Alexa.Tip – Build Intent Handlers in .NET

In this Alexa.Tip series, we explore some little bits of code that can make your life easier in developing Alexa Skills in many languages including C# + .NET, node.jS + TypeScript, Kotlin, etc. We look at concepts that developers might not be aware of, design patterns that and how they can be applied to voice application development, best practices, and more!

In this post, we explore some more best practices in developing Alexa Skills in C# whether you are using an ASP.NET Core API or an AWS Lambda. This time, we talk about abstracting our business logic out of either our Function or Controller and into separate Handler classes.

If you’ve done skill development in node.js or in .NET, you’ve probably noticed that a lot of docs, example apps, and real world apps are written with one BIG class or file. That’s pretty gross.

You may some C# examples look like this:

UglyFunction.cs

public class Function
{
    public async Task<SkillResponse> HandleRequest(SkillRequest input)
    {
        if(input.GetRequestType() == typeof(LaunchRequest))
        {
            return ResponseBuilder.Ask("Welcome to my skill written in one big function class with all my business logic in one place and no real testability! Ask me anything!", null);
        }

        if(input.GetRequestType() == typeof(IntentRequest))
        {
            var intentRequest = input.Request as IntentRequest;

            switch(intentRequest.Intent.Name)
            {
                case "MyIntent1":
                    // get slot values
                    // search database
                    // validate data
                    // build response 
                    // add card if it supports a screen
                    // return
                    break;
                case "Intent2":
                    // get slot values
                    // search third party api
                    // validate data
                    // build response 
                    // add card if it supports a screen
                    // return
                    break;
                case "Intent3":
                    // get slot values
                    // search database
                    // validate data
                    // build response 
                    // add card if it supports a screen
                    // return
                    break;
                case "Intent4":
                    // get slot values
                    // search third party api
                    // validate data
                    // build response 
                    // add card if it supports a screen
                    // return
                    break;
                case "Intent5":
                    // get slot values
                    // search database
                    // validate data
                    // build response 
                    // add card if it supports a screen
                    // return
                    break;

                // I think you get my point here...
            }
        }

        return ResponseBuilder.Tell("Something went wrong. Please try again later");
    }
}

So that’s pretty gross right? It’s untestable, difficult to update, and hard to read! But hey, we’re C# developers. So let’s build Alexa Skills like C# developers.

The proposal here is to abstract your intent logic into Handler classes. Then you can inject those either into your Function or your Controller if you’re using a RESTful API.

Here’s something that I hope can get you started:
– A generic IIntentHandler
– An inherited specific IIntentWhateverHandler
– An implementation of the IIntentWhateverHandler
– A testable and injectable version to be used in the function.

Let’s start.

IIntentHandler.cs

public interface IIntentHandler
{
    Task<SkillResponse> HandleIntent(IntentRequest input);
}

Now let’s get specific. In this simple case, this interface is empty but exists for registration – although you can add specific methods here as needed.

IMyIntentHandler.cs

public interface IMyIntentHandler : IIntentHandler
{
}

Now let’s create an example implementation of an intent handler that houses the business logic of the request.

MyIntentHandler.cs

public class MyIntentHandler : IMyIntentHandler
{
    private readonly MyDbContext _context;
    public MyIntentHandler(MyDbContext context)
    {
        // oh snap, we can inject db context
        _context = context;
    }

    public async Task<SkillResponse> HandleIntent(IntentRequest input)
    {
        var mySlot = input.Slots["MySlot"].Value; // assumes the slot is there from it being required in the interaction model
        var myMessage = await _context.Messages.FirstOrDefaultAsync(m => m.SomeValue == mySlot)

        if(myMessage == null)
        {
            return ResponseBuilder.Ask("I don't know that one. Try something else.");
        }

        return ResponseBuilder.Tell(myMessage.Content);
    }
}

Now let’s go about adding these handlers to our Function (the same thing can apply to our Controllers.

