API Reference

Evaluation Dashboards

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Get Evaluation Dashboard

GET/v5/evaluation-dashboards/{dashboard_id}

Fetch a single dashboard by ID within the caller’s account.

By default only the dashboard’s own fields are returned. Pass views=widgets and/or views=widget_results to eagerly load the dashboard’s widgets and their last-computed results as nested relationships; without those views the widgets and widget_results fields are omitted from the response entirely. Set include_archived=true to retrieve a soft-deleted dashboard. Returns a not-found error if no matching dashboard exists in the account.

Path ParametersExpand Collapse

dashboard_id: string

Query ParametersExpand Collapse

include_archived: optional boolean

views: optional array of "widgets" or "widget_results"

Optional relationships to include: ‘widgets’, ‘widget_results’

One of the following:

"widgets"

"widget_results"

ReturnsExpand Collapse

EvaluationDashboard object { id, account_id, created_at, 13 more }

id: string

Unique identifier of the dashboard

account_id: string

Account that owns this dashboard

created_at: string

When the dashboard was created

formatdate-time

created_by: Identity { id, type, object }

The identity that created the entity.

id: string

type: "user" or "service_account"

One of the following:

"user"

"service_account"

object: optional "identity"

name: string

Dashboard name

tags: array of string

The tags associated with the entity

updated_at: string

When the dashboard was last updated

formatdate-time

archived_at: optional string

When the dashboard was archived (soft-deleted)

formatdate-time

description: optional string

Dashboard description

error_message: optional string

Error message if computation failed

evaluation_group_id: optional string

Evaluation group ID

evaluation_id: optional string

Evaluation ID

object: optional "evaluation_dashboard"

widget_order: optional array of string

Ordered array of widget IDs

widget_results: optional array of EvaluationDashboardWidgetResult { id, account_id, computation_status, 10 more }

Widget results for this dashboard. Populated with ‘widget_results’ view.

id: string

Unique identifier of the widget result

account_id: string

Account that owns this widget result

computation_status: "pending" or "completed" or "failed"

Status of the computation

One of the following:

"pending"

"completed"

"failed"

created_at: string

When the widget result was created

formatdate-time

widget_id: string

Unique identifier of the widget

computation_job_id: optional string

Temporal workflow ID or job ID for async computation tracking

computed_at: optional string

Timestamp when computation completed successfully

formatdate-time

computed_result: optional map[unknown]

Cached computation results

error_message: optional string

Error message if computation failed

evaluation_group_id: optional string

FK to evaluation_groups. Null if result is for a single evaluation.

evaluation_id: optional string

FK to evaluations. Null if result is for an evaluation group.

object: optional "evaluation_dashboard_widget_result"

widget: optional EvaluationDashboardWidget { id, account_id, created_at, 6 more }

Widget that this result is for

id: string

Unique identifier of the widget

account_id: string

Account that owns this widget

created_at: string

When the widget was created

formatdate-time

title: string

Widget title

type: EvaluationWidgetTypeEnum

Widget type

One of the following:

"bar"

"histogram"

"donut"

"scatter"

"metric"

"table"

"markdown"

"heading"

"timeseries"

archived_at: optional string

When the widget was archived (soft-deleted)

formatdate-time

config: optional map[unknown]

Chart-specific display configuration

object: optional "evaluation_dashboard_widget"

query: optional SeriesQuery { select, evaluation_ids, filter, 4 more } or MetricQuery { select, evaluation_ids, filter, latest_only }

Structured query AST for metric computation (SeriesQuery or MetricQuery)

One of the following:

SeriesQuery object { select, evaluation_ids, filter, 4 more }

Query that returns a series of records (used for table/bar/histogram/donut/scatter widgets).

Used for widget types: table, bar, histogram, donut, scatter. Returns: {“type”: “series”, “data”: […]}

Example SQL equivalent: SELECT category, AVG(score) as avg_score, COUNT(*) as count FROM evaluation_items WHERE score > 0.5 AND category = ‘test’ GROUP BY category ORDER BY avg_score DESC LIMIT 100

select: array of SelectItem { expression, alias }

expression: object { column, source, type } or object { column, function, evaluation_ids, 3 more }

Reference to a column from evaluation_items.data

Example: {“type”: “COLUMN”, “column”: “category”}

One of the following:

Column object { column, source, type }

Reference to a column from evaluation_items.data

Example: {“type”: “COLUMN”, “column”: “category”}

column: string

Column name from evaluation_items.data

source: optional string

Column source: ‘data’ or ‘task_result_cache’

type: optional "COLUMN"

Aggregation object { column, function, evaluation_ids, 3 more }

Aggregation function to apply

Examples: {“type”: “AGGREGATION”, “function”: “AVG”, “column”: “score”} {“type”: “AGGREGATION”, “function”: “COUNT”, “column”: ”*”} {“type”: “AGGREGATION”, “function”: “PERCENTILE”, “column”: “score”, “params”: {“percentile”: 95}}

column: string

Column to aggregate, or '' for COUNT()

function: "COUNT" or "SUM" or "AVG" or 7 more

Supported aggregation functions

One of the following:

"COUNT"

"SUM"

"AVG"

"MIN"

"MAX"

"STDDEV"

"VARIANCE"

"PERCENTILE"

"COUNT_DISTINCT"

"PERCENTAGE"

evaluation_ids: optional array of string

Optional subset of evaluation IDs for per-aggregation filtering in evaluation group dashboards.

params: optional map[unknown]

Function parameters (e.g., {‘percentile’: 95} for PERCENTILE, {‘percentage_filters’: Filter} for PERCENTAGE)

source: optional string

Column source: ‘data’ or ‘task_result_cache’

type: optional "AGGREGATION"

alias: optional string

Optional alias for the selected item

evaluation_ids: optional array of string

Optional subset of evaluation IDs to compute on. Only applicable for evaluation group dashboards. If omitted, computes on all evaluations in the group.

filter: optional Filter { conditions, logicalOperators }

Filter conditions (WHERE clause)

conditions: array of object { column, operator, source, value }

column: string

Column name to filter on

operator: "=" or "!=" or ">" or 9 more

Comparison operator

One of the following:

"="

"!="

">"

"<"

">="

"<="

"IN"

"NOT IN"

"LIKE"

"NOT LIKE"

"IS NULL"

"IS NOT NULL"

source: optional string

Column source: ‘data’ or ‘task_result_cache’

value: optional string or number or boolean or array of unknown

Value to compare against. Not required for IS NULL / IS NOT NULL operators.

One of the following:

string

number

boolean

array of unknown

logicalOperators: optional array of "AND" or "OR"

Logical operators connecting conditions. Length must be len(conditions) - 1

One of the following:

"AND"

"OR"

groupBy: optional array of string

Columns to group by

latest_only: optional boolean

When True, the widget computes against rows from only the most recent active evaluation in the group (by EvaluationORM.created_at). Only applicable for evaluation group dashboards. Composes with evaluation_ids (latest within the subset). Cannot be combined with per-aggregation evaluation_ids; the use case enforces these rules.

limit: optional number

Max rows to return

minimum1

orderBy: optional array of object { column, direction, source }

Sort order

column: string

Column name to sort by

direction: optional "ASC" or "DESC"

Sort direction

One of the following:

"ASC"

"DESC"

source: optional string

Column source: ‘data’ or ‘task_result_cache’

MetricQuery object { select, evaluation_ids, filter, latest_only }

Query that returns a single metric value (used for metric widgets).

Used for widget type: metric. Enforces exactly 1 aggregation in select. Returns: {“type”: “metric”, “data”: …}

Example SQL equivalent: SELECT AVG(score) as average_score FROM evaluation_items

select: array of SelectItem { expression, alias }

expression: object { column, source, type } or object { column, function, evaluation_ids, 3 more }

Reference to a column from evaluation_items.data

Example: {“type”: “COLUMN”, “column”: “category”}

One of the following:

Column object { column, source, type }

Reference to a column from evaluation_items.data

Example: {“type”: “COLUMN”, “column”: “category”}

column: string

Column name from evaluation_items.data

source: optional string

Column source: ‘data’ or ‘task_result_cache’

type: optional "COLUMN"

Aggregation object { column, function, evaluation_ids, 3 more }

Aggregation function to apply

Examples: {“type”: “AGGREGATION”, “function”: “AVG”, “column”: “score”} {“type”: “AGGREGATION”, “function”: “COUNT”, “column”: ”*”} {“type”: “AGGREGATION”, “function”: “PERCENTILE”, “column”: “score”, “params”: {“percentile”: 95}}

column: string

Column to aggregate, or '' for COUNT()

function: "COUNT" or "SUM" or "AVG" or 7 more

Supported aggregation functions

One of the following:

