Upload app.py

app.py

@@ -62,11 +62,22 @@ def extract_feature(audio_path):
 
 # Full pipeline: emotion detection + GPT response
 def predict_and_reply(audio_path):
+    model.eval()
+
+    # Load and preprocess audio
     feature = extract_feature(audio_path)
+
+    # Move model and input to correct device
+    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+    model.to(device)
+    feature = feature.to(device)
+
+    # Predict
     with torch.no_grad():
         output = model(feature)
         pred = torch.argmax(output, dim=1).item()
         emotion = emotions[pred]
+        
 
     prompt = f"The user sounds {emotion.lower()}. What would you like to say to them?"