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Create app.py
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app.py
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import gradio as gr
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lpmc_client = gr.load("seungheondoh/LP-Music-Caps-demo", src="spaces")
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from gradio_client import Client
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client = Client("https://ysharma-explore-llamav2-with-tgi.hf.space/")
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def infer(audio_file):
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cap_result = lpmc_client(
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audio_file, # str (filepath or URL to file) in 'audio_path' Audio component
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api_name="predict"
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)
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print(cap_result)
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result = client.predict(
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cap_result, # str in 'Message' Textbox component
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api_name="chat"
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)
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print(result)
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return cap_result, result
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with gr.Blocks() as demo:
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with gr.Column(elem_id="col-container"):
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audio_input = gr.Audio(type="filepath", source="upload")
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infer_btn = gr.Button("Generate")
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lpmc_cap = gr.Textbox(label="Lp Music Caps caption")
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llama_trans_cap = gr.Textbox(label="Llama translation")
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img_result = gr.Video(label="Result")
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infer_btn.click(fn=infer, inputs=[audio_input], outputs=[lpmc_cap, llama_trans_cap])
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demo.queue().launch()
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