Microsoft Bot Builder Instrumentation
This module is used to add instrumentation to bots built with Microsoft Bot Framework.
You can leverage the events from this module using Ibex Dashboard.
Getting Started
- Create an Application Insights service under your subscription.
- Use the
Instrumentation Key
inside your bot registration page under Instrumentation key.
Connect to Cognitive Services
This is an optional step in case you want user messages to be analyzed for sentiments.
Create a new Sentiment Analysis Service under Cognitive Services.
When creating the service, make sure to mark Text Analytics - Preview.
Setting Environment Variables
You can use the following option for running locally.
APPINSIGHTS_INSTRUMENTATIONKEY={App Insights Instrumentation Key}
CG_SENTIMENT_KEY={Cognitive Services Text Analytics Key}
CG_SENTIMENT_KEY
is optional.
Adding instrumentation to your code
const instrumentation = require('botbuilder-instrumentation');
let logging = new instrumentation.BotFrameworkInstrumentation({
instrumentationKey: process.env.APPINSIGHTS_INSTRUMENTATION_KEY,
sentiments: {
key: process.env.CG_SENTIMENT_KEY,
}
});
let recognizer = new builder.LuisRecognizer('...');
logging.monitor(bot, recognizer);
If you're not using a `LuisRecognizer', use the following code in addition:
var instrumentation = require('botbuilder-instrumentation');
let logging = new instrumentation.BotFrameworkInstrumentation({
instrumentationKey: process.env.APPINSIGHTS_INSTRUMENTATION_KEY,
sentiments: {
key: process.env.CG_SENTIMENT_KEY,
}
});
logging.monitor(bot);
Although CG_SENTIMENT_KEY
is optional, it is recommended if you're using Ibex Dashboard, in which case, adding sentiment analysis will add sentiments overview to the dashboard along with a sentiment icon next to all conversations.
Sending logs for QnA maker service
logging.trackQNAEvent(context, userQuery, kbQuestion, kbAnswer, score);
You can see how to implement a QnA service here.
Additional settings
let logger = new instrumentation.BotFrameworkInstrumentation({
instrumentationKey: process.env.APPINSIGHTS_INSTRUMENTATION_KEY,
sentiments: {
key: process.env.CG_SENTIMENT_KEY,
},
omitUserName: true,
autoLogOptions: {
autoCollectConsole: true,
autoCollectExceptions: true,
autoCollectRequests: true,
autoCollectPerf: true
}
customFields: {
userData: [ "CUSTOM_PROPERTY_1" ],
dialogData: [ "CUSTOM_PROPERTY_2" ],
conversationData: [ "CUSTOM_PROPERTY_3" ],
privateConversationData: [ "CUSTOM_PROPERTY_4" ]
}
});
The CUSTOM_PROPERTY
will be searched for in the session/context object of each event and will be added automatically under customDimensions in Application Insights.
If it does not exist, it will not be added to the logged events.
You can use any, all or none of the property bags under session: userData
, conversationData
, privateConversationData
, dialogData
.
Logging custom events
You can track generic goal triggers, just like you would trigger a goal in Google Analytics for a web site. A triggered goal has a name and
optionally custom properties that can be attached to the goal. Triggered goals can be seen in the Generic Goals Triggered dashboard template.
let customEventName = 'myCustomEventName';
let customEventData = { customDataA: 'customValueA', customDataB: 3 };
logging.trackCustomEvent(customEventName, customEventData, session);
logging.trackCustomEvent(customEventName, customEventData);
logging.trackEvent(customEventData);
Logging generic goal triggers
let customEventData = { customDataA: 'customValueA', customDataB: 3 };
logging.trackGoalTriggeredEvent(goalName, customEventData, session);
You can see a working sample in morsh/bot-with-instrumentation
License
This project is licensed under the MIT License.