Fix linting

lightrag/api/routers/document_routes.py

@@ -60,7 +60,9 @@ class InsertResponse(BaseModel):
 
 
 class ClearDocumentsResponse(BaseModel):
-    status: str = Field(description="Status of the clear operation: success/partial_success/busy/fail")
+    status: str = Field(
+        description="Status of the clear operation: success/partial_success/busy/fail"
+    )
     message: str = Field(description="Message describing the operation result")
 
 
@@ -783,7 +785,10 @@ def create_document_routes(
             HTTPException: Raised when a serious error occurs during the clearing process,
                           with status code 500 and error details in the detail field.
         """
-        from lightrag.kg.shared_storage import get_namespace_data, get_pipeline_status_lock
+        from lightrag.kg.shared_storage import (
+            get_namespace_data,
+            get_pipeline_status_lock,
+        )
 
         # Get pipeline status and lock
         pipeline_status = await get_namespace_data("pipeline_status")
@@ -794,14 +799,16 @@ def create_document_routes(
             if pipeline_status.get("busy", False):
                 return ClearDocumentsResponse(
                     status="busy",
-                    message="Cannot clear documents while pipeline is busy"
+                    message="Cannot clear documents while pipeline is busy",
                 )
             # Set busy to true
             pipeline_status["busy"] = True
             pipeline_status["job_name"] = "Clearing Documents"
             pipeline_status["latest_message"] = "Starting document clearing process"
             if "history_messages" in pipeline_status:
-                pipeline_status["history_messages"].append("Starting document clearing process")
+                pipeline_status["history_messages"].append(
+                    "Starting document clearing process"
+                )
 
         try:
             # Use drop method to clear all data
@@ -813,12 +820,14 @@ def create_document_routes(
                 rag.relationships_vdb,
                 rag.chunks_vdb,
                 rag.chunk_entity_relation_graph,
-                rag.doc_status
+                rag.doc_status,
             ]
 
             # Log storage drop start
             if "history_messages" in pipeline_status:
-                pipeline_status["history_messages"].append("Starting to drop storage components")
+                pipeline_status["history_messages"].append(
+                    "Starting to drop storage components"
+                )
 
             for storage in storages:
                 if storage is not None:
@@ -860,14 +869,13 @@ def create_document_routes(
                 logger.error(error_message)
                 if "history_messages" in pipeline_status:
                     pipeline_status["history_messages"].append(error_message)
-                return ClearDocumentsResponse(
+                return ClearDocumentsResponse(status="fail", message=error_message)
-                    status="fail",
-                    message=error_message
-                )
 
             # Log file deletion start
             if "history_messages" in pipeline_status:
-                pipeline_status["history_messages"].append("Starting to delete files in input directory")
+                pipeline_status["history_messages"].append(
+                    "Starting to delete files in input directory"
+                )
 
             # Delete all files in input_dir
             deleted_files_count = 0
@@ -903,16 +911,12 @@ def create_document_routes(
                 final_message = f"All documents cleared successfully. Deleted {deleted_files_count} files."
                 status = "success"
 
-
             # Log final result
             if "history_messages" in pipeline_status:
                 pipeline_status["history_messages"].append(final_message)
 
             # Return response based on results
-            return ClearDocumentsResponse(
+            return ClearDocumentsResponse(status=status, message=final_message)
-                status=status,
-                message=final_message
-            )
         except Exception as e:
             error_msg = f"Error clearing documents: {str(e)}"
             logger.error(error_msg)

lightrag/base.py

@@ -259,7 +259,7 @@ class BaseKVStorage(StorageNameSpace, ABC):
             None
         """
 
-    async def drop_cache_by_modes(self, modes: list[str] | None = None) ->  bool:
+    async def drop_cache_by_modes(self, modes: list[str] | None = None) -> bool:
         """Delete specific records from storage by cache mode
 
         Importance notes for in-memory storage:
@@ -274,6 +274,7 @@ class BaseKVStorage(StorageNameSpace, ABC):
              False: if the cache drop failed, or the cache mode is not supported
         """
 
+
 @dataclass
 class BaseGraphStorage(StorageNameSpace, ABC):
     embedding_func: EmbeddingFunc
@@ -394,7 +395,7 @@ class DocStatusStorage(BaseKVStorage, ABC):
     ) -> dict[str, DocProcessingStatus]:
         """Get all documents with a specific status"""
 
