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

def generate_music(description, melody_audio):
    model = MusicGen.get_pretrained('nateraw/musicgen-songstarter-v0.2')
    model.set_generation_params(duration=8)  # generate 8 seconds.

    if description:
        descriptions = [description] * 3
        if melody_audio:
            melody, sr = torchaudio.load(melody_audio)
            wav = model.generate_with_chroma(descriptions, melody[None].expand(3, -1, -1), sr)
        else:
            wav = model.generate(descriptions)  # generates 3 samples.
    else:
        wav = model.generate_unconditional(4)    # generates 4 unconditional audio samples

    output_audios = []
    for idx, one_wav in enumerate(wav):
        output_path = f'output_{idx}.wav'
        audio_write(output_path, one_wav.cpu(), model.sample_rate, strategy="loudness", loudness_compression=-14)
        output_audios.append(output_path)

    return output_audios

description = gr.Textbox(label="Description", placeholder="acoustic, guitar, melody, trap, d minor, 90 bpm")
melody_audio = gr.Audio(label="Melody Audio (optional)", type="filepath")
output_audio = gr.Audio(label="Generated Music", type="filepath")

gr.Interface(
    fn=generate_music,
    inputs=[description, melody_audio],
    outputs=output_audio,
    title="MusicGen Demo",
    description="Generate music using the MusicGen model.",
    examples=[
        ["trap, synthesizer, songstarters, dark, G# minor, 140 bpm", "./assets/kalhonaho.mp3"],
        ["upbeat, electronic, synth, dance, 120 bpm", None]
    ]
).launch()