Update app.py

app.py

@@ -47,21 +47,11 @@ def sequence_to_wav(sequence: np.ndarray, sample_rate=16000) -> str:
 
 
 @app.get("/generate")
-def generate(prompt: str = Query(None), seq_len: int = Query(64)):
-    """
-    Generate a music sequence and return as WAV file.
-    """
+def generate(seq_len: int = 64):
     with torch.no_grad():
-        if prompt:
-            try:
-                input_vec = music_model.text_to_embedding(prompt).to(DEVICE)
-            except AttributeError:
-                # fallback to random vector if text embedding not implemented
-                input_vec = torch.randn(1, music_model.hidden_dim).to(DEVICE)
-        else:
-            input_vec = torch.randn(1, music_model.hidden_dim).to(DEVICE)
-
-        output = music_model.generate(input_vec, seq_len=seq_len).squeeze(0).cpu().numpy()
+        tokens = music_model.generate(seq_len=seq_len, device=DEVICE)
 
-    wav_path = sequence_to_wav(output)
-    return FileResponse(wav_path, media_type="audio/wav", filename="generated_music.wav")
+    return {
+        "seq_len": seq_len,
+        "output": tokens.cpu().tolist()
+    }