fix(server): Always JSON-encode AgentNodeExecutionInputOutput data (#8010)

- Handle JSON-encoding inside `.data.execution.upsert_execution_output(..)` to ensure it is always encoded the same
- Amend `.executor.manager.execute_node(..)` to pass unencoded data into `upsert_execution_output(..)`

rnd/autogpt_server/autogpt_server/data/execution.py

@@ -245,7 +245,7 @@ async def upsert_execution_input(
 async def upsert_execution_output(
     node_exec_id: str,
     output_name: str,
-    output_data: str,  # JSON serialized data.
+    output_data: Any,
 ) -> None:
     """
     Insert AgentNodeExecutionInputOutput record for as one of AgentNodeExecution.Output.
@@ -253,7 +253,7 @@ async def upsert_execution_output(
     await AgentNodeExecutionInputOutput.prisma().create(
         data={
             "name": output_name,
-            "data": output_data,
+            "data": json.dumps(output_data),
             "referencedByOutputExecId": node_exec_id,
         }
     )

rnd/autogpt_server/autogpt_server/executor/manager.py

@@ -134,13 +134,12 @@ def execute_node(
     output_size = 0
     try:
         for output_name, output_data in node_block.execute(input_data):
-            output_data_str = json.dumps(output_data)
-            output_size += len(output_data_str)
+            output_size += len(json.dumps(output_data))
             logger.info(
                 "Node produced output",
-                extra={"json_fields": {**log_metadata, output_name: output_data_str}},
+                extra={"json_fields": {**log_metadata, output_name: output_data}},
             )
-            wait(upsert_execution_output(node_exec_id, output_name, output_data_str))
+            wait(upsert_execution_output(node_exec_id, output_name, output_data))
 
             for execution in _enqueue_next_nodes(
                 api_client=api_client,