Wire It, Run It, Deploy It: AI Workflows in Gradio

Gradio's gr.Workflow turns a multistep AI pipeline into an interface where developers can run individual steps and inspect intermediate results. Inputs, processing steps and outputs appear as connected nodes, making it easier to locate the step that produced an unexpected value.

The same workflow also exposes each output through a named REST endpoint, so another application can request a result without opening the visual canvas. Processing steps can include custom Python functions or calls to hosted models and applications. The useful connection is that the inspectable workflow and its callable API come from the same graph.