import gradio as gr
import torch
import scipy.io.wavfile
import numpy as np
import tempfile
from audiocraft.models import MusicGen, AudioGen

print("🔄 Chargement des modèles...")
music_model = MusicGen.get_pretrained("facebook/musicgen-small")
audio_model = AudioGen.get_pretrained("facebook/audiogen-medium")

def generate_music(prompt, duration=10):
    music_model.set_generation_params(duration=duration)
    wav = music_model.generate([prompt])
    wav_np = wav[0, 0].cpu().numpy()
    with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as f:
        scipy.io.wavfile.write(f.name, music_model.sample_rate, (wav_np * 32767).astype(np.int16))
        return f.name

def generate_sound(prompt, duration=5):
    audio_model.set_generation_params(duration=duration)
    wav = audio_model.generate([prompt])
    wav_np = wav[0, 0].cpu().numpy()
    with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as f:
        scipy.io.wavfile.write(f.name, audio_model.sample_rate, (wav_np * 32767).astype(np.int16))
        return f.name

with gr.Blocks(title="🎙️ Studio Audio IA") as demo:
    gr.Markdown("## 🎙️ Studio Audio IA")
    with gr.Tab("🎵 Musique"):
        p1 = gr.Textbox(label="Prompt")
        d1 = gr.Slider(5, 30, value=10, step=5, label="Durée (s)")
        b1 = gr.Button("Générer")
        o1 = gr.Audio(label="Résultat")
        b1.click(generate_music, inputs=[p1, d1], outputs=o1)
    with gr.Tab("🔊 Bruitages"):
        p2 = gr.Textbox(label="Prompt")
        d2 = gr.Slider(2, 15, value=5, label="Durée (s)")
        b2 = gr.Button("Générer")
        o2 = gr.Audio(label="Résultat")
        b2.click(generate_sound, inputs=[p2, d2], outputs=o2)

demo.launch(server_name="0.0.0.0", server_port=7860, share=False)