diff --git a/backend/open_webui/retrieval/utils.py b/backend/open_webui/retrieval/utils.py
index a3974f15b..8b187dbe0 100644
--- a/backend/open_webui/retrieval/utils.py
+++ b/backend/open_webui/retrieval/utils.py
@@ -174,9 +174,7 @@ def merge_get_results(get_results: list[dict]) -> dict:
     return result
 
 
-def merge_and_sort_query_results(
-    query_results: list[dict], k: int
-) -> dict:
+def merge_and_sort_query_results(query_results: list[dict], k: int) -> dict:
     # Initialize lists to store combined data
     combined = dict()  # To store documents with unique document hashes
 
diff --git a/backend/open_webui/retrieval/vector/dbs/chroma.py b/backend/open_webui/retrieval/vector/dbs/chroma.py
index 3543cd545..fc91f14a5 100755
--- a/backend/open_webui/retrieval/vector/dbs/chroma.py
+++ b/backend/open_webui/retrieval/vector/dbs/chroma.py
@@ -79,7 +79,7 @@ class ChromaClient:
                 # https://docs.trychroma.com/docs/collections/configure cosine equation
                 distances: list = result["distances"][0]
                 distances = [2 - dist for dist in distances]
-                distances = [[dist/2 for dist in distances]]
+                distances = [[dist / 2 for dist in distances]]
 
                 return SearchResult(
                     **{
diff --git a/backend/open_webui/retrieval/vector/dbs/milvus.py b/backend/open_webui/retrieval/vector/dbs/milvus.py
index 4d0da57ac..26b4dd5ed 100644
--- a/backend/open_webui/retrieval/vector/dbs/milvus.py
+++ b/backend/open_webui/retrieval/vector/dbs/milvus.py
@@ -66,7 +66,7 @@ class MilvusClient:
                 _ids.append(item.get("id"))
                 # normalize milvus score from [-1, 1] to [0, 1] range
                 # https://milvus.io/docs/de/metric.md
-                _dist = (item.get("distance") + 1.0)/2.0
+                _dist = (item.get("distance") + 1.0) / 2.0
                 _distances.append(_dist)
                 _documents.append(item.get("entity", {}).get("data", {}).get("text"))
                 _metadatas.append(item.get("entity", {}).get("metadata"))
diff --git a/backend/open_webui/retrieval/vector/dbs/pgvector.py b/backend/open_webui/retrieval/vector/dbs/pgvector.py
index 0ddf48d1e..c38dbb036 100644
--- a/backend/open_webui/retrieval/vector/dbs/pgvector.py
+++ b/backend/open_webui/retrieval/vector/dbs/pgvector.py
@@ -280,7 +280,7 @@ class PgvectorClient:
                 ids[qid].append(row.id)
                 # normalize and re-orders pgvec distance from [2, 0] to [0, 1] score range
                 # https://github.com/pgvector/pgvector?tab=readme-ov-file#querying
-                distances[qid].append((2.0 - row.distance)/2.0)
+                distances[qid].append((2.0 - row.distance) / 2.0)
                 documents[qid].append(row.text)
                 metadatas[qid].append(row.vmetadata)
 
diff --git a/backend/open_webui/retrieval/vector/dbs/qdrant.py b/backend/open_webui/retrieval/vector/dbs/qdrant.py
index 070bf3de5..be0df6c6a 100644
--- a/backend/open_webui/retrieval/vector/dbs/qdrant.py
+++ b/backend/open_webui/retrieval/vector/dbs/qdrant.py
@@ -100,7 +100,7 @@ class QdrantClient:
             documents=get_result.documents,
             metadatas=get_result.metadatas,
             # qdrant distance is [-1, 1], normalize to [0, 1]
-            distances=[[(point.score + 1.0)/2.0 for point in query_response.points]],
+            distances=[[(point.score + 1.0) / 2.0 for point in query_response.points]],
         )
 
     def query(self, collection_name: str, filter: dict, limit: Optional[int] = None):