to pick their choice of language. The user can either change language by invoking the option cards, or by entering the language code (en/es). The bot will then acknowledge the selection.
This bot has been created using Bot Framework, it shows how to translate incoming and outgoing text using a custom middleware and the Microsoft Translator Text API.
Translation Middleware: We create a translation middleware that can translate text from bot to user and from user to bot, allowing the creation of multi-lingual bots.
The middleware is driven by user state. This means that users can specify their language preference, and the middleware automatically will intercept messages back and forth and present them to the user in their preferred language.
Users can change their language preference anytime, and since this gets written to the user state, the middleware will read this state and instantly modify its behavior to honor the newly selected preferred language.
The Microsoft Translator Text API, Microsoft Translator Text API is a cloud-based machine translation service. With this API you can translate text in near real-time from any app or service through a simple REST API call. The API uses the most modern neural machine translation technology, as well as offering statistical machine translation technology.
This sample requires prerequisites in order to run.
-
Node.js version 10.14 or higher
# determine node version node --version
-
Microsoft Translator Text API key
To consume the Microsoft Translator Text API, first obtain a key following the instructions in the Microsoft Translator Text API documentation. Paste the key in the
TranslatorKey
setting in the.env
file, or use your preferred configuration and update the following line inindex.js
with your translation key:const translator = new MicrosoftTranslator(process.env.translatorKey); adapter.use(new TranslatorMiddleware(translator, languagePreferenceProperty));
-
Clone the repository
git clone https://github.com/Microsoft/botbuilder-samples.git
-
In a terminal, navigate to
samples/javascript_nodejs/17.multilingual-bot
cd samples/javascript_nodejs/17.multilingual-bot
-
Install modules
npm install
-
Setup Translation API
The reprequisites outlined above contain the steps necessary to use the Microsoft Translator Text API. Refer to the above prerequisites if you have not already done so.
-
Start the bot
npm start
Bot Framework Emulator is a desktop application that allows bot developers to test and debug their bots on localhost or running remotely through a tunnel.
- Install the latest Bot Framework Emulator from here
- Launch Bot Framework Emulator
- File -> Open Bot
- Enter a Bot URL of
http://localhost:3978/api/messages
Translation Middleware: We create a translation middleware than can translate text from bot to user and from user to bot, allowing the creation of multilingual bots. Users can specify their language preference, which is stored in the user state. The translation middleware translates to and from the user's preferred language.
The Microsoft Translator Text API, Microsoft Translator Text API is a cloud-based machine translation service. With this API you can translate text in near real-time from any app or service through a simple REST API call. The API uses the most modern neural machine translation technology, as well as offering statistical machine translation technology.
To learn more about deploying a bot to Azure, see Deploy your bot to Azure for a complete list of deployment instructions.
If you used the .env
file to store your translatorKey
then you'll need to add this key and its value to the Application Settings for your deployed bot.
- Log into the Azure portal
- In the left nav, click on
Bot Services
- Click the
<your_bot_name>
Name to display the bot's Web App Settings - Click the
Application Settings
- Scroll to the
Application settings
section - Click
+ Add new setting
- Add the key
translatorKey
with a value of the Translator Text APIAuthentication key
created from the steps above