개선관리 요구사항과 Google 로그인을 완료

apps/api/app/services/orchestrator.py

@@ -79,6 +79,8 @@ class TurnContext:
     state_before: SessionState
     learner_text_raw: str
     learner_text_masked: str = ""
+    counselor_identity: Optional[str] = None
+    client_identity: Optional[str] = None
     crisis: Optional[guardrail.CrisisResult] = None
     state_after: Optional[SessionState] = None
     messages: list[EngineMessage] = field(default_factory=list)
@@ -133,6 +135,7 @@ def prepare_turn(
     card: PersonaCard,
     state: SessionState,
     learner_text: str,
+    learner_identity: Optional[str] = None,
     memory: Optional[TurnMemory] = None,
     theory_mode: Optional[str] = None,
     eval_rapport_signal: Optional[float] = None,
@@ -146,23 +149,42 @@ def prepare_turn(
     state_machine 의 경량 휴리스틱으로 라포 신호를 추정한다.
     """
     turn_memory = memory or TurnMemory()
+    client_identity = card.display_name
     ctx = TurnContext(
         session_id=session_id,
         case_id=case_id,
         persona=card,
         state_before=state,
         learner_text_raw=learner_text,
+        counselor_identity=learner_identity,
+        client_identity=client_identity,
         memory=TurnMemory(
-            recall_summary=_mask_optional_text(turn_memory.recall_summary),
-            pinned_facts=_mask_text_list(turn_memory.pinned_facts),
-            recent_turns=_mask_recent_turns(turn_memory.recent_turns),
+            recall_summary=_mask_optional_text(
+                turn_memory.recall_summary,
+                counselor_identity=learner_identity,
+                client_identity=client_identity,
+            ),
+            pinned_facts=_mask_text_list(
+                turn_memory.pinned_facts,
+                counselor_identity=learner_identity,
+                client_identity=client_identity,
+            ),
+            recent_turns=_mask_recent_turns(
+                turn_memory.recent_turns,
+                counselor_identity=learner_identity,
+                client_identity=client_identity,
+            ),
             kb_behavior_cues=list(turn_memory.kb_behavior_cues or []),
         ),
         theory_mode=theory_mode,
     )
 
     # 1) 입력 가드레일 — PII 마스킹 + 위기분류
-    mask = guardrail.mask_pii(learner_text)
+    mask = guardrail.mask_role_identities(
+        learner_text,
+        counselor_identity=learner_identity,
+        client_identity=client_identity,
+    )
     ctx.learner_text_masked = mask.text_masked
     ctx.crisis = guardrail.classify_crisis(learner_text, speaker_is_persona_context=True)
 
@@ -210,21 +232,51 @@ def prepare_turn(
     return ctx
 
 
-def _mask_optional_text(text: Optional[str]) -> Optional[str]:
+def _mask_optional_text(
+    text: Optional[str],
+    *,
+    counselor_identity: Optional[str] = None,
+    client_identity: Optional[str] = None,
+) -> Optional[str]:
     if text is None:
         return None
-    return guardrail.mask_pii(text).text_masked
+    return guardrail.mask_role_identities(
+        text,
+        counselor_identity=counselor_identity,
+        client_identity=client_identity,
+    ).text_masked
 
 
-def _mask_text_list(values: Optional[list[str]]) -> list[str]:
-    return [guardrail.mask_pii(value).text_masked for value in (values or [])]
+def _mask_text_list(
+    values: Optional[list[str]],
+    *,
+    counselor_identity: Optional[str] = None,
+    client_identity: Optional[str] = None,
+) -> list[str]:
+    return [
+        guardrail.mask_role_identities(
+            value,
+            counselor_identity=counselor_identity,
+            client_identity=client_identity,
+        ).text_masked
+        for value in (values or [])
+    ]
 
 
-def _mask_recent_turns(turns: Optional[list[dict[str, str]]]) -> list[dict[str, str]]:
+def _mask_recent_turns(
+    turns: Optional[list[dict[str, str]]],
+    *,
+    counselor_identity: Optional[str] = None,
+    client_identity: Optional[str] = None,
+) -> list[dict[str, str]]:
     masked: list[dict[str, str]] = []
     for turn in turns or []:
         item = dict(turn)
-        item["text"] = guardrail.mask_pii(str(item.get("text", ""))).text_masked
+        item["text"] = guardrail.mask_role_identities(
+            str(item.get("text", "")),
+            counselor_identity=counselor_identity,
+            client_identity=client_identity,
+        ).text_masked
         masked.append(item)
     return masked
 
@@ -427,6 +479,7 @@ async def run_turn_stream(
     flagged = False
     output_error: str | None = None
     stream_meta: dict[str, Any] = {}
+    gateway_done = False
     previous_client_reply = _latest_client_reply(ctx.memory.recent_turns)
     if ctx.crisis is not None and ctx.crisis.escalate:
         flagged = True
@@ -471,6 +524,7 @@ async def run_turn_stream(
                 payload = packet.payload
                 if isinstance(payload, StreamDoneEvent):
                     stream_meta = payload.model_dump()
+                    gateway_done = True
                 break
 
             payload = packet.payload
@@ -479,6 +533,12 @@ async def run_turn_stream(
             text_piece = payload.text
             accumulated += text_piece
 
+        if not gateway_done:
+            # 토큰 일부 또는 빈 본문 뒤 연결이 끊겨도 성공 done을 합성하지 않는다.
+            # 라우트는 이 error 이벤트를 전달하고 durable turn을 저장하지 않는다.
+            yield StreamEvent("error", {"detail": "client_stream_incomplete"})
+            return
+
         scenario_leakage = rupture_scenario_director.contains_internal_scenario_leakage(
             accumulated
         )