Gradio Auto‑Creates Text Input, Submit Button, and Output from Spec

The interface provides a text input, a submit button, and a text output -- all automatically generated from your simple specification. It requires three essential components: - Function ( fn ): Your Python function that processes inputs - Inputs: Specification of input type(s) - Outputs: Specification of output type(s) // Exploring Input and Output Components While you can use simple strings like "text" , "image" , or "audio" to specify components, Gradio offers more control through explicit component classes. import gradio as gr demo = gr.Interface( fn=lambda x: x, inputs=gr.Textbox(lines=2, placeholder="Enter text here..."), outputs=gr.Textbox(label="Output") ) Common components include: gr.Textbox() : Multi-line text inputgr.Image() : Image upload/previewgr.Audio() : Audio file handlinggr.Checkbox() : Boolean inputgr.Slider() : Numerical range inputgr.Radio() : Multiple choice selectiongr.Dropdown() : Select from options // Handling Multiple Inputs and Outputs Real-world applications often require multiple inputs or produce multiple outputs.

import gradio as gr def process_form(name, is_morning, temperature): greeting = "Good morning" if is_morning else "Hello" message = f"{greeting}, {name}! Similarly, multiple outputs require your function to return multiple values. // Handling Audio Processing Audio applications are just as straightforward: import gradio as gr def transcribe_audio(audio): return "Transcribed text would appear here" demo = gr.Interface( fn=transcribe_audio, inputs=gr.Audio(label="Upload Audio", type="filepath"), outputs=gr.Textbox(label="Transcription"), title="Speech-to-Text Demo" ) demo.launch() In a real application, you would call a speech recognition model inside the transcribe_audio(audio) function.

Think of Blocks as the low-level API that lets you build complex, multi-step applications. Ensure that the Transformers package is installed on your computer. Gradio provides two approaches: global state and session state.

// Managing Session State (User-Specific) For user-specific state, use Gradio's built-in state management. The following example demonstrates a simple chatbot logic using state to maintain conversation history.