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botbuilder-dialogs-adaptive
Advanced tools
Rule system for the Microsoft BotBuilder dialog system.
A dialog stack based conversation manager for Microsoft BotBuilder.
To add the latest version of this package to your bot:
npm install --save botbuilder-dialogs
If you want to play with the very latest versions of botbuilder, you can opt in to working with the daily builds. This is not meant to be used in a production environment and is for advanced development. Quality will vary and you should only use daily builds for exploratory purposes.
To get access to the daily builds of this library, configure npm to use the MyGet feed before installing.
npm config set registry https://botbuilder.myget.org/F/botbuilder-v4-js-daily/npm/
To reset the registry in order to get the latest published version, run:
npm config set registry https://registry.npmjs.org/
This module includes a system for managing multi-turn conversations within a Microsoft Botbuilder app, including tools for creating and managing dialog systems, a means for creating custom interoperable dialog systems, and a series of useful prompts that provide type checking and validation of input.
After adding the module to your application, modify your app's code to import the multi-turn dialog management capabilities. Near your other import
and require
statements, add:
// Import some of the capabities from the module.
const { DialogSet, WaterfallDialog } = require("botbuilder-dialogs");
Then, create one or more DialogSet
objects to manage the dialogs used in your bot.
A DialogSet is used to collect and execute dialogs. A bot may have more than one
DialogSet, which can be used to group dialogs logically and avoid name collisions.
Then, create one or more dialogs and add them to the DialogSet. Use the WaterfallDialog class to construct dialogs defined by a series of functions for sending and receiving input that will be executed in order.
More sophisticated multi-dialog sets can be created using the ComponentDialog
class, which
contains a DialogSet, is itself also a dialog that can be triggered like any other. By building on top ComponentDialog,
developer can bundle multiple dialogs into a single unit which can then be packaged, distributed and reused.
// Set up a storage system that will capture the conversation state.
const storage = new MemoryStorage();
const convoState = new ConversationState(storage);
// Define a property associated with the conversation state.
const dialogState = convoState.createProperty('dialogState');
// Initialize a DialogSet, passing in a property used to capture state.
const dialogs = new DialogSet(dialogState);
// Each dialog is identified by a unique name used to invoke the dialog later.
const DIALOG_ONE = 'dialog_identifier_value';
// Add a dialog. Use the included WaterfallDialog type, or build your own
// by subclassing from the Dialog class.
dialogs.add(new WaterfallDialog(DIALOG_ONE, [
async (step) => {
// access user input from previous step
var last_step_answer = step.result;
// send a message to the user
await step.context.sendActivity('Send a reply');
// continue to the next step
return await step.next();
// OR end
// return await step.endDialog();
},
step2fn,
step3fn,
...,
stepNfn
]));
Finally, from somewhere in your bot's code, invoke your dialog by name:
// Receive and process incoming events into TurnContext objects in the normal way
adapter.processActivity(req, res, async (turnContext) => {
// Create a DialogContext object from the incoming TurnContext
const dc = await dialogs.createContext(turnContext);
// ...evaluate message and do other bot logic...
// If the bot hasn't yet responded, try to continue any active dialog
if (!turnContext.responded) {
const status = await dc.continueDialog();
}
// Invoke the dialog we created above.
if (!turnContext.responded) {
await dc.beginDialog(DIALOG_ONE);
}
});
See this module in action in these example apps:
Prompts This module contains several types of built-in prompt that can be used to create dialogs that capture and validate specific data types like dates, numbers and multiple-choice answers.
DialogSet DialogSet is a container for multiple dialogs. Once added to a DialogSet, dialogs can be called and interlinked.
WaterfallDialog WaterfallDialogs execute a series of step functions in order, passing the resulting user input from each steo into the next step's function.
Track Waterfall Dialogs with Application Insights.
ComponentDialog ComponentDialogs are containers that encapsulate multiple sub-dialogs, but can be invoked like normal dialogs. This is useful for re-usable dialogs, or creating multiple dialogs with similarly named sub-dialogs that would otherwise collide.
FAQs
Rule system for the Microsoft BotBuilder dialog system.
The npm package botbuilder-dialogs-adaptive receives a total of 542 weekly downloads. As such, botbuilder-dialogs-adaptive popularity was classified as not popular.
We found that botbuilder-dialogs-adaptive demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 0 open source maintainers collaborating on the project.
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