/ConversationLearner-Samples

Sample bot using the ConversationLearner SDK

Primary LanguageTypeScriptMIT LicenseMIT

ConversationLearner-Samples

This repo contains sample code for building task-oriented conversational bots using Project Conversation Learner, and demonstrating how to use the @conversationlearner/sdk npm module.

Project Conversation Learner enables you to build and teach task-oriented conversational interfaces that learn from example interactions, combining code, logical constraints and machine learning. Certain absolute parts of your application such as checking if the user is logged in or making an API request to check store inventory can still be coded; however, other changes in state and action selection can be learned from example dialogs given by the domain expert or developer.

This README explains how to get started; full documentation is availble here.

Invitation required

An invitation is required to access Project Conversation Learner.

Project Conversation Learner consists of an SDK you add to your bot, and a cloud service which the SDK accesses for machine learning. At present, access to the Project Conversation Leaner cloud service requires an invitation. If you haven't been invited already, request an invitation. If you have not received an invitation, you will be unable to access the cloud API.

Prerequisites

Quick start

  1. Install and build:

    git clone https://github.com/Microsoft/ConversationLearner-Samples my-bot-01
cd my-bot-01
npm install
npm run build

    Note: during npm install, you can ignore this error if it occurs: gyp ERR! stack Error: Can't find Python executable

  2. Configure:

    Create a file called .env in the directory my-bot-01. The contents of the file should be:

    LUIS_AUTHORING_KEY=<your LUIS authoring key>

  3. Start bot:

    npm start

    This runs the generic empty bot in my-bot-01/src/app.ts.

  4. Run Conversation Learner UI:

    [open second command prompt window]
cd my-bot-01
npm run ui

  5. Open browser to http://localhost:5050

You're now using Conversation Learner and can create and teach a Conversation Learner model.

Tutorials, demos, and switching between bots

The instructions above started the generic empty bot. To run a tutorial or demo bot instead:

  1. If you have the Conversation Learner web UI open, return to the list of apps at http://localhost:5050/home.

  2. If another bot is running (like npm start or npm run demo-pizza), stop it. You do not need to stop the UI process, or close the web browser.

  3. Run a demo bot from the command line (step 2 above). Demos include:

npm run tutorial-general
npm run tutorial-entity-detection
npm run tutorial-session-callbacks
npm run tutorial-api-calls
npm run demo-password
npm run demo-pizza
npm run demo-storage
npm run demo-vrapp

  1. If you're not already, switch to the Conversation Learner web UI in Chrome by loading http://localhost:5050/home.

  2. Click on "Import tutorials" (only needs to be done once). This will take about a minute and will copy the Conversation Learner models for all the tutorials into your Conversation Learner account.

  3. Click on the demo model in the Conversation Learner UI that corresponds to the demo you started.

Source files for the demos are in my-bot-01/src/demos

Create a bot which includes back-end code

  1. If you have the Converstaion Learner web UI open, return to the list of apps at http://localhost:5050/home.

  2. If a bot is running (like npm run demo-pizza), stop it. You do not need to stop the UI process, or close the web browser.

  3. If desired, edit code in blis-bot-01/src/app.ts.

  4. Rebuild and re-start bot:

    npm run build
npm start

  5. If you're not already, switch to the Converstaion Learner web UI in Chrome by loading http://localhost:5050/home.

  6. Create a new Converstaion Learner application in the UI, and start teaching.

  7. To make code changes in blis-bot-01/src/app.ts, repeat the steps above, starting from step 2.

VSCode

In VSCode, there are run configurations for each demo, and for the "Empty bot" in my-bot-01/src/app.ts. Open the my-bot-01 folder in VSCode.

Advanced configuration

There is a template .env.example file shows what environment variables you may set to configure the samples.

You can adjust these ports to avoid conflicts between other services running on your machine by adding a .env file to root of project:

cp .env.example .env

This uses the standard configuration, which lets you run your bot locally, and start using Conversation Learner. (Later on, to deploy your bot to the Bot Framework, some edits to this file will be needed.)

Publishing your bot

Publish your Conversation Learner bot similar to the same way you would publish any other bot. At a high level, you upload your code to a hosted website, set the appropriate configuration values, and then register the bot with various channels. The docs include detailed instructions on deploying to localhost, and deploying to Azure.

Ensure that these variables are set when deploying your bot:

Environment variable Setting
CONVERSATION_LEARNER_SERVICE_URI https://westus.api.cognitive.microsoft.com/conversationlearner/v1.0/
CONVERSATION_LEARNER_APP_ID Application Id GUID, obtained from the Converstaion Learner UI under the "settings" for the app
LUIS_AUTHORING_KEY LUIS authoring key for this app, obtained from https://www.luis.ai
MICROSOFT_APP_ID Microsoft Application Id
MICROSOFT_APP_PASSWORD Microsoft Application Password

Once the bot is deployed and running you can connect different channels to it such as Facebook, Teams, Skype etc using an Azure Bot Channel Registration. For documentation on that process see: https://docs.microsoft.com/en-us/bot-framework/bot-service-quickstart-registration

Support

Contributing

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

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