PrettyFunction.cs

public class Function
{
    private readonly IMyIntentHandler _myIntentHandler;

    private void Setup()
    {
        _myIntentHandler = new MyIntentHandler(...);
        // create the others - optionally implement a ServiceCollection
        // to handle proper dependency injection
    }
    public async Task<SkillResponse> HandleRequest(SkillRequest input)
    {
        if(input.GetRequestType() == typeof(LaunchRequest))
        {
            return ResponseBuilder.Ask("Welcome to my skill written in one big function class with all my business logic in one place and no real testability! Ask me anything!", null);
        }

        if(input.GetRequestType() == typeof(IntentRequest))
        {
            var intentRequest = input.Request as IntentRequest;

            switch(intentRequest.Intent.Name)
            {
                case "MyIntent1":
                    return await _myIntentHandler.HandleIntent(intentRequest);
                    break;
            }
        }

        return ResponseBuilder.Tell("Something went wrong. Please try again later");
    }
}

So now you can separately test your Handler classes, your Data classes, and your Function as a whole.

SO much better šŸ™‚

Conclusion

We don’t have to follow how Amazon writes their node.js skills when we write them in C# – let’s use some proper OO design and testability to build some scalable and awesome skills!

In the next post, we’ll talk about taking this one step closer to avoid that gross switch statement and simply register our Handler implementations for certain intents or RequestTypes which is more similar to how the actual ASK SDK works.

Stay tuned!


If you like what you see, donā€™t forget to follow me on twitter @Suave_Pirate, check out my GitHub, and subscribe to my blog to learn more mobile and AI developer tips and tricks!

Interested in sponsoring developer content? MessageĀ @Suave_PirateĀ on twitter for details.


voicify_logo
I’m the Director and Principal Architect over at Voicify. Learn how you can use the Voice Experience Platform to bring your brand into the world of voice on Alexa, Google Assistant, Cortana, chat bots, and more: https://voicify.com/


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Alexa.Tip – Access Lambda Environment Variables in .NET

In this Alexa.Tip series, we explore some little bits of code that can make your life easier in developing Alexa Skills in many languages including C# + .NET, node.jS + TypeScript, Kotlin, etc. We look at concepts that developers might not be aware of, design patterns that and how they can be applied to voice application development, best practices, and more!

In this post, we’ll look at a simple tip to help secure your Alexa Skills when using an AWS Lambda. In a future post, we’ll look at a similar concept in .NET for developers using ASP.NET Core Web API instead of Lambdas.

So, you’ve taken the step to building proper data-driven Alexa Skills and have stepped out of the simple “todo” examples. Perhaps you need a database connection in your source code, need to change values depending on what environment you are running the skill in, or want to run your skill with options you can change without having to redeploy the codebase over and over again.

For all of these problems, your best bet is to use the Lambda Environment variables. Doing it is INCREDIBLY simple, yet I still see many developers unaware of how to use them and instead use runtime checks or don’t bother scaling their application at all to needing them.

In this example, we’ll look at how to create an instance of an Entity Framework DbContext and set it up for a testable injection based project.

Let’s look at a code snipet example of a piece of an Alexa Skill running in a .NET Lambda using a hard coded connection string:

Message.cs

// a simple table to represent some messages we can grab
public class Message
{
    public int Id { get; set; }
    public string Content { get; set; }
}

And here’s our DbContext we are going to grab data from:
MessageDbContext.cs

public class MessageDbContext : DbContext 
{
    public DbSet<Message> Messages { get; set; }

    public MessageDbContext(DbContextOptions options) : base(options) { }
}

Now check out a lambda I typically see with hard coded connection strings and settings:

BadLambda.cs

public class BadLambda
{
    // an EF DbContext with some message tables
    private readonly MessageDbContext _context;

    public BadLambda()
    {
        var optionsBuilder = new DbOptionsBuilder<MessageDbContext>()
            .UseSqlServer("my_connection_string", providerOptions => providerOptions.CommandTimeout(60));
        _context = new MessageDbContext(optionsBuilder.options);
    }

    public async Task<SkillResponse>(SkillRequest input)
    {
        var message = await _context.Messages.FirstOrDefaultAsync();
        return ResponseBuilder.Tell(message.Content);
    }
}

So breaking down the code… We have an EF DbContext with one table called “Messages” which has a column of Id and Content, and our Skill Lambda sets up the DbContext with a hard coded connection string and timeout setting, then returns the first messages as a simple response.

