fix(handoff): bound escalation assessment latency

Co-Authored-By: Codex <noreply@openai.com>

backend/app/core/config.py

@@ -111,6 +111,7 @@ class Settings(BaseSettings):
     GOOGLE_AI_API_KEY: Optional[str] = None
     AI_MODEL_GEMINI: str = "gemini-2.5-flash"
     AI_MODEL_ANTHROPIC: str = "claude-sonnet-4-6"
+    ESCALATION_AI_ASSESSMENT_TIMEOUT_SECONDS: int = 5
 
     # Model tier routing — maps action types to model tiers
     AI_MODEL_TIERS: dict[str, str] = {

backend/app/services/handoff_manager.py

@@ -57,7 +57,9 @@ class HandoffManager:
         ai_assessment = None
         ai_assessment_data = None
         if intent == "escalate":
-            ai_assessment, ai_assessment_data = await self._generate_ai_assessment(session)
+            ai_assessment, ai_assessment_data = (
+                await self._generate_ai_assessment_with_timeout(session)
+            )
 
         handoff = SessionHandoff(
             session_id=session_id,
@@ -311,6 +313,24 @@ class HandoffManager:
             logger.exception("Failed to generate AI assessment")
             return None, None
 
+    async def _generate_ai_assessment_with_timeout(
+        self, session: AISession
+    ) -> tuple[str | None, dict[str, Any] | None]:
+        """Generate optional escalation assessment within the click-path budget."""
+        timeout = settings.ESCALATION_AI_ASSESSMENT_TIMEOUT_SECONDS
+        try:
+            return await asyncio.wait_for(
+                self._generate_ai_assessment(session),
+                timeout=timeout,
+            )
+        except asyncio.TimeoutError:
+            logger.warning(
+                "Escalation AI assessment timed out after %ss for session %s",
+                timeout,
+                session.id,
+            )
+            return None, None
+
     async def generate_briefing(
         self, handoff_id: UUID, claiming_user_id: UUID
     ) -> str: