List

List Workspaces

agents.evaluation_metrics.workspaces.list() -> WorkspaceListResponse

get/v2/gen-ai/workspaces

To list all workspaces, send a GET request to /v2/gen-ai/workspaces.

ReturnsExpand Collapse

class WorkspaceListResponse: …

workspaces: Optional[List[APIWorkspace]]

Workspaces

agents: Optional[List[APIAgent]]

Agents

created_at: Optional[datetime]

Creation date

formatdate-time

created_by: Optional[str]

The id of user who created this workspace

formatuint64

created_by_email: Optional[str]

The email of the user who created this workspace

deleted_at: Optional[datetime]

Deleted date

formatdate-time

description: Optional[str]

Description of the workspace

evaluation_test_cases: Optional[List[APIEvaluationTestCase]]

Evaluations

archived_at: Optional[datetime]

created_at: Optional[datetime]

created_by_user_email: Optional[str]

created_by_user_id: Optional[str]

dataset: Optional[Dataset]

created_at: Optional[datetime]

Time created at.

formatdate-time

dataset_name: Optional[str]

Name of the dataset.

dataset_uuid: Optional[str]

UUID of the dataset.

file_size: Optional[str]

The size of the dataset uploaded file in bytes.

formatuint64

has_ground_truth: Optional[bool]

Does the dataset have a ground truth column?

row_count: Optional[int]

Number of rows in the dataset.

formatint64

dataset_name: Optional[str]

dataset_uuid: Optional[str]

description: Optional[str]

latest_version_number_of_runs: Optional[int]

metrics: Optional[List[APIEvaluationMetric]]

description: Optional[str]

inverted: Optional[bool]

If true, the metric is inverted, meaning that a lower value is better.

metric_name: Optional[str]

metric_type: Optional[Literal["METRIC_TYPE_UNSPECIFIED", "METRIC_TYPE_GENERAL_QUALITY", "METRIC_TYPE_RAG_AND_TOOL"]]

Accepts one of the following:

"METRIC_TYPE_UNSPECIFIED"

"METRIC_TYPE_GENERAL_QUALITY"

"METRIC_TYPE_RAG_AND_TOOL"

metric_uuid: Optional[str]

metric_value_type: Optional[Literal["METRIC_VALUE_TYPE_UNSPECIFIED", "METRIC_VALUE_TYPE_NUMBER", "METRIC_VALUE_TYPE_STRING", "METRIC_VALUE_TYPE_PERCENTAGE"]]

Accepts one of the following:

"METRIC_VALUE_TYPE_UNSPECIFIED"

"METRIC_VALUE_TYPE_NUMBER"

"METRIC_VALUE_TYPE_STRING"

"METRIC_VALUE_TYPE_PERCENTAGE"

range_max: Optional[float]

The maximum value for the metric.

formatfloat

range_min: Optional[float]

The minimum value for the metric.

formatfloat

star_metric: Optional[APIStarMetric]

metric_uuid: Optional[str]

success_threshold: Optional[float]

The success threshold for the star metric. This is a value that the metric must reach to be considered successful.

formatfloat

success_threshold_pct: Optional[int]

The success threshold for the star metric. This is a percentage value between 0 and 100.

formatint32

test_case_uuid: Optional[str]

total_runs: Optional[int]

updated_at: Optional[datetime]

updated_by_user_email: Optional[str]

updated_by_user_id: Optional[str]

version: Optional[int]

Name of the workspace

updated_at: Optional[datetime]

Update date

formatdate-time

uuid: Optional[str]

Unique id

List Workspaces

from gradient import Gradient

client = Gradient()
workspaces = client.agents.evaluation_metrics.workspaces.list()
print(workspaces.workspaces)

