aip_sdk.get_dataset_metric_availability

aip_sdk.get_dataset_metric_availability(dataset_id: str, version_id: str, *, metrics: Iterable[str] | None = None, has_connection: bool = True, client: APIClient | None = None) -> DatasetVersionMetricAvailability

Report which dataset (row-level) metrics can score a dataset version, and why the rest cannot.

Uses the same gate as POST /runs, so an available metric is one the run gate accepts. For agent-trace datasets, use aip.get_partition_metric_availability() instead.

Parameters

• dataset_id str: Dataset ID.
• version_id str: Dataset version ID to judge metrics against.
• metrics Iterable[str] | None: Restrict the report to these metric names. An unmatched name is reported unavailable (OP_NOT_FOUND) rather than omitted. None reports every metric visible in the dataset's workspace.
• has_connection bool: Whether inference will fill the produced columns (sut_response, retrieved_context) before scoring. Defaults to True. Pass False to judge the version's at-rest columns alone.
• client APIClient | None: Optional API client.

Returns

• DatasetVersionMetricAvailability: The per-metric verdicts; read available_metrics for just the names that can run.

Raises

• InvalidArgumentError: If metrics is given but empty, or contains a blank name.
• AuthError: If credentials are missing or invalid.
• NotFoundError: If the dataset or dataset version does not exist, or the dataset belongs to a workspace the caller is not a member of.
• UnprocessableEntityError: If the dataset holds agent traces.
• ResponseParseError: If the platform's response does not match this SDK version.