Fix linting

lightrag/lightrag.py

@@ -274,6 +274,7 @@ class LightRAG:
         from lightrag.kg.shared_storage import (
             initialize_share_data,
         )
+
         initialize_share_data()
 
         if not os.path.exists(self.working_dir):
@@ -671,44 +672,45 @@ class LightRAG:
         4. Update the document status
         """
         from lightrag.kg.shared_storage import get_namespace_data, get_storage_lock
-        
+
         # Get pipeline status shared data and lock
         pipeline_status = get_namespace_data("pipeline_status")
         storage_lock = get_storage_lock()
-        
+
         # Check if another process is already processing the queue
         process_documents = False
         with storage_lock:
+            # Ensure only one worker is processing documents
             if not pipeline_status.get("busy", False):
-                # No other process is busy, we can process documents
-                # 获取当前的 history_messages 列表
+                # Cleaning history_messages without breaking it as a shared list object 
                 current_history = pipeline_status.get("history_messages", [])
-                
-                # 清空当前列表内容但保持同一个列表对象
                 if hasattr(current_history, "clear"):
                     current_history.clear()
-                
-                pipeline_status.update({
-                    "busy": True,
-                    "job_name": "indexing files",
-                    "job_start": datetime.now().isoformat(),
-                    "docs": 0,
-                    "batchs": 0,
-                    "cur_batch": 0,
-                    "request_pending": False,  # Clear any previous request
-                    "latest_message": "",
-                    # 保持使用同一个列表对象
-                    "history_messages": current_history,
-                })
+
+                pipeline_status.update(
+                    {
+                        "busy": True,
+                        "job_name": "indexing files",
+                        "job_start": datetime.now().isoformat(),
+                        "docs": 0,
+                        "batchs": 0,
+                        "cur_batch": 0,
+                        "request_pending": False,  # Clear any previous request
+                        "latest_message": "",
+                        "history_messages": current_history,  # keep it as a shared list object
+                    }
+                )
                 process_documents = True
             else:
                 # Another process is busy, just set request flag and return
                 pipeline_status["request_pending"] = True
-                logger.info("Another process is already processing the document queue. Request queued.")
-        
+                logger.info(
+                    "Another process is already processing the document queue. Request queued."
+                )
+
         if not process_documents:
             return
-        
+
         try:
             # Process documents until no more documents or requests
             while True:
@@ -734,7 +736,7 @@ class LightRAG:
                 # Update pipeline status with document count (with lock)
                 with storage_lock:
                     pipeline_status["docs"] = len(to_process_docs)
-                
+
                 # 2. split docs into chunks, insert chunks, update doc status
                 docs_batches = [
                     list(to_process_docs.items())[i : i + self.max_parallel_insert]
@@ -742,11 +744,8 @@ class LightRAG:
                 ]
 
                 # Update pipeline status with batch information (directly, as it's atomic)
-                pipeline_status.update({
-                    "batchs": len(docs_batches),
-                    "cur_batch": 0
-                })
-                
+                pipeline_status.update({"batchs": len(docs_batches), "cur_batch": 0})
+
                 log_message = f"Number of batches to process: {len(docs_batches)}."
                 logger.info(log_message)
                 pipeline_status["latest_message"] = log_message
@@ -757,13 +756,15 @@ class LightRAG:
                 for batch_idx, docs_batch in enumerate(docs_batches):
                     # Update current batch in pipeline status (directly, as it's atomic)
                     pipeline_status["cur_batch"] = batch_idx + 1
-                    
+
                     async def batch(
                         batch_idx: int,
                         docs_batch: list[tuple[str, DocProcessingStatus]],
                         size_batch: int,
                     ) -> None:
-                        log_message = f"Start processing batch {batch_idx + 1} of {size_batch}."
+                        log_message = (
+                            f"Start processing batch {batch_idx + 1} of {size_batch}."
+                        )
                         logger.info(log_message)
                         pipeline_status["latest_message"] = log_message
                         pipeline_status["history_messages"].append(log_message)
@@ -822,7 +823,9 @@ class LightRAG:
                                     }
                                 )
                             except Exception as e:
-                                logger.error(f"Failed to process document {doc_id}: {str(e)}")
+                                logger.error(
+                                    f"Failed to process document {doc_id}: {str(e)}"
+                                )
                                 await self.doc_status.upsert(
                                     {
                                         doc_id: {
@@ -837,7 +840,9 @@ class LightRAG:
                                     }
                                 )
                                 continue
-                        log_message = f"Completed batch {batch_idx + 1} of {len(docs_batches)}."
+                        log_message = (
+                            f"Completed batch {batch_idx + 1} of {len(docs_batches)}."
+                        )
                         logger.info(log_message)
                         pipeline_status["latest_message"] = log_message
                         pipeline_status["history_messages"].append(log_message)
@@ -846,7 +851,7 @@ class LightRAG:
 
                 await asyncio.gather(*batches)
                 await self._insert_done()
-                
+
                 # Check if there's a pending request to process more documents (with lock)
                 has_pending_request = False
                 with storage_lock:
@@ -854,15 +859,15 @@ class LightRAG:
                     if has_pending_request:
                         # Clear the request flag before checking for more documents
                         pipeline_status["request_pending"] = False
-                
+
                 if not has_pending_request:
                     break
-                    
+
                 log_message = "Processing additional documents due to pending request"
                 logger.info(log_message)
                 pipeline_status["latest_message"] = log_message
                 pipeline_status["history_messages"].append(log_message)
-        
+
         finally:
             # Always reset busy status when done or if an exception occurs (with lock)
             with storage_lock:
@@ -901,12 +906,13 @@ class LightRAG:
             if storage_inst is not None
         ]
         await asyncio.gather(*tasks)
-        
+
         log_message = "All Insert done"
         logger.info(log_message)
-        
+
         # 获取 pipeline_status 并更新 latest_message 和 history_messages
         from lightrag.kg.shared_storage import get_namespace_data
+
         pipeline_status = get_namespace_data("pipeline_status")
         pipeline_status["latest_message"] = log_message
         pipeline_status["history_messages"].append(log_message)