app.py

import torchaudio
from audiocraft.models import AudioGen
from audiocraft.data.audio import audio_write
import gradio as gr

model = AudioGen.get_pretrained('facebook/audiogen-medium')
model.set_generation_params(duration=8)  # generate 8 seconds.
wav = model.generate_unconditional(1)    # generates 4 unconditional audio samples

def AudioGenie(Prompt):
    descriptions = [Prompt]
    wav = model.generate(descriptions)  # generates 3 samples.
    for idx, one_wav in enumerate(wav):
    # Will save under {idx}.wav, with loudness normalization at -14 db LUFS.
        audio_write(f'{idx}', one_wav.cpu(), model.sample_rate, strategy="loudness", loudness_compressor=True)
    return wav

gr.Interface(fn=AudioGenie, inputs= 'text', outputs= 'audio').launch(debug=True)