Add read-only production runtime audit

apps/ai-service/rag/understanding.py

@@ -593,6 +593,7 @@ class LlmQueryUnderstander:
         frame = _apply_broad_condition_cue(
             frame, turn, self._condition_normalizer
         )
+        frame = _apply_general_condition_scope(frame, turn)
         frame = _apply_reverse_relation_cues(frame, turn)
         section_match = _SECTION_RESOLVER.resolve(turn)
         frame = _apply_named_drug_cues(
@@ -603,7 +604,8 @@ class LlmQueryUnderstander:
             resolved_section_phrase=(section_match.phrase if section_match else None),
         )
         frame = _apply_multi_section_clarify(frame, turn)
-        return _merge_with_prior_frame(frame, prior_frame)
+        frame = _merge_with_prior_frame(frame, prior_frame)
+        return _apply_contextual_candidate_safety(frame, turn, prior_frame)
 
     @staticmethod
     def _resolve_id(value: str, shown: dict[str, str]) -> str | None:
@@ -754,7 +756,7 @@ def _apply_condition_candidate_cue(
     """Keep current medicines subordinate in an explicit condition lookup."""
     if frame.turn_type == "condition_to_drug" and frame.condition is not None:
         return frame
-    condition = normalizer.detect_known_alias(turn)
+    condition = frame.condition or normalizer.detect_known_alias(turn)
     if condition is None:
         return frame
     text = f" {normalize_name(turn)} "
@@ -767,6 +769,8 @@ def _apply_condition_candidate_cue(
         " option dieu tri ",
         " ung vien nao ",
         " cac ung vien nao ",
+        " co chi dinh lien quan ",
+        " co chi dinh cho ",
     )
     if not any(cue in text for cue in candidate_cues):
         return frame
@@ -782,6 +786,80 @@ def _apply_condition_candidate_cue(
     )
 
 
+def _apply_general_condition_scope(frame: QueryFrame, turn: str) -> QueryFrame:
+    """Do not turn a disease name into an unstated patient impairment.
+
+    A general reverse lookup such as ``Viêm gan B mạn dùng thuốc gì?`` names
+    the condition being treated; it does not say that a particular patient has
+    hepatic impairment.  The understanding model can otherwise duplicate the
+    same phrase into ``patient_context.hepatic`` and trigger a stage-2 safety
+    review, mixing contraindication/precaution citations into a general
+    indication list.  Explicit patient cues keep the full context untouched.
+    """
+    if frame.turn_type not in {"condition_to_drug", "symptom_to_drug"}:
+        return frame
+    text = f" {normalize_name(turn)} "
+    patient_cues = (
+        " bn ", " benh nhan ", " nguoi benh ", " kem ", " di ung ",
+        " dang dung ", " mang thai ", " cho con bu ", " tuoi ", " kg ",
+        " ckd ", " suy than ", " suy gan ", " child pugh ", " egfr ",
+        " creatinin ", " ast ", " alt ",
+    )
+    if any(cue in text for cue in patient_cues):
+        return frame
+    primary = (
+        frame.condition.normalized_condition
+        if frame.condition is not None
+        else frame.indication
+    )
+    return replace(frame, patient_context=PatientContext(primary_condition=primary))
+
+
+def _apply_contextual_candidate_safety(
+    frame: QueryFrame,
+    turn: str,
+    prior_frame: QueryFrame | None,
+) -> QueryFrame:
+    """Keep ``các thuốc trên`` on the prior condition-to-drug candidate lane.
+
+    This follow-up asks to compare the already retrieved candidates against a
+    new patient constraint.  It is not a reverse disease->contraindication
+    lookup, even if the current turn contains words such as ``bệnh thận``.
+    """
+    if prior_frame is None or prior_frame.turn_type not in {
+        "condition_to_drug", "symptom_to_drug"
+    }:
+        return frame
+    text = f" {normalize_name(turn)} "
+    refers_to_candidates = any(
+        cue in text for cue in (" cac thuoc tren ", " trong cac thuoc tren ")
+    )
+    safety_cue = any(
+        cue in text
+        for cue in (
+            " luu y ", " than trong ", " benh than ", " suy than ",
+            " benh gan ", " suy gan ", " di ung ", " tuong tac ",
+        )
+    )
+    if not (refers_to_candidates and safety_cue):
+        return frame
+    condition = frame.condition or prior_frame.condition
+    return replace(
+        frame,
+        turn_type="condition_to_drug",
+        indication=(
+            condition.normalized_condition
+            if condition is not None
+            else frame.indication or prior_frame.indication
+        ),
+        condition=condition,
+        condition_relation=ConditionRelation.INDICATION,
+        needs_clarify=False,
+        clarify_reason=None,
+        quick_replies=(),
+    )
+
+
 def _apply_broad_condition_cue(
     frame: QueryFrame, turn: str, normalizer: ConditionNormalizer
 ) -> QueryFrame:
@@ -1037,7 +1115,17 @@ def _merge_with_prior_frame(frame: QueryFrame, prior_frame: QueryFrame | None) -
         indication=indication or prior_frame.indication,
         condition=condition,
         patient_context=patient_context,
-        attribute=frame.attribute or prior_frame.attribute,
+        # A current drug-attribute clarify with no attribute is an explicit
+        # ambiguity signal (for example, the user named both "chỉ định" and
+        # "chống chỉ định"). Re-inheriting the previous turn's attribute here
+        # silently picks one of those sections and poisons the frame remembered
+        # for the next quick reply. Other continuation shapes still inherit the
+        # prior slot as before (notably pediatric dosing clarifications).
+        attribute=(
+            frame.attribute
+            if frame.turn_type == "drug_attribute" and frame.needs_clarify
+            else frame.attribute or prior_frame.attribute
+        ),
     )