Update app.py

app.py

@@ -42,11 +42,10 @@ def classify_transaction(text):
     trans_emb = model.encode([text])[0]
     scores = util.pytorch_cos_sim(torch.tensor(trans_emb), torch.tensor(ref_embeddings)).flatten()
     best_idx = scores.argmax().item()
-    return {
-        "Predicted Category 1": ref_data.iloc[best_idx]["Cat1EN"],
-        "Predicted Category 2": ref_data.iloc[best_idx]["Cat2EN"],
-        "Similarity Score": float(scores[best_idx])
-    }
+    cat1 = ref_data.iloc[best_idx]["Cat1EN"]
+    cat2 = ref_data.iloc[best_idx]["Cat2EN"]
+    score = float(scores[best_idx])
+    return cat1, cat2, score
 
 # ==================================================
 # 🖥️ Gradio Interface