Let’s take this lambda and add environment variables so we can run mutliple environments for multiple dbs including a localhost db if we wanted to test locally before deploying to Lambda and so we can test updates before we make changes to our production skill!

In AWS

Head over to your lambda in AWS and scroll down to “Environment Variables”:
Labmda_env

Here you can add any key-value pairs you want. For this demo, we want to put our database connection string and our timeout setting here:

Lambda_env_filled

Now make sure you smash that save button and head back to Visual Studio to make our final updates!

Don’t forget you can now also create another lambda for a development or staging environment separate from your production lambda – be sure to use a different database connection in your environment variables, and then you can publish to both šŸ˜€

In the Code

Now we just have to use the

Environment.GetEnvironmentVariable(string key);

method to grab the values of these environment variables we set up and we’re off to the races!

Here’s what that looks like when updates:

GoodLambda.cs

public class GoodLambda
{
    // an EF DbContext with some message tables
    private readonly MessageDbContext _context;

    public GoodLambda()
    {
        var connectionString = Environment.GetEnvironmentVariable("DatabaseConnectionString");
        var timeoutSetting = Environment.GetEnvironmentVariable("DatabaseCommandTimeout");
        var optionsBuilder = new DbOptionsBuilder<MessageDbContext>()
            .UseSqlServer(connectionString, providerOptions => providerOptions.CommandTimeout(int.Parse(timeoutSetting)));
        _context = new MessageDbContext(optionsBuilder.options);
    }

    public async Task<SkillResponse>(SkillRequest input)
    {
        var message = await _context.Messages.FirstOrDefaultAsync();
        return ResponseBuilder.Tell(message.Content);
    }
}

Now publish it to your lambda and you’re done!

Recap

  • For the love of god, stop hard coding connection strings and settings in your lambda
  • Use environment variables
  • Setup multiple environments for scalability and testability
  • Abuse Environment.GetEnvironmentVariable()
  • Build more Alexa Skill šŸ™‚

If you like what you see, donā€™t forget to follow me on twitter @Suave_Pirate, check out my GitHub, and subscribe to my blog to learn more mobile and AI developer tips and tricks!

Interested in sponsoring developer content? MessageĀ @Suave_PirateĀ on twitter for details.


voicify_logo
I’m the Director and Principal Architect over at Voicify. Learn how you can use the Voice Experience Platform to bring your brand into the world of voice on Alexa, Google Assistant, Cortana, chat bots, and more: https://voicify.com/


Alexa.Tip – How to Host Alexa Skills in Azure

If you’re a .NET developer in the Azure cloud sphere and want to start dabbling in Alexa Skill Development, you don’t have to uproot your entire career and development process to go learn AWS, how Lambdas work, the serverless lifecycle, etc. In this post, we’ll go over just how easy it can be to build an Alexa Skill using C#, ASP.NET Core, and Azure!

The traditional setup for Alexa Skills is:
– AWS Lambda
– .NET Core Lambda project template

But we’re going to be using:
– Azure App Services
– ASP.NET Core API project template

NOTE: This is not an introduction into how Alexa skills work, or how to create your very first skill. This is meant to provide options for hosting your skills, and for how to build skills in general using .NET. If you’re BRAND new to Alexa Skill development, start by reading through their documentation (mostly using node.js, but focus on the structure of an interaction model, what intents and slots are, etc.)

For source of the entire project checkout: https://github.com/SuavePirate/Alexa.NET.WebApi

Step 1 – Create an Alexa Developer Account

If you haven’t already created an Alexa Developer account, you’ll need one in order to register and test your skill.

Simply follow, the Amazon documentation on how to do this – super simple: https://developer.amazon.com/alexa

Step 2 – Create a Skill in the Developer Console

With your Alexa developer account, create a new Skill.

Choose Custom Skill:

create_skill

Then choose the empty “Start from Scratch” template:

choose_template

Now you can manage your interaction model.

For this example, we are going to create a skill that let’s users ask for information about Animals. We’ll use a custom Intent for this, but use the built in AMAZON.Animal slot.

On the left side, go to JSON Editor and paste this interaction model. You can make adjustments as you see fit:

interactionModel.json

{
  "interactionModel": {
    "languageModel": {
      "invocationName": "animal facts",
      "intents": [
        {
          "name": "AMAZON.FallbackIntent",
          "samples": []
        },
        {
          "name": "AMAZON.CancelIntent",
          "samples": [
            "I'm all set"
          ]
        },
        {
          "name": "AMAZON.HelpIntent",
          "samples": []
        },
        {
          "name": "AMAZON.StopIntent",
          "samples": [
            "Quit",
            "Goodbye"
          ]
        },
        {
          "name": "AnimalFactIntent",
          "slots": [
            {
              "name": "Animal",
              "type": "AMAZON.Animal"
            }
          ],
          "samples": [
            "I'd like to know about {Animal}",
            "What is an {Animal}",
            "Give me information about the {Animal}",
            "Tell me about {Animal}"
          ]
        }
      ],
      "types": []
    }
  }
}

This allows our users to ask things such as “Tell me about Monkeys” and then use the animal they are asking for to send information back to them!

Step 3 – Create the ASP.NET Core API

In Visual Studio, create a new project and choose the ASP.NET Core Web Application:

aspnetcore

In the next dialog, select the API template, and be sure that HTTPS is enabled:

API_project_with_https

With your new web application, you’ll need to install the Alexa.NET Nuget Package from Tim Heuer
https://www.nuget.org/packages/Alexa.NET/1.5.5-pre

This nuget package has models for the JSON that Alexa sends to your API and a convenient fluid API design for building your responses that is similar to how the actual Alexa Java and JavaScript SDKs work.

Now that the Alexa models are available, let’s create a new API controller:

AlexaController.cs

[Route("api/[controller]")]
public class AlexaController : Controller
{
    /// <summary>
    /// This is the entry point for the Alexa skill
    /// </summary>
    /// <param name="input"></param>
    /// <returns></returns>
    [HttpPost]
    public SkillResponse HandleResponse([FromBody]SkillRequest input)
    {
        var requestType = input.GetRequestType();

        // return a welcome message
        if(requestType == typeof(LaunchRequest))
        {
            return ResponseBuilder.Ask("Welcome to animal facts, ask me about information on an animal", null);
        }

        // return information from an intent
        else if (requestType == typeof(IntentRequest))
        {
            // do some intent-based stuff
            var intentRequest = input.Request as IntentRequest;

            // check the name to determine what you should do
            if (intentRequest.Intent.Name.Equals("AnimalFactIntent"))
            {
                // get the slots
                var animal = intentRequest.Intent.Slots["Animal"].Value;
                if(animal == null)
                    return ResponseBuilder.Ask("You forgot to ask about an animal! Please try again.", null);

                return ResponseBuilder.Tell($"I would normally tell you facts about ${animal} but I'm not a real skill yet.");
            }
        }

        return ResponseBuilder.Ask("I didn't understand that, please try again!", null);
    }
}

This controller contains a single HTTP POST endpoint that takes in an SkillRequest. It then breaks down the request in order to respond accordingly. So if the user opens the skill which initiates the LaunchRequest, we can give them a welcome message with hints on what they can ask about. Then if they ask for information about an animal, we can handle the IntentRequest with the intent name of “AnimalFactIntent” and use the Animal slot value!

That’s all there is too it! I’d normally suggest abstracting this out of using the controller so that it is more easily testable with unit tests, but for the sake of a simple example, it will work fine.

