Crafting the User Interface with Gradio

With the research server integrated, the project is complete. It demonstrates an architectural pattern for building modular agentic systems. Multimodal capabilities do not need to reside in a single model or service; they can be composed from specialized, reusable components. This decoupled architecture, coordinated through MCP, can support agentic systems that are easier to extend and maintain.

From CLI to a user-friendly UI

In this final implementation lesson, we will add a web interface to the agent. We will move the agent from a terminal interface to a web-based graphical user interface using Gradio. Our goal is to create an interactive application that lets users upload an image, ask a question, and view the agent’s response through a chat-based interface. To build the interface without creating the web layer from scratch, we will use Gradio, a Python library for building interactive web interfaces.

What is Gradio?

Gradio is an open-source Python library that lets developers build and share interactive interfaces for machine learning models, APIs, and Python functions. It provides customizable UI components with relatively little setup, which can simplify the process of turning Python code into an interactive web application.

For our project, Gradio is the perfect choice for several reasons. It is designed with AI workflows in mind, offering pre-built components like image upload widgets and chatbot displays that perfectly match our needs. This allows us to focus entirely on orchestrating our agent’s logic, while Gradio handles all the front-end complexity. As it’s a pure Python library, it integrates seamlessly into our existing client script.

How to install Gradio

Getting started with Gradio is ...