[Executor] Provide exec_aggregation_async for script executor (#2945)

# Description

Provide exec_aggregation_async for script executor.

# All Promptflow Contribution checklist:
- [x] **The pull request does not introduce [breaking changes].**
- [ ] **CHANGELOG is updated for new features, bug fixes or other
significant changes.**
- [x] **I have read the [contribution guidelines](../CONTRIBUTING.md).**
- [ ] **Create an issue and link to the pull request to get dedicated
review from promptflow team. Learn more: [suggested
workflow](../CONTRIBUTING.md#suggested-workflow).**

## General Guidelines and Best Practices
- [x] Title of the pull request is clear and informative.
- [x] There are a small number of commits, each of which have an
informative message. This means that previously merged commits do not
appear in the history of the PR. For more information on cleaning up the
commits in your PR, [see this
page](https://github.com/Azure/azure-powershell/blob/master/documentation/development-docs/cleaning-up-commits.md).

### Testing Guidelines
- [ ] Pull request includes test coverage for the included changes.

---------

Co-authored-by: Lina Tang <[email protected]>

src/promptflow-core/promptflow/executor/_script_executor.py

@@ -35,6 +35,7 @@
 from promptflow.executor._result import AggregationResult, LineResult
 from promptflow.storage import AbstractRunStorage
 from promptflow.storage._run_storage import DefaultRunStorage
+from promptflow.tracing import ThreadPoolExecutorWithContext
 from promptflow.tracing._trace import _traced
 from promptflow.tracing._tracer import Tracer
 from promptflow.tracing.contracts.trace import TraceType
@@ -193,10 +194,31 @@ def _exec_aggregation(
     ) -> AggregationResult:
         output, metrics = None, {}
         try:
-            if inspect.iscoroutinefunction(self._aggr_func):
-                output = async_run_allowing_running_loop(self._aggr_func, **{self._aggr_input_name: inputs})
-            else:
-                output = self._aggr_func(**{self._aggr_input_name: inputs})
+            output = self._aggr_func(**{self._aggr_input_name: inputs})
+            metrics = output if isinstance(output, dict) else {"metrics": output}
+            for k, v in metrics.items():
+                log_metric(k, v)
+        except Exception:
+            pass
+        return AggregationResult(output, metrics, {})
+
+    async def exec_aggregation_async(
+        self,
+        inputs: Mapping[str, Any],
+        aggregation_inputs: List[Any],
+        run_id: Optional[str] = None,
+    ):
+        if not self._aggr_func:
+            return AggregationResult({}, {}, {})
+        # Similar to dag flow, add a prefix "reduce" for run id of aggregation function.
+        run_id = f"{run_id}_reduce" if run_id is not None else f"{str(uuid.uuid4())}_reduce"
+        with self._update_operation_context_for_aggregation(run_id):
+            return await self._exec_aggregation_async(aggregation_inputs)
+
+    async def _exec_aggregation_async(self, inputs):
+        output = None
+        try:
+            output = await self._aggr_func_async(**{self._aggr_input_name: inputs})
             metrics = output if isinstance(output, dict) else {"metrics": output}
             for k, v in metrics.items():
                 log_metric(k, v)
@@ -430,7 +452,22 @@ def _initialize_aggr_function(self, flow_obj: object):
                 )
             if not hasattr(aggr_func, "__original_function"):
                 aggr_func = _traced(aggr_func)
-            self._aggr_func = aggr_func
+            if inspect.iscoroutinefunction(aggr_func):
+
+                def run_async_function_sync(*args, **kwargs):
+                    return async_run_allowing_running_loop(aggr_func, *args, **kwargs)
+
+                self._aggr_func = run_async_function_sync
+                self._aggr_func_async = aggr_func
+            else:
+
+                async def run_sync_function_async(*args, **kwargs):
+                    with ThreadPoolExecutorWithContext() as executor:
+                        partial_func = partial(aggr_func, *args, **kwargs)
+                        return await asyncio.get_event_loop().run_in_executor(executor, partial_func)
+
+                self._aggr_func = aggr_func
+                self._aggr_func_async = run_sync_function_async
             self._aggr_input_name = list(sign.parameters.keys())[0]
 
     def _parse_flow_file(self):