Fix linting

lightrag/kg/chroma_impl.py

@@ -1,4 +1,3 @@
-import os
 import asyncio
 from dataclasses import dataclass
 from typing import Union
@@ -20,7 +19,9 @@ class ChromaVectorDBStorage(BaseVectorStorage):
             config = self.global_config.get("vector_db_storage_cls_kwargs", {})
             cosine_threshold = config.get("cosine_better_than_threshold")
             if cosine_threshold is None:
-                raise ValueError("cosine_better_than_threshold must be specified in vector_db_storage_cls_kwargs")
+                raise ValueError(
+                    "cosine_better_than_threshold must be specified in vector_db_storage_cls_kwargs"
+                )
             self.cosine_better_than_threshold = cosine_threshold
 
             user_collection_settings = config.get("collection_settings", {})

lightrag/kg/faiss_impl.py

@@ -30,7 +30,9 @@ class FaissVectorDBStorage(BaseVectorStorage):
         config = self.global_config.get("vector_db_storage_cls_kwargs", {})
         cosine_threshold = config.get("cosine_better_than_threshold")
         if cosine_threshold is None:
-            raise ValueError("cosine_better_than_threshold must be specified in vector_db_storage_cls_kwargs")
+            raise ValueError(
+                "cosine_better_than_threshold must be specified in vector_db_storage_cls_kwargs"
+            )
         self.cosine_better_than_threshold = cosine_threshold
 
         # Where to save index file if you want persistent storage

lightrag/kg/milvus_impl.py

@@ -35,7 +35,9 @@ class MilvusVectorDBStorge(BaseVectorStorage):
         config = self.global_config.get("vector_db_storage_cls_kwargs", {})
         cosine_threshold = config.get("cosine_better_than_threshold")
         if cosine_threshold is None:
-            raise ValueError("cosine_better_than_threshold must be specified in vector_db_storage_cls_kwargs")
+            raise ValueError(
+                "cosine_better_than_threshold must be specified in vector_db_storage_cls_kwargs"
+            )
         self.cosine_better_than_threshold = cosine_threshold
 
         self._client = MilvusClient(
@@ -111,7 +113,10 @@ class MilvusVectorDBStorge(BaseVectorStorage):
             data=embedding,
             limit=top_k,
             output_fields=list(self.meta_fields),
-            search_params={"metric_type": "COSINE", "params": {"radius": self.cosine_better_than_threshold}},
+            search_params={
+                "metric_type": "COSINE",
+                "params": {"radius": self.cosine_better_than_threshold},
+            },
         )
         print(results)
         return [

lightrag/kg/nano_vector_db_impl.py

@@ -82,7 +82,9 @@ class NanoVectorDBStorage(BaseVectorStorage):
         config = self.global_config.get("vector_db_storage_cls_kwargs", {})
         cosine_threshold = config.get("cosine_better_than_threshold")
         if cosine_threshold is None:
-            raise ValueError("cosine_better_than_threshold must be specified in vector_db_storage_cls_kwargs")
+            raise ValueError(
+                "cosine_better_than_threshold must be specified in vector_db_storage_cls_kwargs"
+            )
         self.cosine_better_than_threshold = cosine_threshold
 
         self._client_file_name = os.path.join(

lightrag/kg/oracle_impl.py

@@ -1,6 +1,5 @@
 import array
 import asyncio
-import os
 
 # import html
 # import os
@@ -326,7 +325,9 @@ class OracleVectorDBStorage(BaseVectorStorage):
         config = self.global_config.get("vector_db_storage_cls_kwargs", {})
         cosine_threshold = config.get("cosine_better_than_threshold")
         if cosine_threshold is None:
-            raise ValueError("cosine_better_than_threshold must be specified in vector_db_storage_cls_kwargs")
+            raise ValueError(
+                "cosine_better_than_threshold must be specified in vector_db_storage_cls_kwargs"
+            )
         self.cosine_better_than_threshold = cosine_threshold
 
     async def upsert(self, data: dict[str, dict]):

lightrag/kg/postgres_impl.py

@@ -306,7 +306,9 @@ class PGVectorStorage(BaseVectorStorage):
         config = self.global_config.get("vector_db_storage_cls_kwargs", {})
         cosine_threshold = config.get("cosine_better_than_threshold")
         if cosine_threshold is None:
-            raise ValueError("cosine_better_than_threshold must be specified in vector_db_storage_cls_kwargs")
+            raise ValueError(
+                "cosine_better_than_threshold must be specified in vector_db_storage_cls_kwargs"
+            )
         self.cosine_better_than_threshold = cosine_threshold
 
     def _upsert_chunks(self, item: dict):
@@ -424,9 +426,7 @@ class PGDocStatusStorage(DocStatusStorage):
     async def filter_keys(self, data: set[str]) -> set[str]:
         """Return keys that don't exist in storage"""
         keys = ",".join([f"'{_id}'" for _id in data])
-        sql = (
-            f"SELECT id FROM LIGHTRAG_DOC_STATUS WHERE workspace='{self.db.workspace}' AND id IN ({keys})"
-        )
+        sql = f"SELECT id FROM LIGHTRAG_DOC_STATUS WHERE workspace='{self.db.workspace}' AND id IN ({keys})"
         result = await self.db.query(sql, multirows=True)
         # The result is like [{'id': 'id1'}, {'id': 'id2'}, ...].
         if result is None:

lightrag/kg/qdrant_impl.py

@@ -64,7 +64,9 @@ class QdrantVectorDBStorage(BaseVectorStorage):
         config = self.global_config.get("vector_db_storage_cls_kwargs", {})
         cosine_threshold = config.get("cosine_better_than_threshold")
         if cosine_threshold is None:
-            raise ValueError("cosine_better_than_threshold must be specified in vector_db_storage_cls_kwargs")
+            raise ValueError(
+                "cosine_better_than_threshold must be specified in vector_db_storage_cls_kwargs"
+            )
         self.cosine_better_than_threshold = cosine_threshold
 
         self._client = QdrantClient(
@@ -140,5 +142,9 @@ class QdrantVectorDBStorage(BaseVectorStorage):
         )
         logger.debug(f"query result: {results}")
         # 添加余弦相似度过滤
-        filtered_results = [dp for dp in results if dp.score >= self.cosine_better_than_threshold]
-        return [{**dp.payload, "id": dp.id, "distance": dp.score} for dp in filtered_results]
+        filtered_results = [
+            dp for dp in results if dp.score >= self.cosine_better_than_threshold
+        ]
+        return [
+            {**dp.payload, "id": dp.id, "distance": dp.score} for dp in filtered_results
+        ]

lightrag/kg/tidb_impl.py

@@ -222,7 +222,9 @@ class TiDBVectorDBStorage(BaseVectorStorage):
         config = self.global_config.get("vector_db_storage_cls_kwargs", {})
         cosine_threshold = config.get("cosine_better_than_threshold")
         if cosine_threshold is None:
-            raise ValueError("cosine_better_than_threshold must be specified in vector_db_storage_cls_kwargs")
+            raise ValueError(
+                "cosine_better_than_threshold must be specified in vector_db_storage_cls_kwargs"
+            )
         self.cosine_better_than_threshold = cosine_threshold
 
     async def query(self, query: str, top_k: int) -> list[dict]: