In this tutorial, we will explore several popular chatbot development platforms. Our goal is to familiarize ourselves with these platforms and learn to navigate their interfaces and features.
By the end of this tutorial, you will be able to:
- Understand the different chatbot development platforms available.
- Navigate and use these platforms.
- Create simple chatbots using these platforms.
Prerequisites:
- Basic understanding of programming concepts.
- An open mind ready to explore and learn.
Chatbot development platforms provide a set of tools to create, test, and deploy chatbots. They typically offer a visual interface to define conversations and program the chatbot's responses.
Let's take a look at some popular platforms:
Dialogflow (by Google): This platform uses machine learning to understand user intent and generate responses. It supports multiple languages and platforms like Facebook Messenger, Slack, and more.
Microsoft Bot Framework: This platform allows you to build chatbots that can interact with users in a natural way using text, cards, or speech. It supports multiple languages and platforms.
IBM Watson: Watson Assistant provides tools to build, test and deploy conversational interactions into any application, device or channel.
The choice of platform depends on your specific needs, including the desired complexity of the chatbot, the platform where the chatbot will be deployed, and the languages it needs to support.
Since each platform has its own specific way of defining chatbots, I'll provide examples that illustrate the basics of creating a chatbot on each platform.
To create a simple chatbot on Dialogflow:
This isn't actual code, but it gives you an idea of the steps involved in creating a chatbot on Dialogflow.
In Microsoft Bot Framework, you typically write code to define your chatbot. Here's a simple example in Node.js:
var restify = require('restify');
var builder = require('botbuilder');
// Setup Restify Server
var server = restify.createServer();
server.listen(process.env.port || process.env.PORT || 3978, function () {
console.log('%s listening to %s', server.name, server.url);
});
// Create chat connector for communicating with the Bot Framework Service
var connector = new builder.ChatConnector({
appId: process.env.MICROSOFT_APP_ID,
appPassword: process.env.MICROSOFT_APP_PASSWORD
});
// Listen for messages from users
server.post('/api/messages', connector.listen());
// This is a dinner reservation bot that uses a waterfall technique to prompt users for input.
var bot = new builder.UniversalBot(connector, function (session) {
session.send("Welcome to the dinner reservation.");
session.beginDialog('askForDateTime');
});
// Dialog to ask for a date and time
bot.dialog('askForDateTime', [
function (session) {
builder.Prompts.time(session, "Please provide a reservation date and time (e.g.: June 6th at 5pm)");
},
function (session, results) {
session.endDialogWithResult(results);
}
]);
On IBM Watson, you can use the Watson Assistant tool to create a chatbot. Like Dialogflow, this is mainly done through the interface, but you can also use the Watson Assistant API to create more complex chatbots.
In this tutorial, we have explored several chatbot development platforms, including Dialogflow, Microsoft Bot Framework, and IBM Watson. Each platform offers its own set of tools and advantages, and your choice of platform will depend on the specific needs of your chatbot.
Remember that learning is a process and practice is key. Keep exploring these platforms and try creating different chatbots to improve your skills.