Update app.py

app.py

@@ -19,13 +19,9 @@ def generate_music(prompt, duration):
     # Prepare inputs
     inputs = processor(text=[prompt], return_tensors="pt").to(device)
 
-    # Scale tokens with duration (MusicGen ≈ 256 tokens ≈ 8 seconds)
-    max_new_tokens = int(256 * (duration / 8))
-    max_new_tokens = min(max_new_tokens, 2048)  # Safety cap
-
-    # Generate audio
+    # ✅ Use exact audio length parameter instead of token approximation
     with torch.no_grad():
-        audio = model.generate(**inputs, max_new_tokens=max_new_tokens)
+        audio = model.generate(**inputs, do_sample=True, guidance_scale=3, audio_length_in_s=int(duration))
 
     sr = model.config.audio_encoder.sampling_rate
     audio_arr = audio[0, 0].cpu().numpy()
@@ -37,7 +33,7 @@ def generate_music(prompt, duration):
     return tmp.name, f"✅ Generated {duration}s of audio!"
 
 with gr.Blocks(title="MusicGen 🎶") as demo:
-    gr.Markdown("# 🎵 MusicGen — Text-to-Music Generator (Extended 40 s Version)")
+    gr.Markdown("# 🎵 MusicGen — Text-to-Music Generator (Accurate Duration 40s Version)")
     with gr.Row():
         prompt = gr.Textbox(label="🎼 Describe your music", placeholder="e.g. dreamy lo-fi with soft piano")
         duration = gr.Slider(4, 40, value=15, step=1, label="Duration (seconds)")
@@ -46,4 +42,4 @@ with gr.Blocks(title="MusicGen 🎶") as demo:
     msg = gr.Textbox(label="Status", interactive=False)
     btn.click(generate_music, inputs=[prompt, duration], outputs=[audio_out, msg])
 
-demo.launch(share=True)
+demo.launch(share=True)