Create app.py

app.py

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+import gradio as gr
+import random
+import torch
+from audiocraft.models import MusicGen
+from audiocraft.data.audio import audio_write
+import spaces
+
+model = MusicGen.get_pretrained("small")
+
+@spaces.GPU()
+def infer(duration, descriptions):
+    if len(descriptions) > 8192:
+        return "Error: La descripción no puede exceder los 8192 caracteres."
+
+    seed = random.randint(0, 10000)
+    torch.manual_seed(seed)
+
+    model.set_generation_params(duration=duration, temperature=0.5)
+    wav = model.generate(descriptions.split(", "))
+    output_files = []
+
+    for idx, one_wav in enumerate(wav):
+        file_name = f'output_{idx}.wav'
+        audio_write(file_name, one_wav.cpu(), model.sample_rate, strategy="loudness")
+        output_files.append(file_name)
+
+    return output_files[0]
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Generador de Música con MusicGen")
+    duration_input = gr.Slider(minimum=1, maximum=600, label="Duración de la canción (segundos)", value=8)
+    description_input = gr.Textbox(placeholder="Ejemplo: happy rock, energetic EDM", label="Descripción de la música")
+    generate_button = gr.Button("Generar Música")
+    output_audio = gr.Audio(label="Escuchar Música", type="filepath")
+
+    generate_button.click(
+        fn=infer,
+        inputs=[duration_input, description_input],
+        outputs=output_audio
+    )
+
+demo.launch()