feat(backend): migrate AgentExecutor from ProcessPoolExecutor to ThreadPoolExecutor

- Migrate execution manager from ProcessPoolExecutor to ThreadPoolExecutor for improved performance and resource efficiency
- Rename `Executor` class to `ExecutionProcessor` for better clarity
- Convert classmethods to instance methods following proper OOP design patterns
- Implement thread-local storage using `threading.local()` for thread-safe execution
- Replace process ID tracking with thread ID tracking using `threading.get_ident()`
- Replace `multiprocessing.Manager().Event()` with `threading.Event()`
- Remove signal handling code that doesn't work in worker threads
- Update ExecutionManager to use ThreadPoolExecutor with new `init_worker` initializer

Benefits:
- Performance: Reduced overhead compared to process creation/destruction
- Resource Efficiency: Lower memory footprint and faster startup
- Simplicity: Cleaner implementation using thread-local storage pattern
- Thread Safety: Maintained through isolated ExecutionProcessor instances per thread

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

autogpt_platform/backend/backend/executor/manager.py

@@ -1,11 +1,10 @@
 import asyncio
 import logging
-import multiprocessing
 import os
 import threading
 import time
 from collections import defaultdict
-from concurrent.futures import Future, ProcessPoolExecutor
+from concurrent.futures import Future, ThreadPoolExecutor
 from contextlib import asynccontextmanager
 from typing import TYPE_CHECKING, Any, Optional, TypeVar, cast
 
@@ -102,6 +101,22 @@ utilization_gauge = Gauge(
     "Ratio of active graph runs to max graph workers",
 )
 
+# Thread-local storage for ExecutionProcessor instances
+_tls = threading.local()
+
+
+def init_worker():
+    """Initialize ExecutionProcessor instance in thread-local storage"""
+    _tls.processor = ExecutionProcessor()
+    _tls.processor.on_graph_executor_start()
+
+
+def execute_graph(
+    graph_exec_entry: "GraphExecutionEntry", cancel_event: threading.Event
+):
+    """Execute graph using thread-local ExecutionProcessor instance"""
+    return _tls.processor.on_graph_execution(graph_exec_entry, cancel_event)
+
 
 T = TypeVar("T")
 
@@ -366,7 +381,7 @@ async def _enqueue_next_nodes(
     ]
 
 
-class Executor:
+class ExecutionProcessor:
     """
     This class contains event handlers for the process pool executor events.
 
@@ -389,10 +404,9 @@ class Executor:
         9. Node executor enqueues the next executed nodes to the node execution queue.
     """
 
-    @classmethod
     @async_error_logged(swallow=True)
     async def on_node_execution(
-        cls,
+        self,
         node_exec: NodeExecutionEntry,
         node_exec_progress: NodeExecutionProgress,
         nodes_input_masks: Optional[dict[str, dict[str, JsonValue]]],
@@ -411,7 +425,7 @@ class Executor:
         node = await db_client.get_node(node_exec.node_id)
         execution_stats = NodeExecutionStats()
 
-        timing_info, status = await cls._on_node_execution(
+        timing_info, status = await self._on_node_execution(
             node=node,
             node_exec=node_exec,
             node_exec_progress=node_exec_progress,
@@ -454,10 +468,9 @@ class Executor:
 
         return execution_stats
 
-    @classmethod
     @async_time_measured
     async def _on_node_execution(
-        cls,
+        self,
         node: Node,
         node_exec: NodeExecutionEntry,
         node_exec_progress: NodeExecutionProgress,
@@ -497,7 +510,7 @@ class Executor:
 
             async for output_name, output_data in execute_node(
                 node=node,
-                creds_manager=cls.creds_manager,
+                creds_manager=self.creds_manager,
                 data=node_exec,
                 execution_stats=stats,
                 nodes_input_masks=nodes_input_masks,
@@ -537,29 +550,27 @@ class Executor:
 
