Tag Archives: botframework

Create your first QnA bot using botframework’s QnA Maker

When talking about the botframework, and chatbots in general, people usually assume that these are all using some clever logic and Natural Language Processing (NLP) to deliver a chunk of business logic via a natural language interface.

With the botframework this is most likely implemented by wiring up the Language Understanding Intelligent Service (LUIS): originally a stand-alone, (optionally) self-training, natural language understanding service, but now part of Microsoft Research’s Cognitive Services – previously “Project Oxford” – a collection of extremely powerful machine learning APIs for processing images, video, text, speech, to extract meaning.

Exceptionally powerful, incredibly clever stuff.

Almost all botframework articles and tutorials you’ll see at the moment will either do very basic pattern matching to extract intent from a message, or they’ll use LUIS (or a combination of the two); how to use LUIS is the subject of another article entirely, since this is no small task (I’ll come back to this in another article).

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Debugging BotFramework locally using ngrok

No doubt you’re already having lovely long conversations with your bot via Skype (or Facebook Messenger, or even SMS!) built using the botframework, and by using the Bot Emulator you can run your bot locally and debug it.

However, once it’s deployed and is being called via the Bot Connector framework, instead of directly, things get a bit tougher.

If you haven’t managed to override the – rather nasty – default exception handling that swallows exceptions and spews out reams of useless stack trace, then you may not have much idea what’s going on with your deployed bot, since all you get back is “Sorry, my bot code is having a problem.”

When you encounter a strange problem whilst conversing with your bot in Skype, going through the process of adding loads of logging and redeploying, trying again, checking logs – just to see the journey your bot code is going through – isn’t the most efficient.

If only you could debug the code on your development PC just as easily as you could before the bot was deployed, locally in Visual Studio…

In this article I’m going to show you how to debug your bot code from Skype though to your local PC’s Visual Studio instance, thanks to the amazing ngrok!

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Persisting data within a conversation with botframework’s dialogs

In the previous botframework article I covered the different types of responses available for the botframework. This article is going to touch on the Dialog and persisting information between subsequent messages.

So what’s a Dialog?

Dialogs can call child dialogs or send messages to a user. Dialogs are suspended when waiting for a message from the user to the bot. Dialogs are resumed when the bot receives a message from the user.

To create a Dialog, you must implement the IDialog<T> interface and make your dialog class serializable, something like this:

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Rich botframework conversation cards

In the last article about bots I covered creating a basic bot using Microsoft’s botframework, setting up Azure, deploying the bot into Azure, and configuring it to work within Skype.

In this article we’re going to investigate the various response types available to us in the botframework to develop a more rich conversational experience.

Markdown

Luckily you’re not limited to plain text in a bot conversation; we’re able to embed images, add attachments, give headers and subheaders, add a button or link, tap events for various areas, as well as use markdown to format the main text content.

If you’re not already familiar with Markdown, then get on the case! It means you can very easily write HTML by using a shorthand syntax which can easily be converted to HTML.

I’ve been using it for many years for blogging and general documentation; using pandoc you can even convert markdown to PDF or a Word Doc. Using remark.js or the more recent Marp you can use it to easily create PowerPoint-like presentations

markdown example

Botframework messages support using this syntax to make the responses more rich. Of course, for this to work, the attached service needs to know how to render the response (and I’ll get on to this later)

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Create your first botframework bot in Azure!

At //Build 2016 Microsoft unleashed something known as the Bot Framework; a set of three products to help you build conversational bots and connect them with services, like Slack, Skype, and even Email and SMS.

The Bot Framework has a number of components including the Developer Portal, Bot Builder, and the Bot Directory:

  • Developer Portal is where you wire your bot up to existing services like Skype and Slack
  • Bot Directory is where you publish your bot to so that others can search for and connect it to their Skype and Slack
  • Bot Builder is what you use to implement a more complex and intelligent conversational flow, optionally leveraging the awesome power of some of the Microsoft Research’s Cognitive Services for language interpretation, image recognition, and much more.

In this article I’m going to take you through the process of creating, deploying, and configuring your own Skype bot.

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