feat: support structured reward outputs and grouped reward aggregation

areal/api/reward_api.py

@@ -56,7 +56,7 @@ def reward_fn(
     :param completion_ids: The token IDs of the trajectory generated by the model.
     :param kwargs: Other attributes of the data in the dataset, such as solutions, input_outputs, etc.
         Any other attributes in the dataset will be passed as keyword arguments to this function.
-    :rtype: float
+    :rtype: float | dict[str, float]
     """
 
 
@@ -135,7 +135,7 @@ def _recreate_executor(cls, executor_key, max_workers):
                 return cls._executors[executor_key]
         return None
 
-    async def __call__(self, *args, **kwargs) -> float:
+    async def __call__(self, *args, **kwargs) -> float | dict[str, float]:
         last_exception = None
 
         for attempt in range(self.max_retries + 1):

areal/infra/remote_inf_engine.py

@@ -102,6 +102,12 @@ async def arun_episode(
                 "trajectories returned None, using remaining results"
             )
 
+        aggregate_group_results = getattr(
+            self.workflow, "aggregate_group_results", None
+        )
+        if callable(aggregate_group_results):
+            return aggregate_group_results(valid_results)
+
         # Check if results are InteractionWithTokenLogpReward dicts
         first = valid_results[0]
         if (