normalize major topic predictions

interfaces/cap_minor_media.py

@@ -98,9 +98,10 @@ def predict(text, major_model_id, minor_model_id, tokenizer_id, HF_TOKEN=None):
     top_major_id = major_index_to_id[top_major_index]
 
     # Default: show major topic predictions
+    filtered_probs = normalize_probs(np.argsort(major_probs_np)[::-1])
     output_pred = {
-        f"[{major_index_to_id[i]}] {CAP_MEDIA_LABEL_NAMES[major_index_to_id[i]]}": float(major_probs_np[i])
-        for i in np.argsort(major_probs_np)[::-1]
+        f"[{major_index_to_id[k]}] {CAP_MEDIA_LABEL_NAMES[filtered_probs[k]]}": v
+        for k, v in sorted(filtered_probs.items(), key=lambda item: item[1], reverse=True)
     }
 
     # If eligible for minor prediction