app.py

import gradio as gr
from audiosr import super_resolution, build_model
import spaces


audiosr = build_model(model_name='basic')
audiosr_speech = build_model(model_name='speech')

models = {
    'basic': audiosr,
    'speech': audiosr_speech
}

@spaces.GPU
def inference(audio_file, model_name, guidance_scale, ddim_steps):
    audiosr = models[model_name]
    
    waveform = super_resolution(
        audiosr,
        audio_file,
        guidance_scale=guidance_scale,
        ddim_steps=ddim_steps
    )
    
    return (44100, waveform)

iface = gr.Interface(
    fn=inference, 
    inputs=[
        gr.Audio(type="filepath", label="Input Audio"),
        gr.Dropdown(["basic", "speech"], value="basic", label="Model"),
        gr.Slider(1, 10, value=3.5, step=0.1, label="Guidance Scale"),  
        gr.Slider(1, 100, value=50, step=1, label="DDIM Steps")
    ],
    outputs=gr.Audio(type="numpy", label="Output Audio"),
    title="AudioSR",
    description="Audio Super Resolution with AudioSR"
)

iface.launch()