         return status
 
-    @classmethod
     @func_retry
-    def on_graph_executor_start(cls):
+    def on_graph_executor_start(self):
         configure_logging()
         set_service_name("GraphExecutor")
-        cls.pid = os.getpid()
-        cls.creds_manager = IntegrationCredentialsManager()
-        cls.node_execution_loop = asyncio.new_event_loop()
-        cls.node_evaluation_loop = asyncio.new_event_loop()
-        cls.node_execution_thread = threading.Thread(
-            target=cls.node_execution_loop.run_forever, daemon=True
+        self.tid = threading.get_ident()
+        self.creds_manager = IntegrationCredentialsManager()
+        self.node_execution_loop = asyncio.new_event_loop()
+        self.node_evaluation_loop = asyncio.new_event_loop()
+        self.node_execution_thread = threading.Thread(
+            target=self.node_execution_loop.run_forever, daemon=True
         )
-        cls.node_evaluation_thread = threading.Thread(
-            target=cls.node_evaluation_loop.run_forever, daemon=True
+        self.node_evaluation_thread = threading.Thread(
+            target=self.node_evaluation_loop.run_forever, daemon=True
         )
-        cls.node_execution_thread.start()
-        cls.node_evaluation_thread.start()
-        logger.info(f"[GraphExecutor] {cls.pid} started")
+        self.node_execution_thread.start()
+        self.node_evaluation_thread.start()
+        logger.info(f"[GraphExecutor] {self.tid} started")
 
-    @classmethod
     @error_logged(swallow=False)
     def on_graph_execution(
-        cls,
+        self,
         graph_exec: GraphExecutionEntry,
         cancel: threading.Event,
     ):
@@ -615,7 +626,7 @@ class Executor:
         else:
             exec_stats = exec_meta.stats.to_db()
 
-        timing_info, status = cls._on_graph_execution(
+        timing_info, status = self._on_graph_execution(
             graph_exec=graph_exec,
             cancel=cancel,
             log_metadata=log_metadata,
@@ -641,7 +652,7 @@ class Executor:
                     user_id=graph_exec.user_id,
                     execution_status=status,
                 ),
-                cls.node_execution_loop,
+                self.node_execution_loop,
             ).result(timeout=60.0)
             if activity_status is not None:
                 exec_stats.activity_status = activity_status
@@ -652,7 +663,7 @@ class Executor:
                 )
 
             # Communication handling
-            cls._handle_agent_run_notif(db_client, graph_exec, exec_stats)
+            self._handle_agent_run_notif(db_client, graph_exec, exec_stats)
 
         finally:
             update_graph_execution_state(
@@ -662,9 +673,8 @@ class Executor:
                 stats=exec_stats,
             )
 
-    @classmethod
     def _charge_usage(
-        cls,
+        self,
         node_exec: NodeExecutionEntry,
         execution_count: int,
     ) -> int:
@@ -714,22 +724,15 @@ class Executor:
 
         return total_cost
 
-    @classmethod
     @time_measured
     def _on_graph_execution(
-        cls,
+        self,
         graph_exec: GraphExecutionEntry,
         cancel: threading.Event,
         log_metadata: LogMetadata,
         execution_stats: GraphExecutionStats,
     ) -> ExecutionStatus:
 
-        # Agent execution is uninterrupted.
-        import signal
-
-        signal.signal(signal.SIGINT, signal.SIG_IGN)
-        signal.signal(signal.SIGTERM, signal.SIG_IGN)
-
         """
         Returns:
             dict: The execution statistics of the graph execution.
@@ -786,7 +789,7 @@ class Executor:
 
                 # Charge usage (may raise) ------------------------------
                 try:
-                    cost = cls._charge_usage(
+                    cost = self._charge_usage(
                         node_exec=queued_node_exec,
                         execution_count=increment_execution_count(graph_exec.user_id),
                     )
@@ -806,7 +809,7 @@ class Executor:
                         status=ExecutionStatus.FAILED,
                     )
 
-                    cls._handle_low_balance_notif(
+                    self._handle_low_balance_notif(
                         db_client,
                         graph_exec.user_id,
                         graph_exec.graph_id,
@@ -825,7 +828,7 @@ class Executor:
 
