Build Anything with gr.Workflow
Blog post from Hugging Face
Gradio’s new gr.Workflow feature turns AI application pipelines into visual, typed node graphs that serve as interactive drag-and-drop interfaces, REST APIs, and deployable Hugging Face Spaces. Workflows consist of input references, operator nodes, and output subjects, with operators able to run custom Python functions, Hugging Face Inference Provider models, other Gradio Spaces, Hub dataset queries, or GPU-hosted models through ZeroGPU. Demonstrations include image editing, a media studio combining image generation, background removal, text-to-speech, and LLM title generation, parallel generative art, live dataset profiling, and image animation using a locally run video model. Each output can be accessed independently through automatically created REST endpoints using the Gradio client or HTTP, while users can begin by duplicating examples or launching a workflow from a short Python definition.
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