Step 4 – Publish to Azure App Service

Now that we have our ASP.NET Core project, we need to publish it to an Azure App Service. You can do this directly in Visual Studio or in the Azure portal. For the sake of this example, we’ll do it directly in Visual Studio – assuming you have a valid Azure license and account setup.

From the Solution Explorer – right click your project and Select “Publish”.

Select the “App Service” option and click “Create”.

Then fill out the form to create a new App Service:
AzurePublish

Once your publish is done, you’ll need to ensure that HTTPS / SSL is configured correctly for your app service.

In the Azure portal, go to your new App Service, then scroll to the SSL Settings section.

Be sure that you enforce SSL (Alexa requires endpoints to use HTTPS with trusted certificates. The default App Service SSL cert is signed with Microsoft’s trusted certificate which means that Amazon will accept it).

azure_ssl.PNG

Now make sure that you can hit your App service API endpoint. I usually prefer to enable Swagger for my API using Swashbuckle for this: https://docs.microsoft.com/en-us/aspnet/core/tutorials/getting-started-with-swashbuckle?view=aspnetcore-2.1&tabs=visual-studio%2Cvisual-studio-xml

Step 5 – Register Endpoint with Alexa Skill

Now that we have our App Service with HTTPS set up, we need to go back to the Alexa Developer Console and to the skill. In the left menu, scroll down to the “Endpoint” option.

In the main view, select “HTTPS” instead of “AWS Lambda ARN”. Then enter the URL for the endpoint in your app service and choose the subdomain ssl cert option:
azure_alexa_endpoint

Once this is done, you can save, and build your skill then proceed to test it!

Step 6 – Test

In the Alexa Developer Console, go to your skill and select the “Test” tab. Here you can type or say things like “Open Animal Facts” or “Ask Animal Facts to tell me about Monkeys”.

animal skill test

Here you can also view the JSON that Alexa is sending to your skill and use that to test against your skill directly using something like Swagger or Postman.

Here’s an example JSON input you could use to test:

{
    "version": "1.0",
    "session": {
        "new": false,
        "sessionId": "...",
        "application": {
            "applicationId": "..."
        },
        "user": {
            "userId": "..."
        }
    },
    "context": {
        "AudioPlayer": {
            "playerActivity": "IDLE"
        },
        "Display": {
            "token": ""
        },
        "System": {
            "application": {
                "applicationId": "..."
            },
            "user": {
                "userId": "..."
            },
            "device": {
                "deviceId": "...",
                "supportedInterfaces": {
                    "AudioPlayer": {},
                    "Display": {
                        "templateVersion": "1.0",
                        "markupVersion": "1.0"
                    }
                }
            },
            "apiEndpoint": "https://api.amazonalexa.com",
            "apiAccessToken": "..."
        }
    },
    "request": {
        "type": "IntentRequest",
        "requestId": "...",
        "timestamp": "2018-09-04T17:07:45Z",
        "locale": "en-US",
        "intent": {
            "name": "AnimalFactIntent",
            "confirmationStatus": "NONE",
            "slots": {
                "Animal": {
                    "name": "Animal",
                    "value": "monkeys",
                    "confirmationStatus": "NONE"
                }
            }
        }
    }
}

You can also test on a real Alexa device! Once you enabled testing, any device that is assigned to the same email address as your Alexa Developer Account will have it enabled.

And that’s it! Now get out there and build some Alexa Skills in .NET!


If you like what you see, donā€™t forget to follow me on twitter @Suave_Pirate, check out my GitHub, and subscribe to my blog to learn more mobile and AI developer tips and tricks!

