Update handler.py

handler.py

@@ -161,25 +161,24 @@ class EndpointHandler:
                         "RECCON raw spans (answer, score): %s",
                         [(p.get("answer"), p.get("score", 0.0), 3) for p in current_preds[:5]]
                     )
-
-                    best_score = max((p.get("score", 0.0) for p in current_preds), default=0.0)
-
-                    MIN_BEST_SCORE = 0.01  # start here; tune later
-                    if best_score < MIN_BEST_SCORE:
-                        results.append({
-                            "utterance": utterance,
-                            "emotion": emotion,
-                            "triggers": [],  # no highlight
-                            "metadata": {"low_confidence": True, "best_score": best_score}
-                        })
-                        pred_idx += 1
-                        continue
                     
-                    # Extract the answer strings
-                    raw_answers = [p.get('answer', '') for p in current_preds]
+                    def is_good_span(ans: str) -> bool:
+                        if not ans:
+                            return False
+                        a = ans.strip()
+                        if len(a) < 3:
+                            return False
+                        # reject pure punctuation
+                        if all(ch in ".,!?;:-—'\"()[]{}" for ch in a):
+                            return False
+                        # require at least one letter
+                        if not any(ch.isalpha() for ch in a):
+                            return False
+                        return True
                     
-                    # Clean spans using your original logic
-                    triggers = self._clean_spans(raw_answers, utterance) 
+                    raw_answers = [p.get("answer", "") for p in current_preds]
+                    raw_answers = [a for a in raw_answers if is_good_span(a)]
+                    triggers = self._clean_spans(raw_answers, utterance)
 
                     results.append({
                         "utterance": utterance,