Update app.py

app.py

@@ -44,16 +44,24 @@ def predict(text):
         encoded = tokenizer(text, return_tensors="pt", truncation=True, padding=True, max_length=64)
         out_sent, out_event, out_idx = model(encoded["input_ids"], encoded["attention_mask"])
 
+        # Sentiment
         sent_label = torch.argmax(out_sent, dim=1).item()
         sent_result = sentiment_map[sent_label]
 
+        # Event
         event_label = torch.argmax(out_event, dim=1).item()
         event_result = event_map.get(event_label, "unknown")
 
+        # IDX (multi-label + bullish/bearish status)
         idx_probs = torch.sigmoid(out_idx).squeeze(0)
-        idx_result = [label for i, label in enumerate(idx_labels) if idx_probs[i] > 0.5]
+        idx_result = []
+
+        for i, prob in enumerate(idx_probs):
+            status = "Bullish" if prob.item() > 0.5 else "Bearish"
+            idx_result.append(f"{idx_labels[i]}: {status} ({prob.item():.2f})")
+
+    return sent_result, event_result, "\n".join(idx_result)
 
-    return sent_result, event_result, ", ".join(idx_result)
 
 iface = gr.Interface(
     fn=predict,