Upserts data points into a Vertex AI Vector Search 2.0 Collection.
upsert_datapoints(
project_id: str,
region: str,
collection: str,
ids: List[str],
embeddings: List[List[float]],
metadatas: List[dict] | None = None,
credentials: Optional[Credentials] = None,
vector_field_name: str = 'embedding',
sparse_embeddings: List[dict[str, List[int] | List[float]]] | None = None
) -> None| Name | Type | Description |
|---|---|---|
project_id* | str | The GCP project ID. |
region* | str | The GCP region. |
collection* | str | The resource name of the collection. |
ids* | List[str] | List of datapoint IDs. |
embeddings* | List[List[float]] | List of embedding vectors. |
metadatas | List[dict] | None | Default: NoneOptional list of metadata dictionaries. |
credentials | Optional[Credentials] | Default: NoneOptional credentials to use. |
vector_field_name | str | Default: 'embedding'Name of the vector field in the collection schema. |
sparse_embeddings | List[dict[str, List[int] | List[float]]] | None | Default: NoneOptional list of sparse embedding dictionaries. |