-    async def drop_cache_by_modes(self, modes: list[str] | None = None) ->  bool:
+    async def drop_cache_by_modes(self, modes: list[str] | None = None) -> bool:
         """Drop cache is not supported for Doc Status storage"""
         return False
 

lightrag/kg/age_impl.py

@@ -34,9 +34,9 @@ if not pm.is_installed("psycopg-pool"):
 if not pm.is_installed("asyncpg"):
     pm.install("asyncpg")
 
-import psycopg # type: ignore
+import psycopg  # type: ignore
-from psycopg.rows import namedtuple_row # type: ignore
+from psycopg.rows import namedtuple_row  # type: ignore
-from psycopg_pool import AsyncConnectionPool, PoolTimeout # type: ignore
+from psycopg_pool import AsyncConnectionPool, PoolTimeout  # type: ignore
 
 
 class AGEQueryException(Exception):

lightrag/kg/chroma_impl.py

@@ -11,8 +11,8 @@ import pipmaster as pm
 if not pm.is_installed("chromadb"):
     pm.install("chromadb")
 
-from chromadb import HttpClient, PersistentClient # type: ignore
+from chromadb import HttpClient, PersistentClient  # type: ignore
-from chromadb.config import Settings # type: ignore
+from chromadb.config import Settings  # type: ignore
 
 
 @final
@@ -354,7 +354,9 @@ class ChromaVectorDBStorage(BaseVectorStorage):
                 # Delete all documents
                 self._collection.delete(ids=result["ids"])
 
-            logger.info(f"Process {os.getpid()} drop ChromaDB collection {self.namespace}")
+            logger.info(
+                f"Process {os.getpid()} drop ChromaDB collection {self.namespace}"
+            )
             return {"status": "success", "message": "data dropped"}
         except Exception as e:
             logger.error(f"Error dropping ChromaDB collection {self.namespace}: {e}")

lightrag/kg/gremlin_impl.py

@@ -24,9 +24,9 @@ from ..base import BaseGraphStorage
 if not pm.is_installed("gremlinpython"):
     pm.install("gremlinpython")
 
-from gremlin_python.driver import client, serializer # type: ignore
+from gremlin_python.driver import client, serializer  # type: ignore
-from gremlin_python.driver.aiohttp.transport import AiohttpTransport # type: ignore
+from gremlin_python.driver.aiohttp.transport import AiohttpTransport  # type: ignore
-from gremlin_python.driver.protocol import GremlinServerError # type: ignore
+from gremlin_python.driver.protocol import GremlinServerError  # type: ignore
 
 
 @final

lightrag/kg/json_kv_impl.py

@@ -144,7 +144,7 @@ class JsonKVStorage(BaseKVStorage):
                 self._data.pop(doc_id, None)
             await set_all_update_flags(self.namespace)
 
-    async def drop_cache_by_modes(self, modes: list[str] | None = None) ->  bool:
+    async def drop_cache_by_modes(self, modes: list[str] | None = None) -> bool:
         """Delete specific records from storage by by cache mode
 
         Importance notes for in-memory storage:
@@ -167,7 +167,6 @@ class JsonKVStorage(BaseKVStorage):
         except Exception:
             return False
 
-
     async def drop(self) -> dict[str, str]:
         """Drop all data from storage and clean up resources
            This action will persistent the data to disk immediately.

lightrag/kg/milvus_impl.py

@@ -15,7 +15,7 @@ if not pm.is_installed("pymilvus"):
     pm.install("pymilvus")
 
 import configparser
-from pymilvus import MilvusClient # type: ignore
+from pymilvus import MilvusClient  # type: ignore
 
 config = configparser.ConfigParser()
 config.read("config.ini", "utf-8")
@@ -310,7 +310,9 @@ class MilvusVectorDBStorage(BaseVectorStorage):
                 dimension=self.embedding_func.embedding_dim,
             )
 
-            logger.info(f"Process {os.getpid()} drop Milvus collection {self.namespace}")
+            logger.info(
+                f"Process {os.getpid()} drop Milvus collection {self.namespace}"
+            )
             return {"status": "success", "message": "data dropped"}
         except Exception as e:
             logger.error(f"Error dropping Milvus collection {self.namespace}: {e}")

lightrag/kg/mongo_impl.py

@@ -25,13 +25,13 @@ if not pm.is_installed("pymongo"):
 if not pm.is_installed("motor"):
     pm.install("motor")
 
-from motor.motor_asyncio import ( # type: ignore
+from motor.motor_asyncio import (  # type: ignore
     AsyncIOMotorClient,
     AsyncIOMotorDatabase,
     AsyncIOMotorCollection,
 )
-from pymongo.operations import SearchIndexModel # type: ignore
+from pymongo.operations import SearchIndexModel  # type: ignore
-from pymongo.errors import PyMongoError # type: ignore
+from pymongo.errors import PyMongoError  # type: ignore
 
 config = configparser.ConfigParser()
 config.read("config.ini", "utf-8")
@@ -161,7 +161,9 @@ class MongoKVStorage(BaseKVStorage):
 
         try:
             result = await self._data.delete_many({"_id": {"$in": ids}})
-            logger.info(f"Deleted {result.deleted_count} documents from {self.namespace}")
+            logger.info(
+                f"Deleted {result.deleted_count} documents from {self.namespace}"
+            )
         except PyMongoError as e:
             logger.error(f"Error deleting documents from {self.namespace}: {e}")
 
@@ -197,8 +199,13 @@ class MongoKVStorage(BaseKVStorage):
             result = await self._data.delete_many({})
             deleted_count = result.deleted_count
 
-            logger.info(f"Dropped {deleted_count} documents from doc status {self._collection_name}")
+            logger.info(
-            return {"status": "success", "message": f"{deleted_count} documents dropped"}
+                f"Dropped {deleted_count} documents from doc status {self._collection_name}"
+            )
+            return {
+                "status": "success",
+                "message": f"{deleted_count} documents dropped",
+            }
         except PyMongoError as e:
             logger.error(f"Error dropping doc status {self._collection_name}: {e}")
             return {"status": "error", "message": str(e)}
@@ -293,8 +300,13 @@ class MongoDocStatusStorage(DocStatusStorage):
             result = await self._data.delete_many({})
             deleted_count = result.deleted_count
 
-            logger.info(f"Dropped {deleted_count} documents from doc status {self._collection_name}")
+            logger.info(
-            return {"status": "success", "message": f"{deleted_count} documents dropped"}
+                f"Dropped {deleted_count} documents from doc status {self._collection_name}"
+            )
+            return {
+                "status": "success",
+                "message": f"{deleted_count} documents dropped",
+            }
         except PyMongoError as e:
             logger.error(f"Error dropping doc status {self._collection_name}: {e}")
             return {"status": "error", "message": str(e)}
@@ -919,8 +931,13 @@ class MongoGraphStorage(BaseGraphStorage):
             result = await self.collection.delete_many({})
             deleted_count = result.deleted_count
 
-            logger.info(f"Dropped {deleted_count} documents from graph {self._collection_name}")
+            logger.info(
-            return {"status": "success", "message": f"{deleted_count} documents dropped"}
+                f"Dropped {deleted_count} documents from graph {self._collection_name}"
+            )
+            return {
+                "status": "success",
+                "message": f"{deleted_count} documents dropped",
+            }
         except PyMongoError as e:
             logger.error(f"Error dropping graph {self._collection_name}: {e}")
             return {"status": "error", "message": str(e)}
@@ -1226,8 +1243,13 @@ class MongoVectorDBStorage(BaseVectorStorage):
             # Recreate vector index
             await self.create_vector_index_if_not_exists()
 
-            logger.info(f"Dropped {deleted_count} documents from vector storage {self._collection_name} and recreated vector index")
+            logger.info(
-            return {"status": "success", "message": f"{deleted_count} documents dropped and vector index recreated"}
+                f"Dropped {deleted_count} documents from vector storage {self._collection_name} and recreated vector index"
+            )
+            return {
+                "status": "success",
+                "message": f"{deleted_count} documents dropped and vector index recreated",
+            }
         except PyMongoError as e:
             logger.error(f"Error dropping vector storage {self._collection_name}: {e}")
             return {"status": "error", "message": str(e)}

lightrag/kg/nano_vector_db_impl.py

@@ -339,7 +339,9 @@ class NanoVectorDBStorage(BaseVectorStorage):
                 # Reset own update flag to avoid self-reloading
                 self.storage_updated.value = False
 
