Close local release-quality gaps and reconcile workplan status

Assistant: codex
Assistant-Model: gpt-6-astra
Assistant-Session: 01a0e332-3365-77c0-8491-084e9ea33ac1

llm_connect/routing.py

@@ -4,9 +4,9 @@ RoutingPolicy — task-type-aware adapter selection (FR-2).
 Maps task types to preferred adapters with optional cost-cap fallback.
 """
 
+from collections.abc import Mapping
 from dataclasses import dataclass, field
 from datetime import datetime, timedelta, timezone
-from typing import List, Mapping, Optional
 
 from llm_connect.adapter import LLMAdapter
 from llm_connect.quality import QualityLedger, QualityObservation
@@ -27,8 +27,8 @@ class RoutingRule:
 
     task_type: str
     prefer: LLMAdapter
-    max_cost_per_1k: Optional[float] = None
-    fallback: Optional[LLMAdapter] = None
+    max_cost_per_1k: float | None = None
+    fallback: LLMAdapter | None = None
 
 
 @dataclass
@@ -50,13 +50,13 @@ class RoutingPolicy:
         adapter = policy.resolve("triage")
     """
 
-    rules: List[RoutingRule] = field(default_factory=list)
-    default: Optional[LLMAdapter] = None
+    rules: list[RoutingRule] = field(default_factory=list)
+    default: LLMAdapter | None = None
 
     def resolve(
         self,
         task_type: str,
-        estimated_cost_per_1k: Optional[float] = None,
+        estimated_cost_per_1k: float | None = None,
     ) -> LLMAdapter:
         """Return the adapter for *task_type*.
 
@@ -111,11 +111,11 @@ class AdaptiveRoutingPolicy(RoutingPolicy):
     caller can use the same policy on day zero and after observations accrue.
     """
 
-    ledger: Optional[QualityLedger] = None
+    ledger: QualityLedger | None = None
     adapters_by_id: Mapping[str, LLMAdapter] = field(default_factory=dict)
     window_size: int = 20
     min_observations: int = 1
-    max_age: Optional[timedelta] = None
+    max_age: timedelta | None = None
 
     def __post_init__(self) -> None:
         if self.window_size <= 0:
@@ -128,9 +128,9 @@ class AdaptiveRoutingPolicy(RoutingPolicy):
     def resolve(
         self,
         task_type: str,
-        estimated_cost_per_1k: Optional[float] = None,
+        estimated_cost_per_1k: float | None = None,
         *,
-        quality_floor: Optional[float] = None,
+        quality_floor: float | None = None,
     ) -> LLMAdapter:
         """Return the adaptive adapter for *task_type*.