chore: format

backend/open_webui/apps/retrieval/vector/dbs/chroma.py

@@ -110,9 +110,8 @@ class ChromaClient:
     def insert(self, collection_name: str, items: list[VectorItem]):
         # Insert the items into the collection, if the collection does not exist, it will be created.
         collection = self.client.get_or_create_collection(
-            name=collection_name,
-            metadata={"hnsw:space": "cosine"}
-            )
+            name=collection_name, metadata={"hnsw:space": "cosine"}
+        )
 
         ids = [item["id"] for item in items]
         documents = [item["text"] for item in items]
@@ -131,9 +130,8 @@ class ChromaClient:
     def upsert(self, collection_name: str, items: list[VectorItem]):
         # Update the items in the collection, if the items are not present, insert them. If the collection does not exist, it will be created.
         collection = self.client.get_or_create_collection(
-            name=collection_name,
-            metadata={"hnsw:space": "cosine"}
-            )
+            name=collection_name, metadata={"hnsw:space": "cosine"}
+        )
 
         ids = [item["id"] for item in items]
         documents = [item["text"] for item in items]

backend/open_webui/apps/retrieval/vector/dbs/qdrant.py

@@ -9,6 +9,7 @@ from open_webui.config import QDRANT_URI
 
 NO_LIMIT = 999999999
 
+
 class QdrantClient:
     def __init__(self):
         self.collection_prefix = "open-webui"
@@ -38,15 +39,15 @@ class QdrantClient:
         collection_name_with_prefix = f"{self.collection_prefix}_{collection_name}"
         self.client.create_collection(
             collection_name=collection_name_with_prefix,
-            vectors_config=models.VectorParams(size=dimension, distance=models.Distance.COSINE),
+            vectors_config=models.VectorParams(
+                size=dimension, distance=models.Distance.COSINE
+            ),
         )
 
         print(f"collection {collection_name_with_prefix} successfully created!")
 
     def _create_collection_if_not_exists(self, collection_name, dimension):
-        if not self.has_collection(
-                collection_name=collection_name
-        ):
+        if not self.has_collection(collection_name=collection_name):
             self._create_collection(
                 collection_name=collection_name, dimension=dimension
             )
@@ -56,22 +57,23 @@ class QdrantClient:
             PointStruct(
                 id=item["id"],
                 vector=item["vector"],
-                payload={
-                    "text": item["text"],
-                    "metadata": item["metadata"]
-                },
+                payload={"text": item["text"], "metadata": item["metadata"]},
             )
             for item in items
         ]
 
     def has_collection(self, collection_name: str) -> bool:
-        return self.client.collection_exists(f"{self.collection_prefix}_{collection_name}")
+        return self.client.collection_exists(
+            f"{self.collection_prefix}_{collection_name}"
+        )
 
     def delete_collection(self, collection_name: str):
-        return self.client.delete_collection(collection_name=f"{self.collection_prefix}_{collection_name}")
+        return self.client.delete_collection(
+            collection_name=f"{self.collection_prefix}_{collection_name}"
+        )
 
     def search(
-            self, collection_name: str, vectors: list[list[float | int]], limit: int
+        self, collection_name: str, vectors: list[list[float | int]], limit: int
     ) -> Optional[SearchResult]:
         # Search for the nearest neighbor items based on the vectors and return 'limit' number of results.
         if limit is None:
@@ -87,7 +89,7 @@ class QdrantClient:
             ids=get_result.ids,
             documents=get_result.documents,
             metadatas=get_result.metadatas,
-            distances=[[point.score for point in query_response.points]]
+            distances=[[point.score for point in query_response.points]],
         )
 
     def query(self, collection_name: str, filter: dict, limit: Optional[int] = None):
@@ -101,7 +103,10 @@ class QdrantClient:
             field_conditions = []
             for key, value in filter.items():
                 field_conditions.append(
-                    models.FieldCondition(key=f"metadata.{key}", match=models.MatchValue(value=value)))
+                    models.FieldCondition(
+                        key=f"metadata.{key}", match=models.MatchValue(value=value)
+                    )
+                )
 
             points = self.client.query_points(
                 collection_name=f"{self.collection_prefix}_{collection_name}",
@@ -117,7 +122,7 @@ class QdrantClient:
         # Get all the items in the collection.
         points = self.client.query_points(
             collection_name=f"{self.collection_prefix}_{collection_name}",
-            limit=NO_LIMIT  # otherwise qdrant would set limit to 10!
+            limit=NO_LIMIT,  # otherwise qdrant would set limit to 10!
         )
         return self._result_to_get_result(points.points)
 
@@ -134,10 +139,10 @@ class QdrantClient:
         return self.client.upsert(f"{self.collection_prefix}_{collection_name}", points)
 
     def delete(
-            self,
-            collection_name: str,
-            ids: Optional[list[str]] = None,
-            filter: Optional[dict] = None,
+        self,
+        collection_name: str,
+        ids: Optional[list[str]] = None,
+        filter: Optional[dict] = None,
     ):
         # Delete the items from the collection based on the ids.
         field_conditions = []
@@ -162,9 +167,7 @@ class QdrantClient:
         return self.client.delete(
             collection_name=f"{self.collection_prefix}_{collection_name}",
             points_selector=models.FilterSelector(
-                filter=models.Filter(
-                    must=field_conditions
-                )
+                filter=models.Filter(must=field_conditions)
             ),
         )