-                logger.info(f"Process {os.getpid()} drop {self.namespace}(file:{self._client_file_name})")
+                logger.info(
+                    f"Process {os.getpid()} drop {self.namespace}(file:{self._client_file_name})"
+                )
             return {"status": "success", "message": "data dropped"}
         except Exception as e:
             logger.error(f"Error dropping {self.namespace}: {e}")

lightrag/kg/neo4j_impl.py

@@ -1046,7 +1046,9 @@ class Neo4JStorage(BaseGraphStorage):
                 result = await session.run(query)
                 await result.consume()  # Ensure result is fully consumed
 
-                logger.info(f"Process {os.getpid()} drop Neo4j database {self._DATABASE}")
+                logger.info(
+                    f"Process {os.getpid()} drop Neo4j database {self._DATABASE}"
+                )
                 return {"status": "success", "message": "data dropped"}
         except Exception as e:
             logger.error(f"Error dropping Neo4j database {self._DATABASE}: {e}")

lightrag/kg/networkx_impl.py

@@ -479,7 +479,9 @@ class NetworkXStorage(BaseGraphStorage):
                 await set_all_update_flags(self.namespace)
                 # Reset own update flag to avoid self-reloading
                 self.storage_updated.value = False
-                logger.info(f"Process {os.getpid()} drop graph {self.namespace} (file:{self._graphml_xml_file})")
+                logger.info(
+                    f"Process {os.getpid()} drop graph {self.namespace} (file:{self._graphml_xml_file})"
+                )
             return {"status": "success", "message": "data dropped"}
         except Exception as e:
             logger.error(f"Error dropping graph {self.namespace}: {e}")

lightrag/kg/oracle_impl.py

@@ -27,7 +27,7 @@ if not pm.is_installed("oracledb"):
     pm.install("oracledb")
 
 from graspologic import embed
-import oracledb # type: ignore
+import oracledb  # type: ignore
 
 
 class OracleDB:
@@ -411,7 +411,9 @@ class OracleKVStorage(BaseKVStorage):
             delete_sql = f"DELETE FROM {table_name} WHERE workspace=:workspace AND id IN ({ids_list})"
 
             await self.db.execute(delete_sql, {"workspace": self.db.workspace})
-            logger.info(f"Successfully deleted {len(ids)} records from {self.namespace}")
+            logger.info(
+                f"Successfully deleted {len(ids)} records from {self.namespace}"
+            )
         except Exception as e:
             logger.error(f"Error deleting records from {self.namespace}: {e}")
 
@@ -455,7 +457,10 @@ class OracleKVStorage(BaseKVStorage):
         try:
             table_name = namespace_to_table_name(self.namespace)
             if not table_name:
-                return {"status": "error", "message": f"Unknown namespace: {self.namespace}"}
+                return {
+                    "status": "error",
+                    "message": f"Unknown namespace: {self.namespace}",
+                }
 
             drop_sql = SQL_TEMPLATES["drop_specifiy_table_workspace"].format(
                 table_name=table_name
@@ -683,7 +688,10 @@ class OracleVectorDBStorage(BaseVectorStorage):
         try:
             table_name = namespace_to_table_name(self.namespace)
             if not table_name:
-                return {"status": "error", "message": f"Unknown namespace: {self.namespace}"}
+                return {
+                    "status": "error",
+                    "message": f"Unknown namespace: {self.namespace}",
+                }
 
             drop_sql = SQL_TEMPLATES["drop_specifiy_table_workspace"].format(
                 table_name=table_name
@@ -1025,10 +1033,14 @@ class OracleGraphStorage(BaseGraphStorage):
         """Drop the storage"""
         try:
             # 使用图形查询删除所有节点和关系
-            delete_edges_sql = """DELETE FROM LIGHTRAG_GRAPH_EDGES WHERE workspace=:workspace"""
+            delete_edges_sql = (
+                """DELETE FROM LIGHTRAG_GRAPH_EDGES WHERE workspace=:workspace"""
+            )
             await self.db.execute(delete_edges_sql, {"workspace": self.db.workspace})
 