                 # Kick off async node execution -------------------------
                 node_execution_task = asyncio.run_coroutine_threadsafe(
-                    cls.on_node_execution(
+                    self.on_node_execution(
                         node_exec=queued_node_exec,
                         node_exec_progress=running_node_execution[node_id],
                         nodes_input_masks=nodes_input_masks,
@@ -834,7 +837,7 @@ class Executor:
                             execution_stats_lock,
                         ),
                     ),
-                    cls.node_execution_loop,
+                    self.node_execution_loop,
                 )
                 running_node_execution[node_id].add_task(
                     node_exec_id=queued_node_exec.node_exec_id,
@@ -875,7 +878,7 @@ class Executor:
                             node_output_found = True
                             running_node_evaluation[node_id] = (
                                 asyncio.run_coroutine_threadsafe(
-                                    cls._process_node_output(
+                                    self._process_node_output(
                                         output=output,
                                         node_id=node_id,
                                         graph_exec=graph_exec,
@@ -883,7 +886,7 @@ class Executor:
                                         nodes_input_masks=nodes_input_masks,
                                         execution_queue=execution_queue,
                                     ),
-                                    cls.node_evaluation_loop,
+                                    self.node_evaluation_loop,
                                 )
                             )
                     if (
@@ -926,7 +929,7 @@ class Executor:
             raise
 
         finally:
-            cls._cleanup_graph_execution(
+            self._cleanup_graph_execution(
                 execution_queue=execution_queue,
                 running_node_execution=running_node_execution,
                 running_node_evaluation=running_node_evaluation,
@@ -937,10 +940,9 @@ class Executor:
                 db_client=db_client,
             )
 
-    @classmethod
     @error_logged(swallow=True)
     def _cleanup_graph_execution(
-        cls,
+        self,
         execution_queue: ExecutionQueue[NodeExecutionEntry],
         running_node_execution: dict[str, "NodeExecutionProgress"],
         running_node_evaluation: dict[str, Future],
@@ -991,10 +993,9 @@ class Executor:
 
         clean_exec_files(graph_exec_id)
 
-    @classmethod
     @async_error_logged(swallow=True)
     async def _process_node_output(
-        cls,
+        self,
         output: ExecutionOutputEntry,
         node_id: str,
         graph_exec: GraphExecutionEntry,
@@ -1027,9 +1028,8 @@ class Executor:
         ):
             execution_queue.add(next_execution)
 
-    @classmethod
     def _handle_agent_run_notif(
-        cls,
+        self,
         db_client: "DatabaseManagerClient",
         graph_exec: GraphExecutionEntry,
         exec_stats: GraphExecutionStats,
@@ -1065,9 +1065,8 @@ class Executor:
             )
         )
 
-    @classmethod
     def _handle_low_balance_notif(
-        cls,
+        self,
         db_client: "DatabaseManagerClient",
         user_id: str,
         graph_id: str,
@@ -1132,11 +1131,11 @@ class ExecutionManager(AppProcess):
         return self._stop_consuming
 
     @property
-    def executor(self) -> ProcessPoolExecutor:
+    def executor(self) -> ThreadPoolExecutor:
         if self._executor is None:
-            self._executor = ProcessPoolExecutor(
+            self._executor = ThreadPoolExecutor(
                 max_workers=self.pool_size,
-                initializer=Executor.on_graph_executor_start,
+                initializer=init_worker,
             )
         return self._executor
 
@@ -1313,11 +1312,9 @@ class ExecutionManager(AppProcess):
             _ack_message(reject=True)
             return
 
-        cancel_event = multiprocessing.Manager().Event()
+        cancel_event = threading.Event()
 
-        future = self.executor.submit(
-            Executor.on_graph_execution, graph_exec_entry, cancel_event
-        )
+        future = self.executor.submit(execute_graph, graph_exec_entry, cancel_event)
         self.active_graph_runs[graph_exec_id] = (future, cancel_event)
         self._update_prompt_metrics()