feat: add tiered durable state and memory bounds

modelhub_submmit_api/config_optimizer.py

@@ -18,7 +18,13 @@ class SafeConfigOptimizer:
         self._qualified = self._learn()
 
     def _learn(self) -> dict[tuple[str, str, str], list[dict[str, Any]]]:
-        outcomes = read_jsonl(self.outcomes_path)
+        recent_path = Path(".modelhub_state/recent_outcomes.jsonl")
+        outcomes_by_key: dict[str, dict[str, Any]] = {}
+        for item in [*read_jsonl(recent_path), *read_jsonl(self.outcomes_path)]:
+            task_id = str(item.get("taskId") or "")
+            if task_id:
+                outcomes_by_key[task_id] = item
+        outcomes = list(outcomes_by_key.values())
         by_task = {
             str(item.get("taskId")): item
             for item in outcomes
@@ -117,4 +123,3 @@ class SafeConfigOptimizer:
             "evidenceLowerBound": choice["lowerBound"],
             "fingerprint": choice["fingerprint"],
         }
-