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


iface = gr.Interface(fn=audioGen, inputs="text", outputs="text")
iface.launch()

def audioGen(audioPrompt):
    model = AudioGen.get_pretrained('facebook/audiogen-medium')
    model.set_generation_params(duration=5)  # generate 8 seconds.
    wav = model.generate_unconditional(4)    # generates 4 unconditional audio samples
    descriptions = ['dog barking', 'sirenes of an emergency vehicule', 'footsteps in a corridor']
    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 "Hello " + audioPrompt + "!!"