datasets

load_dataset

def load_dataset(dataset: Union['Dataset', list[dict[str, Any] | str], str, None],
                 dataset_id: str | None,
                 dataset_name: str | None) -> Optional['Dataset']

Load dataset based on provided parameters.

Arguments

• dataset: Dataset object, list of records, or dataset name
• dataset_id: ID of the dataset
• dataset_name: Name of the dataset

Raises

• ValueError: If no dataset information is provided or dataset doesn’t exist

Returns

• Dataset object or None:

load_dataset_and_records

def load_dataset_and_records(dataset: Union['Dataset', list[dict[str, Any] | str], str, None],
                             dataset_id: str | None,
                             dataset_name: str | None) -> tuple[Optional['Dataset'], list[DatasetRecord]]

Load dataset and records based on provided parameters.

Arguments

• dataset: Dataset object, list of records, or dataset name
• dataset_id: ID of the dataset
• dataset_name: Name of the dataset

Raises

• ValueError: If no dataset information is provided or dataset doesn’t exist

Returns

• Tuple containing (Dataset object or None, records list):

normalize_dataset_rows

def normalize_dataset_rows(rows: list[dict[str, Any]]) -> list[dict[str, Any]]

Normalize dataset rows by renaming ground_truth to output.

Allows callers to use either field name. output takes precedence when both are present. The caller’s original dicts are never mutated.

remap_output_to_ground_truth

def remap_output_to_ground_truth(content: DatasetContent) -> DatasetContent

Renames ‘output’ back to ‘ground_truth’ in DatasetContent returned by the API.

The API stores ground_truth as ‘output’ internally. This is the inverse of normalize_dataset_rows, applied when reading content back out.