From 624b5a150bd831efea5428f891117ddc96843ec1 Mon Sep 17 00:00:00 2001
From: nicoboy <contact@lebel-audio.com>
Date: Mon, 23 Feb 2026 13:27:46 +0000
Subject: [PATCH] Actualiser server.py(gradio)

---
 server.py(gradio) | 110 ++++++++++++++++++++++++++++------------------
 1 file changed, 67 insertions(+), 43 deletions(-)

diff --git a/server.py(gradio) b/server.py(gradio)
index f706d28..0541691 100644
--- a/server.py(gradio)
+++ b/server.py(gradio)
@@ -1,43 +1,67 @@
-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)
\ No newline at end of file
+import gradio as gr
+import torch
+import scipy.io.wavfile
+import numpy as np
+import tempfile
+import os
+from audiocraft.models import MusicGen, AudioGen
+
+# Force l'utilisation du GPU si disponible
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+print(f"🔄 Chargement des modèles sur {device}...")
+try:
+    # On utilise 'small' pour la musique et 'medium' pour l'audio pour un bon ratio vitesse/qualité
+    music_model = MusicGen.get_pretrained("facebook/musicgen-small")
+    audio_model = AudioGen.get_pretrained("facebook/audiogen-medium")
+except Exception as e:
+    print(f"❌ Erreur lors du chargement des modèles : {e}")
+
+def generate_music(prompt, duration=10):
+    if not prompt: return None
+    music_model.set_generation_params(duration=duration)
+    wav = music_model.generate([prompt])
+    wav_np = wav[0, 0].cpu().numpy()
+    
+    path = os.path.join(tempfile.gettempdir(), "music_out.wav")
+    scipy.io.wavfile.write(path, music_model.sample_rate, (wav_np * 32767).astype(np.int16))
+    return path
+
+def generate_sound(prompt, duration=5):
+    if not prompt: return None
+    audio_model.set_generation_params(duration=duration)
+    wav = audio_model.generate([prompt])
+    wav_np = wav[0, 0].cpu().numpy()
+    
+    path = os.path.join(tempfile.gettempdir(), "sound_out.wav")
+    scipy.io.wavfile.write(path, audio_model.sample_rate, (wav_np * 32767).astype(np.int16))
+    return path
+
+# Interface UI
+with gr.Blocks(title="🎙️ Studio Audio IA", theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# 🎙️ Studio Audio IA")
+    gr.Markdown("Générez de la musique et des effets sonores avec les modèles de Facebook Research.")
+    
+    with gr.Tab("🎵 Musique (MusicGen)"):
+        with gr.Row():
+            with gr.Column():
+                p1 = gr.Textbox(label="Description de la musique", placeholder="Ex: Epic cinematic orchestral music, high strings...")
+                d1 = gr.Slider(minimum=1, maximum=30, value=10, step=1, label="Durée (secondes)")
+                b1 = gr.Button("Générer la musique", variant="primary")
+            with gr.Column():
+                o1 = gr.Audio(label="Résultat Audio", type="filepath")
+        b1.click(generate_music, inputs=[p1, d1], outputs=o1)
+
+    with gr.Tab("🔊 Bruitages (AudioGen)"):
+        with gr.Row():
+            with gr.Column():
+                p2 = gr.Textbox(label="Effet sonore", placeholder="Ex: Dogs barking, car engine revving, rain on window...")
+                d2 = gr.Slider(minimum=1, maximum=15, value=5, step=1, label="Durée (secondes)")
+                b2 = gr.Button("Générer le son", variant="primary")
+            with gr.Column():
+                o2 = gr.Audio(label="Résultat Audio", type="filepath")
+        b2.click(generate_sound, inputs=[p2, d2], outputs=o2)
+
+# Important : server_name="0.0.0.0" permet l'accès externe depuis Vast.ai
+if __name__ == "__main__":
+    demo.launch(server_name="0.0.0.0", server_port=7860, share=False)
\ No newline at end of file