Update app.py

app.py

@@ -25,7 +25,15 @@ id2label = {
 def classify_emotion(audio_file):
     # Load and process audio
     speech, sr = librosa.load(audio_file, sr=16000)
-    inputs = processor(speech, sampling_rate=16000, return_tensors="pt", padding=True, truncation=True)
+    inputs = processor(
+        speech,
+        sampling_rate=16000,
+        return_tensors="pt",
+        padding="max_length",
+        truncation=True,
+        max_length=48000  # You can adjust this depending on expected audio length
+        )
+
 
     # Get predictions
     with torch.no_grad():