-            delete_nodes_sql = """DELETE FROM LIGHTRAG_GRAPH_NODES WHERE workspace=:workspace"""
+            delete_nodes_sql = (
+                """DELETE FROM LIGHTRAG_GRAPH_NODES WHERE workspace=:workspace"""
+            )
             await self.db.execute(delete_nodes_sql, {"workspace": self.db.workspace})
 
             return {"status": "success", "message": "graph data dropped"}

lightrag/kg/postgres_impl.py

@@ -398,8 +398,12 @@ class PGKVStorage(BaseKVStorage):
         delete_sql = f"DELETE FROM {table_name} WHERE workspace=$1 AND id = ANY($2)"
 
         try:
-            await self.db.execute(delete_sql, {"workspace": self.db.workspace, "ids": ids})
+            await self.db.execute(
-            logger.debug(f"Successfully deleted {len(ids)} records from {self.namespace}")
+                delete_sql, {"workspace": self.db.workspace, "ids": ids}
+            )
+            logger.debug(
+                f"Successfully deleted {len(ids)} records from {self.namespace}"
+            )
         except Exception as e:
             logger.error(f"Error while deleting records from {self.namespace}: {e}")
 
@@ -427,10 +431,7 @@ class PGKVStorage(BaseKVStorage):
             DELETE FROM {table_name}
             WHERE workspace = $1 AND mode = ANY($2)
             """
-            params = {
+            params = {"workspace": self.db.workspace, "modes": modes}
-                "workspace": self.db.workspace,
-                "modes": modes
-            }
 
             logger.info(f"Deleting cache by modes: {modes}")
             await self.db.execute(sql, params)
@@ -444,7 +445,10 @@ class PGKVStorage(BaseKVStorage):
         try:
             table_name = namespace_to_table_name(self.namespace)
             if not table_name:
-                return {"status": "error", "message": f"Unknown namespace: {self.namespace}"}
+                return {
+                    "status": "error",
+                    "message": f"Unknown namespace: {self.namespace}",
+                }
 
             drop_sql = SQL_TEMPLATES["drop_specifiy_table_workspace"].format(
                 table_name=table_name
@@ -622,7 +626,9 @@ class PGVectorStorage(BaseVectorStorage):
         delete_sql = f"DELETE FROM {table_name} WHERE workspace=$1 AND id = ANY($2)"
 
         try:
-            await self.db.execute(delete_sql, {"workspace": self.db.workspace, "ids": ids})
+            await self.db.execute(
+                delete_sql, {"workspace": self.db.workspace, "ids": ids}
+            )
             logger.debug(
                 f"Successfully deleted {len(ids)} vectors from {self.namespace}"
             )
@@ -759,7 +765,10 @@ class PGVectorStorage(BaseVectorStorage):
         try:
             table_name = namespace_to_table_name(self.namespace)
             if not table_name:
-                return {"status": "error", "message": f"Unknown namespace: {self.namespace}"}
+                return {
+                    "status": "error",
+                    "message": f"Unknown namespace: {self.namespace}",
+                }
 
             drop_sql = SQL_TEMPLATES["drop_specifiy_table_workspace"].format(
                 table_name=table_name
@@ -930,7 +939,10 @@ class PGDocStatusStorage(DocStatusStorage):
         try:
             table_name = namespace_to_table_name(self.namespace)
             if not table_name:
-                return {"status": "error", "message": f"Unknown namespace: {self.namespace}"}
+                return {
+                    "status": "error",
+                    "message": f"Unknown namespace: {self.namespace}",
+                }
 
             drop_sql = SQL_TEMPLATES["drop_specifiy_table_workspace"].format(
                 table_name=table_name

lightrag/kg/qdrant_impl.py

@@ -13,11 +13,12 @@ import pipmaster as pm
 if not pm.is_installed("qdrant-client"):
     pm.install("qdrant-client")
 
-from qdrant_client import QdrantClient, models # type: ignore
+from qdrant_client import QdrantClient, models  # type: ignore
 
 config = configparser.ConfigParser()
 config.read("config.ini", "utf-8")
 
+
 def compute_mdhash_id_for_qdrant(
     content: str, prefix: str = "", style: str = "simple"
 ) -> str:
@@ -349,11 +350,14 @@ class QdrantVectorDBStorage(BaseVectorStorage):
                 self._client,
                 self.namespace,
                 vectors_config=models.VectorParams(
-                    size=self.embedding_func.embedding_dim, distance=models.Distance.COSINE
+                    size=self.embedding_func.embedding_dim,
+                    distance=models.Distance.COSINE,
                 ),
             )
 
-            logger.info(f"Process {os.getpid()} drop Qdrant collection {self.namespace}")
+            logger.info(
+                f"Process {os.getpid()} drop Qdrant collection {self.namespace}"
+            )
             return {"status": "success", "message": "data dropped"}
         except Exception as e:
             logger.error(f"Error dropping Qdrant collection {self.namespace}: {e}")

lightrag/kg/redis_impl.py

@@ -8,7 +8,7 @@ if not pm.is_installed("redis"):
     pm.install("redis")
 
 # aioredis is a depricated library, replaced with redis
-from redis.asyncio import Redis # type: ignore
+from redis.asyncio import Redis  # type: ignore
 from lightrag.utils import logger
 from lightrag.base import BaseKVStorage
 import json
@@ -84,7 +84,7 @@ class RedisKVStorage(BaseKVStorage):
             f"Deleted {deleted_count} of {len(ids)} entries from {self.namespace}"
         )
 
-    async def drop_cache_by_modes(self, modes: list[str] | None = None) ->  bool:
+    async def drop_cache_by_modes(self, modes: list[str] | None = None) -> bool:
         """Delete specific records from storage by by cache mode
 
         Importance notes for Redis storage:

lightrag/kg/tidb_impl.py

@@ -20,7 +20,7 @@ if not pm.is_installed("pymysql"):
 if not pm.is_installed("sqlalchemy"):
     pm.install("sqlalchemy")
 
-from sqlalchemy import create_engine, text # type: ignore
+from sqlalchemy import create_engine, text  # type: ignore
 
 
 class TiDB:
@@ -299,7 +299,9 @@ class TiDBKVStorage(BaseKVStorage):
             delete_sql = f"DELETE FROM {table_name} WHERE workspace = :workspace AND {id_field} IN ({ids_list})"
 
             await self.db.execute(delete_sql, {"workspace": self.db.workspace})
-            logger.info(f"Successfully deleted {len(ids)} records from {self.namespace}")
+            logger.info(
+                f"Successfully deleted {len(ids)} records from {self.namespace}"
+            )
         except Exception as e:
             logger.error(f"Error deleting records from {self.namespace}: {e}")
 
@@ -343,7 +345,10 @@ class TiDBKVStorage(BaseKVStorage):
         try:
             table_name = namespace_to_table_name(self.namespace)
             if not table_name:
-                return {"status": "error", "message": f"Unknown namespace: {self.namespace}"}
+                return {
+                    "status": "error",
+                    "message": f"Unknown namespace: {self.namespace}",
+                }
 
             drop_sql = SQL_TEMPLATES["drop_specifiy_table_workspace"].format(
                 table_name=table_name
@@ -502,7 +507,9 @@ class TiDBVectorDBStorage(BaseVectorStorage):
 
         try:
             await self.db.execute(delete_sql, {"workspace": self.db.workspace})
-            logger.debug(f"Successfully deleted {len(ids)} vectors from {self.namespace}")
+            logger.debug(
+                f"Successfully deleted {len(ids)} vectors from {self.namespace}"
+            )
         except Exception as e:
             logger.error(f"Error while deleting vectors from {self.namespace}: {e}")
 
@@ -551,7 +558,10 @@ class TiDBVectorDBStorage(BaseVectorStorage):
         try:
             table_name = namespace_to_table_name(self.namespace)
             if not table_name:
-                return {"status": "error", "message": f"Unknown namespace: {self.namespace}"}
+                return {
+                    "status": "error",
+                    "message": f"Unknown namespace: {self.namespace}",
+                }
 
             drop_sql = SQL_TEMPLATES["drop_specifiy_table_workspace"].format(
                 table_name=table_name