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README.md

CoreBot with Application Insights

Bot Framework v4 core bot sample.

This bot has been created using Bot Framework, it shows how to:

  • Use LUIS to implement core AI capabilities
  • Implement a multi-turn conversation using Dialogs
  • Handle user interruptions for such things as Help or Cancel
  • Prompt for and validate requests for information from the user
  • Use Application Insights to monitor your bot

This sample is a Spring Boot app and uses the Azure CLI and azure-webapp Maven plugin to deploy to Azure.

Prerequisites

  • Java 1.8+
  • Install Maven
  • An account on Azure if you want to deploy to Azure.

Overview

This bot uses LUIS, an AI based cognitive service, to implement language understanding and Application Insights, an extensible Application Performance Management (APM) service for web developers on multiple platforms.

Create a LUIS Application to enable language understanding

LUIS language model setup, training, and application configuration steps can be found here.

If you wish to create a LUIS application via the CLI, these steps can be found in the README-LUIS.md.

Add Application Insights service to enable the bot monitoring

Application Insights resource creation steps can be found here.

To try this sample

  • From the root of this project folder:
    • Build the sample using mvn package
    • Run it by using java -jar .\target\bot-corebot-app-insights-sample.jar

Testing the bot using Bot Framework Emulator

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 latest Bot Framework Emulator from here

Connect to the bot using Bot Framework Emulator

  • Launch Bot Framework Emulator
  • File -> Open Bot
  • Enter a Bot URL of http://localhost:3978/api/messages

Deploy the bot to Azure

As described on Deploy your bot, you will perform the first 4 steps to setup the Azure app, then deploy the code using the azure-webapp Maven plugin.

1. Login to Azure

From a command (or PowerShell) prompt in the root of the bot folder, execute:
az login

2. Set the subscription

az account set --subscription "<azure-subscription>"

If you aren't sure which subscription to use for deploying the bot, you can view the list of subscriptions for your account by using az account list command.

3. Create an App registration

az ad app create --display-name "<botname>" --password "<appsecret>" --available-to-other-tenants

Replace <botname> and <appsecret> with your own values.

<botname> is the unique name of your bot.
<appsecret> is a minimum 16 character password for your bot.

Record the appid from the returned JSON

4. Create the Azure resources

Replace the values for <appid>, <appsecret>, <botname>, and <groupname> in the following commands:

To a new Resource Group

az deployment sub create --name "corebotAppInsightsDeploy" --location "westus" --template-file ".\deploymentTemplates\template-with-new-rg.json" --parameters appId="<appid>" appSecret="<appsecret>" botId="<botname>" botSku=S1 newAppServicePlanName="corebotAppInsightsPlan" newWebAppName="corebotAppInsights" groupLocation="westus" newAppServicePlanLocation="westus"

To an existing Resource Group

az deployment group create --resource-group "<groupname>" --template-file ".\deploymentTemplates\template-with-preexisting-rg.json" --parameters appId="<appid>" appSecret="<appsecret>" botId="<botname>" newWebAppName="corebotAppInsights" newAppServicePlanName="corebotAppInsightsPlan" appServicePlanLocation="westus" --name "corebotAppInsights"

5. Update app id and password

In src/main/resources/application.properties update

  • MicrosoftAppPassword with the botsecret value
  • MicrosoftAppId with the appid from the first step

6. Deploy the code

  • Execute mvn clean package
  • Execute mvn azure-webapp:deploy -Dgroupname="<groupname>" -Dbotname="<bot-app-service-name>"

If the deployment is successful, you will be able to test it via "Test in Web Chat" from the Azure Portal using the "Bot Channel Registration" for the bot.

After the bot is deployed, you only need to execute #6 if you make changes to the bot.

Further reading