As a data scientist cannot directly integrate Watson Assistant chatbot directly into the UI frontend of the web applications, it is essential that the Watson Assistant Embedded configuration is done before building the Chatbot.With the help of Watson Assistant on IBM Cloud or Watson Studio on IBM Cloud, you can easily connect the built Watson Assistant Chatbot service into a website or a browser-dependent web applications or mobile applications, analyse the data, and enhance the data according to the user/business requirements.
<script>
window.watsonAssistantChatOptions = {
integrationID: "***-bc18-4a67-a017-**", // Replace this with the integration ID of your Watson Assistant here.
region: "us-south", // The region your integration is hosted in.
serviceInstanceID: "****-db18-4353-95fe-*****", // Replace this with ID of your service instance.
onLoad: function(instance) {
instance.render();
}
};
setTimeout(function(){
const t=document.createElement('script');
t.src="https://web****.global.assistant.watson.appdomain.cloud/*****/" + (window.watsonAssistantChatOptions.clientVersion || 'latest') + "/WatsonAssistantChatEntry.js";
document.head.appendChild(t); // replace the t.src with your code
});
</script>
Now we need to run our application and the Watson Assistant is now shown at the bottom right corner of the screen to answer your queries.
This tutorial serves as a comprehensive guide for data scientists and developers, providing the necessary steps to integrate IBM Watson Assistant seamlessly across different web applications. By leveraging the capabilities of IBM Cloud, users can enhance their web applications with intelligent conversational agents that deliver exceptional user experiences and valuable insights.
As next steps, this project can now be used as a base to build and add more features on top of it to create chatbots for different use cases.
Watson Assistant Documentation:
https://cloud.ibm.com/docs/assistant?topic=assistant-getting-started
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