Complete evaluation dataset with metadata. An evaluation dataset is a collection of queries with ground truth relevance labels, used to measure retriever quality.
| Name | Type | Description | Notes |
|---|---|---|---|
| dataset_id | str | Unique dataset identifier | |
| dataset_name | str | Human-readable dataset name | |
| description | str | Dataset description | [optional] |
| queries | List[GroundTruthQuery] | List of queries with ground truth | |
| created_at | datetime | When dataset was created | |
| updated_at | datetime | Last update timestamp | |
| namespace_id | str | Namespace this dataset belongs to | |
| internal_id | str | Internal organization ID | |
| query_count | int | Number of queries in dataset | |
| metadata | Dict[str, object] | Additional metadata (e.g., labeling instructions, version info) | [optional] |
from mixpeek.models.evaluation_dataset import EvaluationDataset
# TODO update the JSON string below
json = "{}"
# create an instance of EvaluationDataset from a JSON string
evaluation_dataset_instance = EvaluationDataset.from_json(json)
# print the JSON string representation of the object
print(EvaluationDataset.to_json())
# convert the object into a dict
evaluation_dataset_dict = evaluation_dataset_instance.to_dict()
# create an instance of EvaluationDataset from a dict
evaluation_dataset_from_dict = EvaluationDataset.from_dict(evaluation_dataset_dict)