import gradio as gr from gradio_huggingfacehub_search import HuggingfaceHubSearch example = HuggingfaceHubSearch().example_value() def predict(hub_repo_id): print("hub_repo_id", hub_repo_id) return hub_repo_id with gr.Blocks() as demo: with gr.Row(): with gr.Column(): search_in = HuggingfaceHubSearch( label="Search Huggingface Hub", search_type=["model", "dataset"], ) btn = gr.Button("Run") with gr.Column(): search_out = HuggingfaceHubSearch(label="Search Huggingface Hub") gr.on( [btn.click, search_in.submit], fn=predict, inputs=[search_in], outputs=[search_out], ) if __name__ == "__main__": demo.launch()