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Building Bots with Microsoft Bot Framework

By : Gaddam

2.3 (3)

Buy this Book

Building Bots with Microsoft Bot Framework

2.3 (3)

By: Gaddam

Buy this Book

Overview of this book

Bots help users to use the language as a UI and interact with the applications from any platform. This book teaches you how to develop real-world bots using Microsoft Bot Framework. The book starts with setting up the Microsoft Bot Framework development environment and emulator, and moves on to building the first bot using Connector and Builder SDK. Explore how to register, connect, test, and publish your bot to the Slack, Skype, and Facebook Messenger platforms. Throughout this book, you will build different types of bots from simple to complex, such as a weather bot, a natural speech and intent processing bot, an Interactive Voice Response (IVR) bot for a bank, a facial expression recognition bot, and more from scratch. These bots were designed and developed to teach you concepts such as text detection, implementing LUIS dialogs, Cortana Intelligence Services, third-party authentication, Rich Text format, Bot State Service, and microServices so you can practice working with the standard development tools such as Visual Studio, Bot Emulator, and Azure.

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Free Chapter

Setting up Microsoft Bot Framework Dev Environment

Conversation as a Service (CaaS)

Your bot

The Bot Connector

The Bot Directory

Setting up the development environment

Messages

Cards and buttons

Groups

Calling

Summary

Developing Your First Bot Using the Connector and Builder SDK

Bots are evolving

Bots use cases

Developing your first bot

Creating our first bot

Post method

How to deploy and run the bot application in the Bot Framework emulator locally

How to use dialogs in bot applications

How to use FormFlow in the bot application

Summary

Developing WeatherBot Using Dialogs and LUIS

Language Understanding Intelligent Service (LUIS)

Intents and Entities

Training your bot using utterances

Development of WeatherBot code

Calling LUIS from the bot

Natural speech and Intent processing bot using Microsoft Cognitive Services

Identifying the name of a person, place, and company using LUIS

Training your app

Calling LUIS from the bot

Summary

Natural Speech and Intent Processing Bot Using Microsoft Cognitive Services

Microsoft Cognitive Services

Identifying the name of a person, place, and company using LUIS

Training your app using utterances

Calling LUIS from the bot

Summary

Developing Bots Using LUIS Prompt Dialogs with State and Nearby Bot Using Custom APIs

Employee Enroll bot using LUIS prompt dialogs

Creating the C# class for LUIS response

Bot state service

Developing a Nearby Bot using custom APIs

Summary

Developing an IVR Bot for a Bank Using Advanced Microsoft Bot Framework Technologies

High-level architectural diagram

Let's start coding

Storing the bot conversation (new account info) data in an Azure SQL database

Checking your savings account balance using the bot

Checking your current account balance using the bot

Paying your credit card bill using the bot

Deleting an account using the bot

Summary

Intelligent Bots with Microsoft Bot Framework and Service Fabric

Getting started using stateless microservices

Publishing a Service Fabric project in Azure

Summary

Developing Intelligent Facial Expression Identification Bot for IoT Using Azure and Power BI

Before getting started

Configuring Raspberry Pi and sensors

Device identity and registry with IoT Hub

Face API

Emotion API

Registering your Bot in Bot Framework

Configure Direct Line Channel

Develop an UWP app for Raspberry Pi device

Deploy Code in to Raspberry Pi

Show facial analytics data in Power BI

Summary

Publishing a Bot to Skype, Slack, Facebook, and the GroupMe Channel

Publishing bots to various channels

Registering your bot with Microsoft Bot Framework

Configuring channels

Summary

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Deploy Code in to Raspberry Pi

Now that we are done with the code for our project, let's look at the following steps to deploy code to the Raspberry Pi:

First, connect your Raspberry Pi to your developer machine using a LAN cable, or connect to your Wi-Fi router in the same network.
Download and install the Windows 10 IoT Core Dashboard tool from http://go.microsoft.com/fwlink/?LinkID=708576 .

Open it: after a few seconds it will show your Raspberry Pi device on the My Devices page shown in the following screenshot. Then, copy the IP address.

Before deploying the code, make sure that the registered device ID in Device Registry with IoT Hub step and your Raspberry Pi device name is the same. For example, in device registry step 1 given device Id as 101B and my Raspberry Pi device name 101B, both are same. So, we can identify and manage easily from IoT hub.