Overview Use Cases Connectors Authentication Getting Started with the Python SDK API API Reference ai_agents ai_chat algorithm annotations application_connectors batch_prediction code_completion custom_loss_function custom_metric database_connectors dataset deployment deployment_conversations docstore document_retrievers documentation eda external_app feature_drift feature_group feature_group_row_process feature_group_template file_connectors graph_dashboard holdout_analysis llm_apps model model_monitoring module natural_language_explanation organization pipelines predict prediction_operator project python_function refresh secrets streaming appendData appendMultipleData createStreamingDataset createStreamingToken deleteItemEmbeddings deleteStreamingToken getRecentFeatureGroupStreamedData listStreamingTokens upsertItemEmbeddings upsertMultipleItemEmbeddings streaming_connectors upload user webhooks API Classes API Inputs Documentation Chat Bot API Search How to

Method

upsertItemEmbeddings POST

Copy POST

Upserts an embedding vector for an item id for a model_id.

Arguments:

REQUIRED	KEY	TYPE	DESCRIPTION
Yes	streamingToken	str	The streaming token for authenticating requests to the model.
Yes	modelId	str	A unique string identifier for the model to upsert item embeddings to.
Yes	itemId	str	The item id for which its embeddings will be upserted.
Yes	vector	List[float]	The embedding vector.
No	catalogId	str	The name of the catalog in the model to update.

Note: The arguments for the API methods follow camelCase but for Python SDK underscore_case is followed.

Response:

KEY	TYPE	DESCRIPTION
success	Boolean	true if the call succeeded, false if there was an error

Exceptions:

TYPE	WHEN
DataNotFoundError	`modelId` is not found.
DataNotFoundError	`itemId` is not found.
DataNotFoundError	`catalogId` is not found.

Language: