Added code to avoid early termination

app.py

@@ -141,6 +141,28 @@ def compute_audio_features(audio_path: str) -> Dict[str, float]:
         return {}
 
 
+def detect_explicit_suicidality(text: Optional[str]) -> bool:
+    if not text:
+        return False
+    t = text.lower()
+    patterns = [
+        r"\bkill myself\b",
+        r"\bend my life\b",
+        r"\bend it all\b",
+        r"\bcommit suicide\b",
+        r"\bsuicide\b",
+        r"\bself[-\s]?harm\b",
+        r"\bhurt myself\b",
+        r"\bno reason to live\b",
+        r"\bwant to die\b",
+        r"\bending it\b",
+    ]
+    for pat in patterns:
+        if re.search(pat, t):
+            return True
+    return False
+
+
 def synthesize_tts(text: Optional[str]) -> Optional[str]:
     if not text:
         return None
@@ -288,7 +310,15 @@ def scoring_agent_infer(chat_history: List[Tuple[str, str]], features: Dict[str,
         total = int(sum(scores.values()))
         severity = parsed.get("Severity") or severity_from_total(total)
         overall_conf = float(parsed.get("Confidence", min(confidences)))
-        high_risk = bool(parsed.get("High_Risk", False)) or (scores.get("suicidal_thoughts", 0) >= 1)
+        # Conservative high-risk detection: require explicit language or high suicidal_thoughts score
+        # Extract last patient message
+        last_patient = ""
+        for user_text, assistant_text in reversed(chat_history):
+            if user_text:
+                last_patient = user_text
+                break
+        explicit_flag = detect_explicit_suicidality(last_patient) or detect_explicit_suicidality(transcript)
+        high_risk = bool(explicit_flag or (scores.get("suicidal_thoughts", 0) >= 2))
 
         return {
             "PHQ9_Scores": scores,
@@ -409,7 +439,15 @@ def process_turn(
     total = scoring.get("Total_Score", 0)
     severity = scoring.get("Severity", severity_from_total(total))
     overall_conf = float(scoring.get("Confidence", min(confidences) if confidences else 0.0))
-    high_risk = bool(scoring.get("High_Risk", False))
+    # Override high-risk to reduce false positives: rely on explicit text or high item score
+    # Extract last patient message
+    last_patient = ""
+    for user_text, assistant_text in reversed(chat_history):
+        if user_text:
+            last_patient = user_text
+            break
+    explicit_flag = detect_explicit_suicidality(last_patient)
+    high_risk = bool(explicit_flag or (scores.get("suicidal_thoughts", 0) >= 2))
 
     meta = {"Severity": severity, "Total_Score": total, "Confidence": overall_conf}