Interested in sponsoring developer content? MessageĀ @Suave_PirateĀ on twitter for details.


voicify_logo
I’m the Director and Principal Architect over at Voicify. Learn how you can use the Voice Experience Platform to bring your brand into the world of voice on Alexa, Google Assistant, Cortana, chat bots, and more: https://voicify.com/


Xamarin.Meetup – Boston Meetup Today: DevOps for Mobile Apps with Dan Hermes

Join us at Microsoft’s NERD Center to learn aboutĀ DevOps for Mobile Apps! Meet with some of the local Xamarin MVPs and employees while also enjoying some food.

https://www.meetup.com/bostonmobiledev/events/244933704/

How do we keep our iOS and Android builds organized, tested, and distributed to team members and users who need them, with the correct versions flowing into the app stores? This is DevOps for mobile apps.

Dan Hermes, Xamarin MVP and co-organizer of Boston Mobile C# Developers Group, will discuss the high points of hisĀ upcoming edX video course for MicrosoftĀ on how to do all of these things using Visual Studio Mobile Center (VSMC). He will talk about developing, deploying and managing mobile applications in DevOps environments. He’ll cover setup and management of VSMC and the testing and deployment of mobile apps. Mobile Center Build, Test, and Distribute are powered by Visual Studio Team System (VSTS), Xamarin Test Cloud, and HockeyApp. Ā Learn the VSMC workflows that tie all of these tools together.

This talk is for any and all native app developers, not just C#.Ā  Many features of VSMC work for Objective-C and Java just as well as Xamarin.

About the Speaker

Dan Hermes is a Xamarin MVP, Ā Microsoft MVP, and founder of Lexicon Systems, an award-winning Xamarin consulting firm. Mr. Hermes helps developers create great mobile apps and helps businesses develop a winning mobile strategy. His firm’s Xamarin projects include B4UFLY, a drone app for the Federal Aviation Administration, and a cross-platform app for Thermo Fisher Scientific which won a W3, a Davey award, and was a finalist for a Xammy award. Mr. Hermes’ clientele includes dozens of software-building firms such as Fidelity Investments, EDS, and Computerworld Magazine. He has spoken recently at Microsoft Ignite, IBM InterConnect, Microsoft Azure Day, Xamarin DevDays, and mobile user groups nationwide . His mobile cross-platform dev blog isĀ http://mobilecsharpcafe.com/. Connect with him on Twitter at @danhermes. Dan is a writer for MSDN Magazine, a video course instructor for Microsoft’s OpenEdX curriculum, and author of the best-selling Apress bookĀ Xamarin Mobile Application Development.

 

 

If you like what you see, donā€™t forget to follow me on twitter @Suave_Pirate, check out my GitHub, and subscribe to my blog to learn more mobile developer tips and tricks!

Interested in sponsoring developer content? MessageĀ @Suave_PirateĀ on twitter for details.

Xamarin.Meetup – Boston Meetup Today: Xamarin on Azure and Cognitive Services

Join us at Microsoft’s NERD Center to learn about using Azure Cognitive Services in your Xamarin apps! Meet with some of the local Xamarin MVPs and employees while also enjoying some food.

https://www.meetup.com/bostonmobiledev/events/242566795/

Xamarin on Azure and Cognitive Services

Mobile development and cloud technologies are very popular right now. If you are a C# developer and already created your first application with Xamarin, you might be interested in learning some more details about Xamarin and Xamarin Forms. You might also want to use all benefits of Azure in your application or jump right into advanced topics and select one (or a couple) Cognitive Services for your application to integrate with. You will be able to get a flavor of all those tools from this talk. Also final demo will add some visual understanding of the topic.

About the speaker

Veronika Kolesnikova is a web developer at UMass Medical School.

Passionate about backend web development, mainly with Microsoft technologies like C#, .NET, SQL, Azure. Loves to learn new development tools and languages and share the knowledge with the community. Recently started working with Xamarin and cannot wait to provide her insights.
Last year Veronika graduated with MS degree in Information Technology.
In her free time, she likes dancing, traveling and practicing aerial yoga.

 

If you like what you see, donā€™t forget to follow me on twitter @Suave_Pirate, check out my GitHub, and subscribe to my blog to learn more mobile developer tips and tricks!

Interested in sponsoring developer content? MessageĀ @Suave_PirateĀ on twitter for details.