app.py

import gradio as gr
import torch
from diffusers import DiffusionPipeline

# Cargar el modelo preentrenado de Hugging Face
model = DiffusionPipeline.from_pretrained("harmonai/ddpm-256")
model.to("cuda" if torch.cuda.is_available() else "cpu")

def generate_beat(prompt):
    audio = model(prompt, num_inference_steps=50)
    audio_path = "generated_beat.wav"
    audio.save(audio_path)
    return audio_path

# Crear interfaz de usuario con Gradio
iface = gr.Interface(fn=generate_beat, inputs="text", outputs="audio")
iface.launch()