Sttabot Documentation
  • SDK & API Official Documentation
  • Understanding The SDK
    • Introduction of Sttabot
    • History and Background
    • The Problem
    • Basis of this Research
    • The Solution
    • An Introduction to the Sttabot SDK
  • Platform Architecture
    • The Sttabot API and its Importance
    • The SDK Architecture
    • Integrating the Application - Frontend vs Backend
    • Headless Architecture
    • Scope of Scalability
  • How To?
    • How to Configure the Sttabot API?
Powered by GitBook
On this page
  1. Platform Architecture

Integrating the Application - Frontend vs Backend

Your AI applications are pre-configured using the Sttabot API. This means that in order to go live, you do not need to do any other configuration to the code. Hence, whether frontend or backend, you can simply add your AI app’s source code and push the publish button to go live.

Example :

For frontend, let’s think about integrating your AI app to your WordPress blog or Medium article. For this, you will just need to copy your code, go to the article editor, add a custom HTML element and paste the code there. Once you publish the blog/article, your users will be able to use your AI instantly.

Now for the backend, suppose you are adding your AI to your e-commerce platform. You just need to locate where you want to add the AI, go to the SDK where you developed your AI, click on get separate files and get your frontend, backend, scripting and javascript codes which you can place directly into your source code there and save the code. That’s all you need to integrate it to your core app.

Note : The single source code generated at first is just for testing and the API details are easily visible through developer tools. We recommend adding separate files while you integrate your AI app into your core application.

This will help you create a proxy for the API data and protect sensitive API details.

PreviousThe SDK ArchitectureNextHeadless Architecture

Last updated 1 year ago