PGVectoRsStore

pydantic model llama_index.vector_stores.PGVectoRsStore

Show JSON schema

{
   "title": "PGVectoRsStore",
   "description": "Abstract vector store protocol.",
   "type": "object",
   "properties": {
      "stores_text": {
         "title": "Stores Text",
         "default": true,
         "type": "boolean"
      },
      "is_embedding_query": {
         "title": "Is Embedding Query",
         "default": true,
         "type": "boolean"
      },
      "class_name": {
         "title": "Class Name",
         "type": "string",
         "default": "PGVectoRsStore"
      }
   }
}

Config

• schema_extra: function = <function BaseComponent.Config.schema_extra at 0x7ff1e41e53a0>

Fields

add(nodes: List[BaseNode]) → List[str]

Add nodes to vector store.

classmethod class_name() → str

Get the class name, used as a unique ID in serialization.

This provides a key that makes serialization robust against actual class name changes.

delete(ref_doc_id: str, **delete_kwargs: Any) → None

Delete nodes using with ref_doc_id.

query(query: VectorStoreQuery, **kwargs: Any) → VectorStoreQueryResult

Query vector store.

property client: Any

Get client.