[fix] celery task

api/app/celery_worker.py

@@ -19,15 +19,35 @@ import app.tasks
 @worker_process_init.connect
 def _reinit_db_pool(**kwargs):
     """
-    prefork 子进程启动时重建 SQLAlchemy 连接池。
+    prefork 子进程启动时重建被 fork 污染的资源。
     
-    fork() 后子进程继承了父进程的连接池和底层 TCP socket，
+    fork() 后子进程继承了父进程的：
-    多个子进程共享同一个 socket 会导致 PostgreSQL 连接损坏。
+    1. SQLAlchemy 连接池 — 多进程共享 TCP socket 导致 DB 连接损坏
-    dispose() 会关闭继承来的连接，后续操作会自动创建新连接。
+    2. ThreadPoolExecutor — fork 后线程状态不确定，第二个任务会死锁
     """
+    # 重建 DB 连接池
     from app.db import engine
     engine.dispose()
     logger.info("DB connection pool disposed for forked worker process")
 
+    # 重建模块级 ThreadPoolExecutor（fork 后线程池不可用）
+    try:
+        from app.core.rag.deepdoc.parser import figure_parser
+        from concurrent.futures import ThreadPoolExecutor
+        figure_parser.shared_executor = ThreadPoolExecutor(max_workers=10)
+        logger.info("figure_parser.shared_executor recreated")
+    except Exception as e:
+        logger.warning(f"Failed to recreate figure_parser.shared_executor: {e}")
+
+    try:
+        from app.core.rag.utils import libre_office
+        from concurrent.futures import ThreadPoolExecutor
+        import os
+        max_workers = os.cpu_count() * 2 if os.cpu_count() else 4
+        libre_office.executor = ThreadPoolExecutor(max_workers=max_workers)
+        logger.info("libre_office.executor recreated")
+    except Exception as e:
+        logger.warning(f"Failed to recreate libre_office.executor: {e}")
+
 
 __all__ = ['celery_app']

api/app/core/rag/common/connection_utils.py

@@ -33,18 +33,16 @@ def timeout(seconds: float | int | str = None, attempts: int = 2, *, exception:
             thread.daemon = True
             thread.start()
 
+            effective_timeout = seconds if seconds else 120  # 默认 120 秒超时
             for a in range(attempts):
                 try:
-                    if os.environ.get("ENABLE_TIMEOUT_ASSERTION"):
+                    result = result_queue.get(timeout=effective_timeout)
-                        result = result_queue.get(timeout=seconds)
-                    else:
-                        result = result_queue.get()
                     if isinstance(result, Exception):
                         raise result
                     return result
                 except queue.Empty:
                     pass
-            raise TimeoutError(f"Function '{func.__name__}' timed out after {seconds} seconds and {attempts} attempts.")
+            raise TimeoutError(f"Function '{func.__name__}' timed out after {effective_timeout} seconds and {attempts} attempts.")
 
         @wraps(func)
         async def async_wrapper(*args, **kwargs) -> Any:

api/app/tasks.py

@@ -268,18 +268,21 @@ def parse_document(file_path: str, document_id: uuid.UUID):
             try:
                 with open(file_path, "rb") as f:
                     file_binary = f.read()
+                if not file_binary:
+                    # NFS 上文件存在但内容为空（可能还在同步中）
+                    raise IOError(f"File is empty (0 bytes), NFS may still be syncing: {file_path}")
                 break
-            except FileNotFoundError:
+            except (FileNotFoundError, IOError) as e:
                 if waited >= max_wait_seconds:
-                    raise FileNotFoundError(
+                    raise type(e)(
-                        f"File not found at '{file_path}' after waiting {max_wait_seconds}s "
+                        f"File not accessible at '{file_path}' after waiting {max_wait_seconds}s: {e}"
-                        f"(NFS cache may be stale)"
                     )
-                logger.warning(f"File not visible yet on this node, retrying in {wait_interval}s: {file_path}")
+                logger.warning(f"File not ready on this node, retrying in {wait_interval}s: {file_path} ({e})")
                 time.sleep(wait_interval)
                 waited += wait_interval
 
         from app.core.rag.app.naive import chunk
+        logger.info(f"[ParseDoc] file_binary size={len(file_binary)} bytes, type={type(file_binary).__name__}, bool={bool(file_binary)}")
         res = chunk(filename=file_path,
                     binary=file_binary,
                     from_page=0,