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Create a Gradio Interface to Interact with AI Models

IntermediateGuided Project

Discover how to create interactive web interfaces using Gradio and Python. This project focuses on setting up user-friendly applications that connect with backend models, such as chatbots or sentiment analysis tools. You’ll learn how to bridge complex algorithms with simple design, enabling real-time feedback and rapid prototyping. By the end, you'll be able to build functional interfaces that make machine learning models accessible and easy to use.

Language

  • English

Topic

  • Artificial Intelligence

Enrollment Count

  • 50

Skills You Will Learn

  • Gradio, Python, Machine Learning, User Interface Design, Artificial Intelligence, Granite

Offered By

  • IBMSkillsNetwork

Estimated Effort

  • 30 minutes

Platform

  • SkillsNetwork

Last Update

  • November 11, 2025
About this Guided Project

In this guided project, you will discover the exciting world of deploying intuitive machine learning interfaces using Gradio and Python. If you've ever wanted to bridge the gap between large language models and user-friendly design, this project is the perfect opportunity. You will learn how to set up interactive web applications for AI models, making advanced algorithms accessible and engaging for users of all skill levels. By the end of this project, you'll have the ability to rapidly prototype and receive real-time feedback, greatly enhancing your model's performance and usability. Whether you're a data scientist, developer, or enthusiast, this project will empower you to transform user interactions with your AI models in just 30 minutes.

Creating an interface is crucial for several reasons:

  • User accessibility: A front-end interface makes it easy for users to interact with the LLM without needing technical expertise.
  • Enhanced user experience: An intuitive interface can provide a better user experience, making interactions smoother and more efficient.
  • Customization: Gradio allows you to customize the interface to meet specific needs, whether for a chatbot, a data analysis tool, or other applications.
  • Seamless integration: Gradio's flexibility enables you to seamlessly integrate the front-end with various backend technologies, including LLMs.


What you'll learn


By the end of this project, you will be able to:

  • Use Gradio to build interactive front-end interfaces, enabling users to interact with backend LLMs seamlessly
  • Create a functional chatbot, allowing users to input queries and receive responses from an LLM, such as IBM's Granite or Mistral AI's Mixtral model
  • Implement essential and commonly used Gradio elements, such as text input fields, buttons, and display areas, to enhance user experience
  • Customize and deploy web-based applications, facilitating various use cases like customer support, data analysis, and more


What you'll need 


Before starting this guided project, you should have:

- Basic knowledge of Python programming.
- Familiarity with machine learning concepts.
- Access to a web browser like Chrome, Edge, Firefox, Internet Explorer, or Safari.
- No need for additional installations as the IBM Skills Network Labs environment includes pre-installed tools like Docker to streamline your setup.

Instructors

Ricky Shi

Data Scientist at IBM

Ricky Shi is a Data Scientist at IBM, specializing in deep learning, computer vision, and Large Language Models. He applies advanced machine learning and generative AI techniques to solve complex challenges across various sectors. As an enthusiastic mentor, Ricky is committed to helping colleagues and peers master technical intricacies and drive innovation.

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Wojciech "Victor" Fulmyk

Data Scientist at IBM

Wojciech "Victor" Fulmyk is a Data Scientist and AI Engineer on IBM’s Skills Network team, where he focuses on helping learners build expertise in data science, artificial intelligence, and machine learning. He is also a Kaggle competition expert, currently ranked in the top 3% globally among competition participants. An economist by training, he applies his knowledge of statistics and econometrics to bring a distinctive perspective to AI and ML—one that considers both technical depth and broader socioeconomic implications.

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Kang Wang

Data Scientist

I was a Data Scientist in the IBM. I also hold a PhD from the University of Waterloo.

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Contributors

Joseph Santarcangelo

Senior Data Scientist at IBM

Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.

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