"COUNT"

"SUM"

"AVG"

"MIN"

"MAX"

"STDDEV"

"VARIANCE"

"PERCENTILE"

"COUNT_DISTINCT"

"PERCENTAGE"

evaluation_ids: optional array of string

Optional subset of evaluation IDs for per-aggregation filtering in evaluation group dashboards.

params: optional map[unknown]

Function parameters (e.g., {‘percentile’: 95} for PERCENTILE, {‘percentage_filters’: Filter} for PERCENTAGE)

source: optional string

Column source: ‘data’ or ‘task_result_cache’

type: optional "AGGREGATION"

alias: optional string

Optional alias for the selected item

evaluation_ids: optional array of string

Optional subset of evaluation IDs to compute on. Only applicable for evaluation group dashboards. If omitted, computes on all evaluations in the group.

filter: optional Filter { conditions, logicalOperators }

Filter conditions (WHERE clause)

conditions: array of object { column, operator, source, value }

column: string

Column name to filter on

operator: "=" or "!=" or ">" or 9 more

Comparison operator

One of the following:

"="

"!="

">"

"<"

">="

"<="

"IN"

"NOT IN"

"LIKE"

"NOT LIKE"

"IS NULL"

"IS NOT NULL"

source: optional string

Column source: ‘data’ or ‘task_result_cache’

value: optional string or number or boolean or array of unknown

Value to compare against. Not required for IS NULL / IS NOT NULL operators.

One of the following:

string

number

boolean

array of unknown

logicalOperators: optional array of "AND" or "OR"

Logical operators connecting conditions. Length must be len(conditions) - 1

One of the following:

"AND"

"OR"

latest_only: optional boolean

When True, the widget computes against rows from only the most recent active evaluation in the group (by EvaluationORM.created_at). Only applicable for evaluation group dashboards. Composes with evaluation_ids (latest within the subset). Cannot be combined with per-aggregation evaluation_ids; the use case enforces these rules.

widgets: optional array of EvaluationDashboardWidget { id, account_id, created_at, 6 more }

Widgets associated with this dashboard. Populated with ‘widgets’ view.

id: string

Unique identifier of the widget

account_id: string

Account that owns this widget

created_at: string

When the widget was created

formatdate-time

title: string

Widget title

type: EvaluationWidgetTypeEnum

Widget type

One of the following:

"bar"

"histogram"

"donut"

"scatter"

"metric"

"table"

"markdown"

"heading"

"timeseries"

archived_at: optional string

When the widget was archived (soft-deleted)

formatdate-time

config: optional map[unknown]

Chart-specific display configuration

object: optional "evaluation_dashboard_widget"

query: optional SeriesQuery { select, evaluation_ids, filter, 4 more } or MetricQuery { select, evaluation_ids, filter, latest_only }

Structured query AST for metric computation (SeriesQuery or MetricQuery)

One of the following:

SeriesQuery object { select, evaluation_ids, filter, 4 more }

Query that returns a series of records (used for table/bar/histogram/donut/scatter widgets).

Used for widget types: table, bar, histogram, donut, scatter. Returns: {“type”: “series”, “data”: […]}

Example SQL equivalent: SELECT category, AVG(score) as avg_score, COUNT(*) as count FROM evaluation_items WHERE score > 0.5 AND category = ‘test’ GROUP BY category ORDER BY avg_score DESC LIMIT 100

select: array of SelectItem { expression, alias }

expression: object { column, source, type } or object { column, function, evaluation_ids, 3 more }

Reference to a column from evaluation_items.data

Example: {“type”: “COLUMN”, “column”: “category”}

One of the following:

Column object { column, source, type }

Reference to a column from evaluation_items.data

Example: {“type”: “COLUMN”, “column”: “category”}

column: string

Column name from evaluation_items.data

source: optional string

Column source: ‘data’ or ‘task_result_cache’

type: optional "COLUMN"

