Gradio makes the pipeline the interface

Gradio introduced gr.Workflow for describing AI pipelines as graphs of typed nodes. The same structure becomes an interactive canvas, with runnable stages and visible intermediate outputs, as well as an API and a route to deployment on Hugging Face Spaces.

Context

Seeing intermediate results makes failures easier to locate. A poor final output may originate in transcription, image generation, or a transformation between them. A visible workflow helps separate those causes. The graph still needs clear input contracts and error handling to remain dependable beyond a demonstration.