refactor app.py

app.py

@@ -16,12 +16,17 @@ model.load_state_dict(torch.load(os.path.join(MODEL_DIR, "regressor_model.pt"),
 model.eval()
 
 def predict_sentiment(text):
+    print(f"[DEBUG] Input text: {text}")
     processed = preprocess_texts([text])[0]
+    print(f"[DEBUG] Processed text: {processed}")
+
     inputs = tokenizer(processed, return_tensors="pt", truncation=True, padding='max_length', max_length=128)
     inputs = {k: v.to(DEVICE) for k, v in inputs.items() if k != "token_type_ids"}
     with torch.no_grad():
         score = model(**inputs)["score"].item()
 
+    print(f"[DEBUG] Score: {score}")
+
     if score > 0.3:
         interpretation = "positive"
     elif score < -0.3: