lint

backend/modules/vector_db/chroma.py

@@ -8,7 +8,10 @@
 from langchain.embeddings.base import Embeddings
 from langchain_community.vectorstores import Chroma
 
-from backend.constants import DATA_POINT_FQN_METADATA_KEY, DEFAULT_BATCH_SIZE_FOR_VECTOR_STORE
+from backend.constants import (
+    DATA_POINT_FQN_METADATA_KEY,
+    DEFAULT_BATCH_SIZE_FOR_VECTOR_STORE,
+)
 from backend.logger import logger
 from backend.modules.vector_db.base import BaseVectorDB
 from backend.types import ChromaVectorDBConfig, DataPointVector
@@ -104,7 +107,6 @@ def upsert_documents(
             for doc in documents
             if doc.metadata.get(DATA_POINT_FQN_METADATA_KEY)
         ]
-
 
     def delete_documents(self, collection_name: str, document_ids: List[str]):
         # Fetch the collection

backend/modules/vector_db/qdrant.py

@@ -154,18 +154,16 @@ def upsert_documents(
         )
 
         # Delete old documents
-        
+
         # If there are no record ids to be upserted, return
         if not len(record_ids_to_be_upserted):
             return
-        
+
         logger.debug(
             f"[Qdrant] Deleting {len(documents)} outdated documents from collection {collection_name}"
         )
         for i in range(0, len(record_ids_to_be_upserted), BATCH_SIZE):
-            record_ids_to_be_processed = record_ids_to_be_upserted[
-                i : i + BATCH_SIZE
-            ]
+            record_ids_to_be_processed = record_ids_to_be_upserted[i : i + BATCH_SIZE]
             self.qdrant_client.delete(
                 collection_name=collection_name,
                 points_selector=models.PointIdsList(
@@ -420,4 +418,3 @@ def list_document_vector_points(
             f"[Qdrant] Listing {len(document_vector_points)} document vector points for collection {collection_name}"
         )
         return document_vector_points
-