Vector Stores
VectorStoresResource
Methods
List all vector stores for the current account with pagination.
Returns a paginated list of vector stores owned by the authenticated account.
Create a new vector store.
The vector store will be scoped to the authenticated account. The name must be unique within the account.
Args: request: Vector store creation parameters including name, dimensions, and optional model vector_store_use_case: Injected vector store use case
Returns: The created vector store details
Get a vector store by name.
Args: vector_store_name: The unique name of the vector store within the account vector_store_use_case: Injected vector store use case
Returns: The vector store details
Configure the settings of a vector store.
Currently only supports updating indexed_metadata_fields. The name, embedding_dimensions, and embedding_model are immutable after creation.
Args: request: Configuration update with indexed_metadata_fields vector_store_name: The unique name of the vector store within the account vector_store_use_case: Injected vector store use case
Returns: The updated vector store details
Delete (drop) a vector store by name.
This is a hard delete operation that permanently removes the vector store.
Args: vector_store_name: The unique name of the vector store within the account vector_store_use_case: Injected vector store use case
Returns: Deletion confirmation with the vector store ID
Insert or update documents in a vector store.
Existing documents (by ID) will be updated, new documents will be inserted.
Args: request: Array of documents to upsert vector_store_name: The unique name of the vector store vector_store_use_case: Injected vector store use case
Returns: Batch operation results with success/failure counts
Delete documents from a vector store by IDs or filter.
Args: request: Either IDs or filter criteria for deletion vector_store_name: The unique name of the vector store vector_store_use_case: Injected vector store use case
Returns: Number of documents deleted
List documents in a vector store with pagination.
Args: vector_store_name: The unique name of the vector store limit: Maximum number of documents per page (max 100 with vectors, 1000 without) cursor: Pagination cursor from previous response filter_param: Optional metadata filter (JSON string) include_vectors: Whether to include embedding vectors vector_store_use_case: Injected vector store use case
Returns: Paginated list of documents
Count documents in a vector store, optionally filtered by metadata.
Args: vector_store_name: The unique name of the vector store request: Optional filter criteria (empty body counts all documents) vector_store_use_case: Injected vector store use case
Returns: The count of documents matching the criteria
The name of the vector store
Metadata filter expression
Response for count operation.
Number of documents matching the criteria
Query documents by similarity search.
Supports semantic (vector), lexical (text), or hybrid search modes.
Args: request: Query parameters including text, filters, and reranking options vector_store_name: The unique name of the vector store vector_store_use_case: Injected vector store use case
Returns: Matching documents with similarity scores and query metadata
Domain types
Response model for vector store operations.