Using Gradio and Gradio Lite

Gradio and Gradio Lite make it easy to turn Python functions into interactive dashboards—even if you don’t have web development experience. These tools are especially powerful when paired with large language models (LLMs) that help generate UI code based on your descriptions.

Gradio is Python-based and works well inside Jupyter or Google Colab. You can wrap any function with input and output components and instantly see it as a working web interface.
Gradio Lite runs entirely in the browser using static HTML and JavaScript. You write Python code that gets converted into a portable .html file—ideal for embedding or sharing.

You can create powerful dashboards with filters, charts, and file upload options, just by describing what you want in natural language.

🎨 Prompting Techniques for Dashboard Interfaces

AI prompting can speed up dashboard development by letting you describe UI components and get working code in return. You don’t need to memorize every function—just know how to describe the interface.

Here are some techniques and tips for prompting:

✅ Describe the Full User Interface (UI) Flow

Instead of saying “make a dashboard,” be specific. For example:

“Create a Gradio dashboard where users upload a CSV, select a numeric column from a dropdown, and view a histogram. Add a slider to filter by date range.”

✅ Use Known Component Names

Refer to components by their names in the Gradio Components Library. Common ones include:

gr.File() – for file uploads
gr.Dropdown() – for selecting a column or option
gr.Slider() – for numeric filters
gr.Plot() – for charts (can output matplotlib, plotly, or altair visuals)
gr.Image() – for image inputs or outputs

The more clearly you specify component names, the better the results.

✅ Use Visual Prompting

If you’re struggling to describe the UI layout or expected interactions:

Draw it using a simple wireframe or screenshot
Upload it to your LLM/chatbot
Prompt: “Convert the attached UI design into a working Gradio interface.”

This technique is particularly useful when you’re designing dashboards with multiple tabs, filters, or layout regions.

✅ Be Iterative

Don’t expect to get everything right in the first try. A good workflow is:

Prompt the dashboard code.
Run it inside a Jupyter or Colab notebook.
Interact with the UI and note what’s missing.
Provide feedback to the AI:

“Update the dropdown to list only columns with numeric data”
“Add a date slider on the left side”
“Use Plotly instead of matplotlib for better interactivity”

Repeat this loop to gradually refine your dashboard.

🧪 Exercise 1 – Build an Interactive Scatter Plot Tool (Gradio)

In this task, you’ll write a prompt to an LLM chatbot (e.g., ChatGPT, Claude, or Gemini) to generate Python code for an interactive scatter plot tool using Gradio.

The interface should:

Allow the user to upload a CSV file.
Let the user select any two columns for the X and Y axes from dropdown menus.
Display an interactive scatter plot based on the selected columns.

✅ Instructions

Write a prompt like the one below:

“Write Python code using Gradio to build an interactive tool that lets the user upload a CSV, choose two numeric columns for the X and Y axes, and view a scatter plot.”
Try the generated code in one of the following:
- Jupyter Notebook
- Google Colab
- The online Gradio Playground: https://www.gradio.app/playground
In the Playground, you can also use the built-in LLM assistant to refine the interface. Ask for:
- Filtering numeric columns only
- Adding color options
- Using Plotly instead of Matplotlib

Tip

💡 Tip: Always test the UI and provide feedback iteratively. The Playground supports real-time editing and re-running.

Warning

💡 Tip: The Gradio chatbot is not as capable as OpenAI ChatGPT or Google Gemini at debugging errors. If you encounter an error that it can’t fix, then please use OpenAI ChatGPT or Google Gemini.

🧪 Exercise 2 – Build the Same Tool Using Gradio Lite

Now, let’s build the same interactive scatter plot using Gradio Lite, but with an added feature:

Overlay a regression line on the scatter plot.

Gradio Lite lets you write Python logic that compiles to a static, embeddable HTML page—perfect for lightweight deployment.

✅ Prompt Example

Write a prompt like:

“Write Gradio Lite code that allows the user to upload a CSV, choose numeric columns for X and Y, and display a scatter plot with a regression line. Use the required Gradio Lite HTML template and embed the Python code inside the <gradio-lite> block. The plot should be generated using matplotlib.”

📋 Required HTML Template

Ensure your code is embedded inside the following structure:

<html>
    <head>
        <script type="module" crossorigin src="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.js"></script>
        <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.css" />
    </head>
    <body>
        <gradio-lite>
            <!-- Python code will go here -->
            # remember to include .launch() eg demo.launch()
        </gradio-lite>
    </body>
</html>

✅ Test It Locally

Copy the entire generated HTML (including the template).
Paste it into a text editor (like VS Code or Spyder) and save it as scatter_regression.html.
Open the file in your browser to test and validate the dashboard.
Reopen the HTML file in your editor to refine and improve as needed.

Note

📚 Refer to the official Gradio Lite documentation for more examples and components:
👉 https://www.gradio.app/guides/gradio-lite

Tip

💡 Tip: As Gradio Lite loads everything in the Web Browser, it can take a few seconds to load.