Use multiple LUIS and QnA models

In Startup.cs, ConfigureServices reads in the configuration file, and InitBotServices uses that information to initialize the services. Each time it's created, the bot is initialized with the registered BotServices object. Here are the relevant parts of these two methods.

public void ConfigureServices(IServiceCollection services)
{
    //...
    var botConfig = BotConfiguration.Load(botFilePath ?? @".\nlp-with-dispatch.bot", secretKey);
    services.AddSingleton(sp => botConfig
        ?? throw new InvalidOperationException($"The .bot config file could not be loaded. ({botConfig})"));

    // ...
    
    var connectedServices = InitBotServices(botConfig);
    services.AddSingleton(sp => connectedServices);
    
    services.AddBot<NlpDispatchBot>(options =>
    {
          
          // The Memory Storage used here is for local bot debugging only. 
          // When the bot is restarted, everything stored in memory will be gone.

          Storage dataStore = new MemoryStorage();

          // ...

          // Create Conversation State object.
          // The Conversation State object is where we persist anything at the conversation-scope.

          var conversationState = new ConversationState(dataStore);
          options.State.Add(conversationState);
     });
}

The following code initializes the bot's references to external services. For example, LUIS and QnaMaker services are created here. These external services are configured using the BotConfiguration class (based on the contents of your ".bot" file.

private static BotServices InitBotServices(BotConfiguration config)
{
    var qnaServices = new Dictionary<string, QnAMaker>();
    var luisServices = new Dictionary<string, LuisRecognizer>();

    foreach (var service in config.Services)
    {
        switch (service.Type)
        {
            case ServiceTypes.Luis:
                {
                    // ...
                    var app = new LuisApplication(luis.AppId, luis.AuthoringKey, luis.GetEndpoint());
                    var recognizer = new LuisRecognizer(app);
                    luisServices.Add(luis.Name, recognizer);
                    break;
                }

            case ServiceTypes.Dispatch:
                // ...
                var dispatchApp = new LuisApplication(dispatch.AppId, dispatch.AuthoringKey, dispatch.GetEndpoint());

                // Since the Dispatch tool generates a LUIS model, we use the LuisRecognizer to resolve the
                // dispatching of the incoming utterance.
                var dispatchARecognizer = new LuisRecognizer(dispatchApp);
                luisServices.Add(dispatch.Name, dispatchARecognizer);
                break;

            case ServiceTypes.QnA:
                {
                    // ...
                    var qnaEndpoint = new QnAMakerEndpoint()
                    {
                        KnowledgeBaseId = qna.KbId,
                        EndpointKey = qna.EndpointKey,
                        Host = qna.Hostname,
                    };

                    var qnaMaker = new QnAMaker(qnaEndpoint);
                    qnaServices.Add(qna.Name, qnaMaker);
                    break;
                }
        }
    }

    return new BotServices(qnaServices, luisServices);
}

In the NlpDispatchBot.cs file, the bot's constructor gets the BotServices object that we registered at startup.

private readonly BotServices _services;

public NlpDispatchBot(BotServices services)
{
    _services = services ?? throw new System.ArgumentNullException(nameof(services));

    //...
}

In the bot's OnTurnAsync method, we check incoming messages from the user against the Dispatch model.

// Get the intent recognition result
var recognizerResult = await _services.LuisServices[DispatchKey].RecognizeAsync(context, cancellationToken);
var topIntent = recognizerResult?.GetTopScoringIntent();

if (topIntent == null)
{
    await context.SendActivityAsync("Unable to get the top intent.");
}
else
{
    await DispatchToTopIntentAsync(context, topIntent, cancellationToken);
}

When the model produces a result, it indicates which service can most appropriately process the utterance. The code in this bot routes the request to the corresponding service, and then summarizes the response from the called service.

// Depending on the intent from Dispatch, routes to the right LUIS model or QnA service.
private async Task DispatchToTopIntentAsync(
    ITurnContext context,
    (string intent, double score)? topIntent,
    CancellationToken cancellationToken = default(CancellationToken))
{
    const string homeAutomationDispatchKey = "l_Home_Automation";
    const string weatherDispatchKey = "l_Weather";
    const string noneDispatchKey = "None";
    const string qnaDispatchKey = "q_sample-qna";

    switch (topIntent.Value.intent)
    {
        case homeAutomationDispatchKey:
            await DispatchToLuisModelAsync(context, HomeAutomationLuisKey);

            // Here, you can add code for calling the hypothetical home automation service, passing in any entity
            // information that you need.
            break;
        case weatherDispatchKey:
            await DispatchToLuisModelAsync(context, WeatherLuisKey);

            // Here, you can add code for calling the hypothetical weather service,
            // passing in any entity information that you need
            break;
        case noneDispatchKey:
            // You can provide logic here to handle the known None intent (none of the above).
            // In this example we fall through to the QnA intent.
        case qnaDispatchKey:
            await DispatchToQnAMakerAsync(context, QnAMakerKey);
            break;

        default:
            // The intent didn't match any case, so just display the recognition results.
            await context.SendActivityAsync($"Dispatch intent: {topIntent.Value.intent} ({topIntent.Value.score}).");
            break;
    }
}

// Dispatches the turn to the request QnAMaker app.
private async Task DispatchToQnAMakerAsync(
    ITurnContext context,
    string appName,
    CancellationToken cancellationToken = default(CancellationToken))
{
    if (!string.IsNullOrEmpty(context.Activity.Text))
    {
        var results = await _services.QnAServices[appName].GetAnswersAsync(context).ConfigureAwait(false);
        if (results.Any())
        {
            await context.SendActivityAsync(results.First().Answer, cancellationToken: cancellationToken);
        }
        else
        {
            await context.SendActivityAsync($"Couldn't find an answer in the {appName}.");
        }
    }
}


// Dispatches the turn to the requested LUIS model.
private async Task DispatchToLuisModelAsync(
    ITurnContext context,
    string appName,
    CancellationToken cancellationToken = default(CancellationToken))
{
    await context.SendActivityAsync($"Sending your request to the {appName} system ...");
    var result = await _services.LuisServices[appName].RecognizeAsync(context, cancellationToken);

    await context.SendActivityAsync($"Intents detected by the {appName} app:\n\n{string.Join("\n\n", result.Intents)}");

    if (result.Entities.Count > 0)
    {
        await context.SendActivityAsync($"The following entities were found in the message:\n\n{string.Join("\n\n", result.Entities)}");
    }
}