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ChatbotExample

README.md

Chatbot with Cognitive Services Personalizer

This sample shows how two Cognitive Services, LUIS and Personalizer, can be integrated into a coffee recommendation chat bot using ASP.NET Core 2.

Setting up the bot

Download the sample

  • Clone the samples repository
git clone https://github.com/Azure-Samples/cognitive-services-personalizer-samples.git

Necessary Azure resources

  • Create both a Personalizer and a Language Understanding (LUIS) resource in the Azure portal. These will be used to power the reinforcement learning and NLP cababilities of the bot, respectively.
  • NOTE: when creating a LUIS resource in the portal, you can choose between creating a prediction resource, an authoring resource, or both. Only an authoring resource is needed for this sample. More on the two here

Set up Personalizer

  • In appsettings.json, modify PersonalizerServiceEndpoint to be your resource's endpoint; this can be found in the quick start tab in the portal
  • Configure the PersonalizerEndpointKey (can also be found in the quick start tab) as an app secret in one of the following ways:
    • If you are using VS Code, you can use the dotnet user-secrets set "PersonalizerEndpointKey" "<Endpoint Key>" command.
    • If you are using Visual Studio, you can right-click the project and select the Manage User Secrets menu option to configure the Personalizer keys. By doing this, Visual Studio will open a secrets.json file where you can add the keys as follows: 
      {
  "PersonalizerEndpointKey": "<your endpoint key>",
}

Set up LUIS

  • Navigate to LUIS portal.

  • Click the Sign in button.

  • Click on My Apps.

  • Select the LUIS authoring resource you created earlier.

  • Click on the Import new app button.

  • Click on the Choose File and select coffeebot.json from the cognitive-services-personalizer-samples/samples/ChatbotExample/CognitiveModels folder.

  • Click on the Train button on the top right of the page; this will train your app on the model inside of chatbot.json.

  • Once this is done, press the Publish button and select "Production". NOTE: Once you publish your app on LUIS portal for the first time, it takes some time for the endpoint to become available, about 5 minutes of wait should be sufficient.

  • Update nlp-with-luis.bot file with your AppId, AuthoringKey, Region and Version. You can find this information under the Manage tab.

    • The AppID can be found in "Application Information"
    • The AuthoringKey can be found in "Azure Resources" > "Authoring Resource" > "Primary key"
    • The Region is listed above the primary key (authoring key)
    • The Version is located next to the name of your app in the top left corner

    You will have something similar to this in the services section of your .bot file to run this sample:

    {
    "type":"luis",
    "name":"<some name>",
    "appId":"<your app id>",
    "version":"<your version number>",
    "authoringKey":"<your authoring key>",
    "region":"<your region>",
    "id":"<some number>"
},

  • [Optional] Update the appsettings.json file under cognitive-services-personalizer-samples/samples/ChatbotExample/ with your botFileSecret. For Azure Bot Service bots, you can find the botFileSecret under application settings.

Running and interacting with the bot

Visual Studio

  • Right click on the LuisBot project file > Properties > Debug and change the App URL to match the base URL of the endpoint listed in nlp-with-luis.bot
  • Run the project (press F5 key)

Visual Studio Code

  • Open the launch.jsonfile generated for you inside ./vscode; inside of Configurations.env, add an entry with key "ASPNETCORE_URLS: <your bot endpoint>, where your bot endpoint is the base URL of the endpoint listed in nlp-with-luis.bot For example: Json "env": { "ASPNETCORE_ENVIRONMENT": "Development", "ASPNETCORE_URLS": "http://localhost:4034" },
  • Bring up a terminal, navigate to cognitive-services-personalizer-samples/samples/ChatbotExample/ folder.
  • Type dotnet run.

Testing the bot using Bot Framework Emulator

Microsoft 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 Bot Framework Emulator from here.

Connect to bot using Bot Framework Emulator V4

  • Launch the Bot Framework Emulator
  • File -> Open bot and navigate to cognitive-services-personalizer-samples/samples/ChatbotExample/ folder
  • Select nlp-with-luis.bot file

Interact with Chatbot

The chatbot can understand human inputs by defined "Intents" and "utterances". Those definitions can be found in coffeebot.json. For example, if you type "what do you suggest", Luis will be able to categorize it as the Intent - "ChooseRank".

Intent Processing

In this example, Luis Intents will be processed in LuisBot.cs and then it will call the Ranking API to get a suggestion, shown below:

public async Task OnTurnAsync(ITurnContext turnContext, CancellationToken cancellationToken = default(CancellationToken))
{
    if (turnContext.Activity.Type == ActivityTypes.Message)
    {
        var recognizerResult = await _services.LuisServices[LuisKey].RecognizeAsync(turnContext, cancellationToken);
        var topIntent = recognizerResult?.GetTopScoringIntent();
        if (topIntent != null && topIntent.HasValue && topIntent.Value.intent != "None")
        {
            Intents intent = (Intents)Enum.Parse(typeof(Intents), topIntent.Value.intent);
            switch (intent)
            {
                ...
                case Intents.ChooseRank:
                    var response = await ChooseRankAsync(turnContext, _rlFeaturesManager.GenerateEventId());
                    await turnContext.SendActivityAsync($"What about {response.RewardActionId}");
                    break;
                ...
            }
            ...
        }
        ...
    }
    ...
}

Deploy this bot to Azure (optional)

Follow this tutorial if you want to deploy your bot to Azure. Additionally, if you would like to register your bot with Azure Bot Service, you can follow the steps at this link.

Further reading