{
  "workspaces": [
    {
      "agents": [],
      "created_at": "2023-01-01T00:00:00Z",
      "created_by": "12345",
      "created_by_email": "[email protected]",
      "deleted_at": "2023-01-01T00:00:00Z",
      "description": "example string",
      "evaluation_test_cases": [
        {
          "archived_at": "2023-01-01T00:00:00Z",
          "created_at": "2023-01-01T00:00:00Z",
          "created_by_user_email": "[email protected]",
          "created_by_user_id": "12345",
          "dataset": {
            "created_at": "2023-01-01T00:00:00Z",
            "dataset_name": "example name",
            "dataset_uuid": "123e4567-e89b-12d3-a456-426614174000",
            "file_size": "12345",
            "has_ground_truth": true,
            "row_count": 123
          },
          "dataset_name": "example name",
          "dataset_uuid": "123e4567-e89b-12d3-a456-426614174000",
          "description": "example string",
          "latest_version_number_of_runs": 123,
          "metrics": [
            {
              "description": "example string",
              "inverted": true,
              "metric_name": "example name",
              "metric_type": "METRIC_TYPE_UNSPECIFIED",
              "metric_uuid": "123e4567-e89b-12d3-a456-426614174000",
              "metric_value_type": "METRIC_VALUE_TYPE_UNSPECIFIED",
              "range_max": 123,
              "range_min": 123
            }
          ],
          "name": "example name",
          "star_metric": {
            "metric_uuid": "123e4567-e89b-12d3-a456-426614174000",
            "name": "example name",
            "success_threshold": 123,
            "success_threshold_pct": 123
          },
          "test_case_uuid": "123e4567-e89b-12d3-a456-426614174000",
          "total_runs": 123,
          "updated_at": "2023-01-01T00:00:00Z",
          "updated_by_user_email": "[email protected]",
          "updated_by_user_id": "12345",
          "version": 123
        }
      ],
      "name": "example name",
      "updated_at": "2023-01-01T00:00:00Z",
      "uuid": "123e4567-e89b-12d3-a456-426614174000"
    }
  ]
}

Returns Examples

{
  "workspaces": [
    {
      "agents": [],
      "created_at": "2023-01-01T00:00:00Z",
      "created_by": "12345",
      "created_by_email": "[email protected]",
      "deleted_at": "2023-01-01T00:00:00Z",
      "description": "example string",
      "evaluation_test_cases": [
        {
          "archived_at": "2023-01-01T00:00:00Z",
          "created_at": "2023-01-01T00:00:00Z",
          "created_by_user_email": "[email protected]",
          "created_by_user_id": "12345",
          "dataset": {
            "created_at": "2023-01-01T00:00:00Z",
            "dataset_name": "example name",
            "dataset_uuid": "123e4567-e89b-12d3-a456-426614174000",
            "file_size": "12345",
            "has_ground_truth": true,
            "row_count": 123
          },
          "dataset_name": "example name",
          "dataset_uuid": "123e4567-e89b-12d3-a456-426614174000",
          "description": "example string",
          "latest_version_number_of_runs": 123,
          "metrics": [
            {
              "description": "example string",
              "inverted": true,
              "metric_name": "example name",
              "metric_type": "METRIC_TYPE_UNSPECIFIED",
              "metric_uuid": "123e4567-e89b-12d3-a456-426614174000",
              "metric_value_type": "METRIC_VALUE_TYPE_UNSPECIFIED",
              "range_max": 123,
              "range_min": 123
            }
          ],
          "name": "example name",
          "star_metric": {
            "metric_uuid": "123e4567-e89b-12d3-a456-426614174000",
            "name": "example name",
            "success_threshold": 123,
            "success_threshold_pct": 123
          },
          "test_case_uuid": "123e4567-e89b-12d3-a456-426614174000",
          "total_runs": 123,
          "updated_at": "2023-01-01T00:00:00Z",
          "updated_by_user_email": "[email protected]",
          "updated_by_user_id": "12345",
          "version": 123
        }
      ],
      "name": "example name",
      "updated_at": "2023-01-01T00:00:00Z",
      "uuid": "123e4567-e89b-12d3-a456-426614174000"
    }
  ]
}