Create app.py

app.py

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+import torch
+import torchaudio
+from einops import rearrange
+from stable_audio_tools import get_pretrained_model
+from stable_audio_tools.inference.generation import generate_diffusion_cond
+import gradio as gr
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+# تحميل النموذج
+model, model_config = get_pretrained_model("stabilityai/stable-audio-open-small")
+sample_rate = model_config["sample_rate"]
+sample_size = model_config["sample_size"]
+model = model.to(device)
+
+def generate_audio(prompt, duration):
+    conditioning = [{
+        "prompt": prompt,
+        "seconds_total": duration
+    }]
+    output = generate_diffusion_cond(
+        model,
+        steps=8,
+        conditioning=conditioning,
+        sample_size=sample_size,
+        sampler_type="pingpong",
+        device=device
+    )
+    output = rearrange(output, "b d n -> d (b n)")
+    output = output.to(torch.float32).div(torch.max(torch.abs(output))).clamp(-1, 1).mul(32767).to(torch.int16).cpu()
+    torchaudio.save("output.wav", output, sample_rate)
+    return "output.wav"
+
+gr.Interface(
+    fn=generate_audio,
+    inputs=[
+        gr.Textbox(label="Prompt", placeholder="مثال: 128 BPM tech house drum loop"),
+        gr.Slider(1, 11, step=1, label="مدة الصوت بالثواني")
+    ],
+    outputs=gr.Audio(label="الصوت الناتج"),
+    title="تجربة Stable Audio Open Small",
+    description="أدخل وصفًا صوتيًا، وجرب توليد مقطع صوتي من النموذج."
+).launch()