Aggregation object { column, function, evaluation_ids, 3 more }

Aggregation function to apply

Examples: {“type”: “AGGREGATION”, “function”: “AVG”, “column”: “score”} {“type”: “AGGREGATION”, “function”: “COUNT”, “column”: ”*”} {“type”: “AGGREGATION”, “function”: “PERCENTILE”, “column”: “score”, “params”: {“percentile”: 95}}

column: string

Column to aggregate, or '' for COUNT()

function: "COUNT" or "SUM" or "AVG" or 7 more

Supported aggregation functions

One of the following:

"COUNT"

"SUM"

"AVG"

"MIN"

"MAX"

"STDDEV"

"VARIANCE"

"PERCENTILE"

"COUNT_DISTINCT"

"PERCENTAGE"

evaluation_ids: optional array of string

Optional subset of evaluation IDs for per-aggregation filtering in evaluation group dashboards.

params: optional map[unknown]

Function parameters (e.g., {‘percentile’: 95} for PERCENTILE, {‘percentage_filters’: Filter} for PERCENTAGE)

source: optional string

Column source: ‘data’ or ‘task_result_cache’

type: optional "AGGREGATION"

alias: optional string

Optional alias for the selected item

evaluation_ids: optional array of string

Optional subset of evaluation IDs to compute on. Only applicable for evaluation group dashboards. If omitted, computes on all evaluations in the group.

filter: optional Filter { conditions, logicalOperators }

Filter conditions (WHERE clause)

conditions: array of object { column, operator, source, value }

column: string

Column name to filter on

operator: "=" or "!=" or ">" or 9 more

Comparison operator

One of the following:

"="

"!="

">"

"<"

">="

"<="

"IN"

"NOT IN"

"LIKE"

"NOT LIKE"

"IS NULL"

"IS NOT NULL"

source: optional string

Column source: ‘data’ or ‘task_result_cache’

value: optional string or number or boolean or array of unknown

Value to compare against. Not required for IS NULL / IS NOT NULL operators.

One of the following:

string

number

boolean

array of unknown

logicalOperators: optional array of "AND" or "OR"

Logical operators connecting conditions. Length must be len(conditions) - 1

One of the following:

"AND"

"OR"

groupBy: optional array of string

Columns to group by

latest_only: optional boolean

When True, the widget computes against rows from only the most recent active evaluation in the group (by EvaluationORM.created_at). Only applicable for evaluation group dashboards. Composes with evaluation_ids (latest within the subset). Cannot be combined with per-aggregation evaluation_ids; the use case enforces these rules.

limit: optional number

Max rows to return

minimum1

orderBy: optional array of object { column, direction, source }

Sort order

column: string

Column name to sort by

direction: optional "ASC" or "DESC"

Sort direction

One of the following:

"ASC"

"DESC"

source: optional string

Column source: ‘data’ or ‘task_result_cache’

MetricQuery object { select, evaluation_ids, filter, latest_only }

Query that returns a single metric value (used for metric widgets).

Used for widget type: metric. Enforces exactly 1 aggregation in select. Returns: {“type”: “metric”, “data”: …}

Example SQL equivalent: SELECT AVG(score) as average_score FROM evaluation_items

select: array of SelectItem { expression, alias }

expression: object { column, source, type } or object { column, function, evaluation_ids, 3 more }

Reference to a column from evaluation_items.data

Example: {“type”: “COLUMN”, “column”: “category”}

One of the following:

Column object { column, source, type }

Reference to a column from evaluation_items.data

Example: {“type”: “COLUMN”, “column”: “category”}

column: string

Column name from evaluation_items.data

source: optional string

Column source: ‘data’ or ‘task_result_cache’

type: optional "COLUMN"

Aggregation object { column, function, evaluation_ids, 3 more }

Aggregation function to apply

Examples: {“type”: “AGGREGATION”, “function”: “AVG”, “column”: “score”} {“type”: “AGGREGATION”, “function”: “COUNT”, “column”: ”*”} {“type”: “AGGREGATION”, “function”: “PERCENTILE”, “column”: “score”, “params”: {“percentile”: 95}}

column: string

Column to aggregate, or '' for COUNT()

function: "COUNT" or "SUM" or "AVG" or 7 more

Supported aggregation functions

One of the following:

"COUNT"

"SUM"

"AVG"

"MIN"

"MAX"

"STDDEV"

"VARIANCE"

