Refactor vector store component class names for consistency

src/backend/base/langflow/components/vectorsearch/AstraDBSearch.py

@@ -1,6 +1,6 @@
 from typing import List, Optional
 
-from langflow.components.vectorstores.AstraDB import AstraDBVectorStoreComponent
+from langflow.components.vectorstores.AstraDB import AstraVectorStoreComponent
 from langflow.components.vectorstores.base.model import LCVectorStoreComponent
 from langflow.field_typing import Embeddings, Text
 from langflow.schema import Data
@@ -120,7 +120,7 @@ class AstraDBSearchComponent(LCVectorStoreComponent):
         metadata_indexing_exclude: Optional[List[str]] = None,
         collection_indexing_policy: Optional[dict] = None,
     ) -> List[Data]:
-        vector_store = AstraDBVectorStoreComponent().build(
+        vector_store = AstraVectorStoreComponent().build(
             embedding=embedding,
             collection_name=collection_name,
             token=token,

src/backend/base/langflow/components/vectorsearch/CouchbaseSearch.py

@@ -1,7 +1,7 @@
 from typing import List
 
 from langflow.components.vectorstores.base.model import LCVectorStoreComponent
-from langflow.components.vectorstores.Couchbase import CouchbaseComponent
+from langflow.components.vectorstores.Couchbase import CouchbaseVectorStoreComponent
 from langflow.field_typing import Embeddings, Text
 from langflow.schema import Data
 
@@ -52,7 +52,7 @@ class CouchbaseSearchComponent(LCVectorStoreComponent):
         couchbase_username: str = "",
         couchbase_password: str = "",
     ) -> List[Data]:
-        vector_store = CouchbaseComponent().build(
+        vector_store = CouchbaseVectorStoreComponent().build(
             couchbase_connection_string=couchbase_connection_string,
             couchbase_username=couchbase_username,
             couchbase_password=couchbase_password,

src/backend/base/langflow/components/vectorsearch/MongoDBAtlasVectorSearch.py

@@ -1,7 +1,7 @@
 from typing import List, Optional
 
 from langflow.components.vectorstores.base.model import LCVectorStoreComponent
-from langflow.components.vectorstores.MongoDBAtlasVector import MongoDBAtlasComponent
+from langflow.components.vectorstores.MongoDBAtlasVector import MongoVectorStoreComponent
 from langflow.field_typing import Embeddings, NestedDict, Text
 from langflow.schema import Data
 
@@ -43,7 +43,7 @@ class MongoDBAtlasSearchComponent(LCVectorStoreComponent):
         search_kwargs: Optional[NestedDict] = None,
     ) -> List[Data]:
         search_kwargs = search_kwargs or {}
-        vector_store = MongoDBAtlasComponent().build(
+        vector_store = MongoVectorStoreComponent().build(
             mongodb_atlas_cluster_uri=mongodb_atlas_cluster_uri,
             collection_name=collection_name,
             db_name=db_name,

src/backend/base/langflow/components/vectorsearch/PineconeSearch.py

@@ -3,13 +3,13 @@ from typing import List, Optional
 from langchain_pinecone._utilities import DistanceStrategy
 
 from langflow.components.vectorstores.base.model import LCVectorStoreComponent
-from langflow.components.vectorstores.Pinecone import PineconeComponent
+from langflow.components.vectorstores.Pinecone import PineconeVectorStoreComponent
 from langflow.field_typing import Embeddings, Text
 from langflow.field_typing.constants import NestedDict
 from langflow.schema import Data
 
 
-class PineconeSearchComponent(PineconeComponent, LCVectorStoreComponent):
+class PineconeSearchComponent(PineconeVectorStoreComponent, LCVectorStoreComponent):
     display_name = "Pinecone Search"
     description = "Search a Pinecone Vector Store for similar documents."
     icon = "Pinecone"

src/backend/base/langflow/components/vectorsearch/QdrantSearch.py

@@ -1,12 +1,12 @@
 from typing import List, Optional
 
 from langflow.components.vectorstores.base.model import LCVectorStoreComponent
-from langflow.components.vectorstores.Qdrant import QdrantComponent
+from langflow.components.vectorstores.Qdrant import QdrantVectorStoreComponent
 from langflow.field_typing import Embeddings, NestedDict, Text
 from langflow.schema import Data
 
 
-class QdrantSearchComponent(QdrantComponent, LCVectorStoreComponent):
+class QdrantSearchComponent(QdrantVectorStoreComponent, LCVectorStoreComponent):
     display_name = "Qdrant Search"
     description = "Construct Qdrant wrapper from a list of texts."
     icon = "Qdrant"

src/backend/base/langflow/components/vectorsearch/RedisSearch.py

@@ -3,12 +3,12 @@ from typing import List, Optional
 from langchain_core.embeddings import Embeddings
 
 from langflow.components.vectorstores.base.model import LCVectorStoreComponent
-from langflow.components.vectorstores.Redis import RedisComponent
+from langflow.components.vectorstores.Redis import RedisVectorStoreComponent
 from langflow.field_typing import Text
 from langflow.schema import Data
 
 
-class RedisSearchComponent(RedisComponent, LCVectorStoreComponent):
+class RedisSearchComponent(RedisVectorStoreComponent, LCVectorStoreComponent):
     """
     A custom component for implementing a Vector Store using Redis.
     """

src/backend/base/langflow/components/vectorsearch/VectaraSearch.py

@@ -3,12 +3,12 @@ from typing import List
 from langchain_community.vectorstores.vectara import Vectara
 
 from langflow.components.vectorstores.base.model import LCVectorStoreComponent
-from langflow.components.vectorstores.Vectara import VectaraComponent
+from langflow.components.vectorstores.Vectara import VectaraVectorStoreComponent
 from langflow.field_typing import Text
 from langflow.schema import Data
 
 
-class VectaraSearchComponent(VectaraComponent, LCVectorStoreComponent):
+class VectaraSearchComponent(VectaraVectorStoreComponent, LCVectorStoreComponent):
     display_name: str = "Vectara Search"
     description: str = "Search a Vectara Vector Store for similar documents."
     documentation = "https://python.langchain.com/docs/integrations/vectorstores/vectara"

src/backend/base/langflow/components/vectorsearch/pgvectorSearch.py

@@ -3,12 +3,12 @@ from typing import List
 from langchain_core.embeddings import Embeddings
 
 from langflow.components.vectorstores.base.model import LCVectorStoreComponent
-from langflow.components.vectorstores.pgvector import PGVectorComponent
+from langflow.components.vectorstores.pgvector import PGVectorStoreComponent
 from langflow.field_typing import Text
 from langflow.schema import Data
 
 
-class PGVectorSearchComponent(PGVectorComponent, LCVectorStoreComponent):
+class PGVectorSearchComponent(PGVectorStoreComponent, LCVectorStoreComponent):
     display_name: str = "PGVector Search"
     description: str = "Search a PGVector Store for similar documents."
     documentation = "https://python.langchain.com/docs/integrations/vectorstores/pgvector"

src/backend/base/langflow/components/vectorstores/AstraDB.py

@@ -14,7 +14,7 @@ from langflow.field_typing import Embeddings
 
 from loguru import logger
 
-class AstraDBComponent(Component):
+class AstraVectorStoreComponent(Component):
     display_name: str = "Astra DB Vector Store"
     description: str = "Implementation of Vector Store using Astra DB with search capabilities"
     documentation: str = "https://python.langchain.com/docs/integrations/vectorstores/astradb"

src/backend/base/langflow/components/vectorstores/FAISS.py

@@ -15,7 +15,7 @@ from langflow.helpers.data import docs_to_data
 from loguru import logger
 
 
-class FAISSVectorStoreComponent(Component):
+class FaissVectorStoreComponent(Component):
     """
     FAISS Vector Store with search capabilities
     """

src/backend/base/langflow/components/vectorstores/MongoDBAtlasVector.py

@@ -11,7 +11,7 @@ from langflow.inputs import BoolInput, IntInput, StrInput, HandleInput
 from langflow.template import Output
 from langflow.helpers.data import docs_to_data
 
-class MongoDBAtlasComponent(Component):
+class MongoVectorStoreComponent(Component):
     display_name = "MongoDB Atlas"
     description = "MongoDB Atlas Vector Store with search capabilities"
     documentation = "https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/mongodb_atlas"

src/backend/base/langflow/components/vectorstores/Redis.py

@@ -9,7 +9,7 @@ from langflow.custom import CustomComponent
 from langflow.schema import Data
 
 
-class RedisComponent(CustomComponent):
+class RedisVectorStoreComponent(CustomComponent):
     """
     A custom component for implementing a Vector Store using Redis.
     """

src/backend/base/langflow/components/vectorstores/pgvector.py

@@ -11,7 +11,7 @@ from langflow.inputs import BoolInput, IntInput, StrInput, HandleInput
 from langflow.template import Output
 from langflow.helpers.data import docs_to_data
 
-class PGVectorComponent(Component):
+class PGVectorStoreComponent(Component):
     display_name = "PGVector"
     description = "PGVector Vector Store with search capabilities"
     documentation = "https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/pgvector"