Gradio is an open-source Python library that enables quick building and sharing of interactive machine learning web apps without requiring web development skills.
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Gradio is primarily used by machine learning practitioners and developers to create interactive demos or web applications for their models, APIs, or Python functions. It allows users to easily showcase and share their AI models with others via simple Python code and built-in sharing features, making model testing and collaboration seamless.
Gradio requires Python 3.10 or higher and is best installed in a virtual environment to avoid dependency conflicts. It abstracts away frontend development, making it ideal for rapid prototyping and sharing of ML models but may not be suitable for complex production-grade web applications without additional customization.
Ensure Python 3.10 or higher is installed
Use pip to install or upgrade Gradio: pip install --upgrade gradio
It is recommended to install Gradio within a virtual environment
Refer to official guides for virtual environment setup on different OSpip install --upgrade gradio
Installs or upgrades the Gradio package using pip
import gradio as gr
Imports the Gradio library with the alias 'gr' for easier usage
demo = gr.Interface(fn=greet, inputs=["text", "slider"], outputs=["text"])
Creates a Gradio interface wrapping the 'greet' function with specified input and output components
demo.launch()
Launches the Gradio app locally, opening a browser window to interact with the demo
python app.py
Runs the Python script containing the Gradio app to start the demo server