"PERCENTILE"

"COUNT_DISTINCT"

"PERCENTAGE"

evaluation_ids: optional array of string

Optional subset of evaluation IDs for per-aggregation filtering in evaluation group dashboards.

params: optional map[unknown]

Function parameters (e.g., {‘percentile’: 95} for PERCENTILE, {‘percentage_filters’: Filter} for PERCENTAGE)

source: optional string

Column source: ‘data’ or ‘task_result_cache’

type: optional "AGGREGATION"

alias: optional string

Optional alias for the selected item

evaluation_ids: optional array of string

Optional subset of evaluation IDs to compute on. Only applicable for evaluation group dashboards. If omitted, computes on all evaluations in the group.

filter: optional Filter { conditions, logicalOperators }

Filter conditions (WHERE clause)

conditions: array of object { column, operator, source, value }

column: string

Column name to filter on

operator: "=" or "!=" or ">" or 9 more

Comparison operator

One of the following:

"="

"!="

">"

"<"

">="

"<="

"IN"

"NOT IN"

"LIKE"

"NOT LIKE"

"IS NULL"

"IS NOT NULL"

source: optional string

Column source: ‘data’ or ‘task_result_cache’

value: optional string or number or boolean or array of unknown

Value to compare against. Not required for IS NULL / IS NOT NULL operators.

One of the following:

string

number

boolean

array of unknown

logicalOperators: optional array of "AND" or "OR"

Logical operators connecting conditions. Length must be len(conditions) - 1

One of the following:

"AND"

"OR"

latest_only: optional boolean

When True, the widget computes against rows from only the most recent active evaluation in the group (by EvaluationORM.created_at). Only applicable for evaluation group dashboards. Composes with evaluation_ids (latest within the subset). Cannot be combined with per-aggregation evaluation_ids; the use case enforces these rules.

Get Evaluation Dashboard

HTTP

HTTP

TypeScript

Python

Go

curl https://api.egp.scale.com/v5/evaluation-dashboards/$DASHBOARD_ID \
    -H "x-api-key: $SGP_API_KEY"

200 example

{
  "id": "id",
  "account_id": "account_id",
  "created_at": "2019-12-27T18:11:19.117Z",
  "created_by": {
    "id": "id",
    "type": "user",
    "object": "identity"
  },
  "name": "name",
  "tags": [
    "string"
  ],
  "updated_at": "2019-12-27T18:11:19.117Z",
  "archived_at": "2019-12-27T18:11:19.117Z",
  "description": "description",
  "error_message": "error_message",
  "evaluation_group_id": "evaluation_group_id",
  "evaluation_id": "evaluation_id",
  "object": "evaluation_dashboard",
  "widget_order": [
    "string"
  ],
  "widget_results": [
    {
      "id": "id",
      "account_id": "account_id",
      "computation_status": "pending",
      "created_at": "2019-12-27T18:11:19.117Z",
      "widget_id": "widget_id",
      "computation_job_id": "computation_job_id",
      "computed_at": "2019-12-27T18:11:19.117Z",
      "computed_result": {
        "foo": "bar"
      },
      "error_message": "error_message",
      "evaluation_group_id": "evaluation_group_id",
      "evaluation_id": "evaluation_id",
      "object": "evaluation_dashboard_widget_result",
      "widget": {
        "id": "id",
        "account_id": "account_id",
        "created_at": "2019-12-27T18:11:19.117Z",
        "title": "title",
        "type": "bar",
        "archived_at": "2019-12-27T18:11:19.117Z",
        "config": {
          "foo": "bar"
        },
        "object": "evaluation_dashboard_widget",
        "query": {
          "select": [
            {
              "expression": {
                "column": "column",
                "source": "source",
                "type": "COLUMN"
              },
              "alias": "alias"
            }
          ],
          "evaluation_ids": [
            "string"
          ],
          "filter": {
            "conditions": [
              {
                "column": "column",
                "operator": "=",
                "source": "source",
                "value": "string"
              }
            ],
            "logicalOperators": [
              "AND"
            ]
          },
          "groupBy": [
            "string"
          ],
          "latest_only": true,
          "limit": 1,
          "orderBy": [
            {
              "column": "column",
              "direction": "ASC",
              "source": "source"
            }
          ]
        }
      }
    }
  ],
  "widgets": [
    {
      "id": "id",
      "account_id": "account_id",
      "created_at": "2019-12-27T18:11:19.117Z",
      "title": "title",
      "type": "bar",
      "archived_at": "2019-12-27T18:11:19.117Z",
      "config": {
        "foo": "bar"
      },
      "object": "evaluation_dashboard_widget",
      "query": {
        "select": [
          {
            "expression": {
              "column": "column",
              "source": "source",
              "type": "COLUMN"
            },
            "alias": "alias"
          }
        ],
        "evaluation_ids": [
          "string"
        ],
        "filter": {
          "conditions": [
            {
              "column": "column",
              "operator": "=",
              "source": "source",
              "value": "string"
            }
          ],
          "logicalOperators": [
            "AND"
          ]
        },
        "groupBy": [
          "string"
        ],
        "latest_only": true,
        "limit": 1,
        "orderBy": [
          {
            "column": "column",
            "direction": "ASC",
            "source": "source"
          }
        ]
      }
    }
  ]
}

