Gradio Applications

What is Gradio

Gradio is an open-source Python library for quickly building interactive demo interfaces for machine learning models. With just a few lines of code, you can create a web application with input and output components for model testing and demonstration.

Create a Gradio Space

1. Follow the steps in Create Space to open the creation form.
2. Select Gradio as the SDK Type.
3. If you selected a GPU compute resource, also choose a Driver Version (11.8.0 or 12.1.0).
4. Fill in the remaining parameters and click Create Application Space to submit.

Initialize the Application

After creation, push application code to the repository to initialize the Gradio space.

Step 1: Clone the Repository

git clone https://<platform-host>/<namespace>/<space-name>
cd <space-name>

Step 2: Create the Dependencies File

Create a requirements.txt file specifying the Gradio version and other dependencies:

gradio==4.44.1

Step 3: Create the Application File

Create an app.py file with your Gradio application code. Here is a simple text greeting example:

import gradio as gr

def greet(name):
    return f"Hello, {name}! Welcome to the AI platform."

demo = gr.Interface(
    fn=greet,
    inputs=gr.Textbox(label="Your Name", placeholder="Enter your name..."),
    outputs=gr.Textbox(label="Greeting"),
    title="Hello World Demo",
    description="A simple Gradio application deployed on the platform."
)

demo.launch()

Step 4: Push the Code

git add requirements.txt app.py
git commit -m "Initialize Gradio application"
git push origin main

Automatic Build and Deployment

After the code is pushed, the platform automatically triggers the build and deployment process:

1. Installs dependencies from requirements.txt.
2. Starts the app.py application.
3. Once the build is complete, the space page displays the Gradio interface.

You can view build logs and running status on the space detail page.

Related Documentation

• Create Space
• Streamlit Applications
• Docker Applications