Returns Examples

200 example

{
  "id": "id",
  "account_id": "account_id",
  "created_at": "2019-12-27T18:11:19.117Z",
  "created_by": {
    "id": "id",
    "type": "user",
    "object": "identity"
  },
  "name": "name",
  "tags": [
    "string"
  ],
  "updated_at": "2019-12-27T18:11:19.117Z",
  "archived_at": "2019-12-27T18:11:19.117Z",
  "description": "description",
  "error_message": "error_message",
  "evaluation_group_id": "evaluation_group_id",
  "evaluation_id": "evaluation_id",
  "object": "evaluation_dashboard",
  "widget_order": [
    "string"
  ],
  "widget_results": [
    {
      "id": "id",
      "account_id": "account_id",
      "computation_status": "pending",
      "created_at": "2019-12-27T18:11:19.117Z",
      "widget_id": "widget_id",
      "computation_job_id": "computation_job_id",
      "computed_at": "2019-12-27T18:11:19.117Z",
      "computed_result": {
        "foo": "bar"
      },
      "error_message": "error_message",
      "evaluation_group_id": "evaluation_group_id",
      "evaluation_id": "evaluation_id",
      "object": "evaluation_dashboard_widget_result",
      "widget": {
        "id": "id",
        "account_id": "account_id",
        "created_at": "2019-12-27T18:11:19.117Z",
        "title": "title",
        "type": "bar",
        "archived_at": "2019-12-27T18:11:19.117Z",
        "config": {
          "foo": "bar"
        },
        "object": "evaluation_dashboard_widget",
        "query": {
          "select": [
            {
              "expression": {
                "column": "column",
                "source": "source",
                "type": "COLUMN"
              },
              "alias": "alias"
            }
          ],
          "evaluation_ids": [
            "string"
          ],
          "filter": {
            "conditions": [
              {
                "column": "column",
                "operator": "=",
                "source": "source",
                "value": "string"
              }
            ],
            "logicalOperators": [
              "AND"
            ]
          },
          "groupBy": [
            "string"
          ],
          "latest_only": true,
          "limit": 1,
          "orderBy": [
            {
              "column": "column",
              "direction": "ASC",
              "source": "source"
            }
          ]
        }
      }
    }
  ],
  "widgets": [
    {
      "id": "id",
      "account_id": "account_id",
      "created_at": "2019-12-27T18:11:19.117Z",
      "title": "title",
      "type": "bar",
      "archived_at": "2019-12-27T18:11:19.117Z",
      "config": {
        "foo": "bar"
      },
      "object": "evaluation_dashboard_widget",
      "query": {
        "select": [
          {
            "expression": {
              "column": "column",
              "source": "source",
              "type": "COLUMN"
            },
            "alias": "alias"
          }
        ],
        "evaluation_ids": [
          "string"
        ],
        "filter": {
          "conditions": [
            {
              "column": "column",
              "operator": "=",
              "source": "source",
              "value": "string"
            }
          ],
          "logicalOperators": [
            "AND"
          ]
        },
        "groupBy": [
          "string"
        ],
        "latest_only": true,
        "limit": 1,
        "orderBy": [
          {
            "column": "column",
            "direction": "ASC",
            "source": "source"
          }
        ]
      }
    }
  ]
}