Get domain template
Returns the full template for a semantic domain: its datasets and fields, relationships, metrics, composed dimensions, and context.
The template is always returned in the 2.1 shape
(schemaVersion: "2.1"), even when the domain was last saved in the
2.0 shape. The stored copy is upgraded the next time the domain is
saved.
This endpoint requires write access to the domain (Author role or above), since templates are typically read in the context of editing.
If the stored template is corrupted or uses an unrecognized format,
the endpoint returns 400 so you can replace it with a valid
template.
Authorization
BearerAuth AuthorizationBearer <token>
A project-scoped access token. Generate one via the Token API with your projectId and projectSecret.
In: header
Path Parameters
domainId*string
The unique identifier of the semantic domain.
Response Body
application/json
application/json
application/json
application/json
application/json
curl -X get "https://semaphor.cloud/api/v1/domains/domain_abc123/template"{
"template": {
"schemaVersion": "2.1",
"id": "domain_abc123",
"name": "sales_metrics",
"label": "Sales Metrics",
"description": "Revenue and order tracking",
"aiContext": "Revenue is net of refunds. Use order_date for time questions.",
"datasets": [
{
"name": "orders",
"label": "Orders",
"description": "string",
"aiContext": "Revenue is net of refunds. Use order_date for time questions.",
"analyticsRole": "fact",
"source": {
"kind": "table",
"connectionId": "conn_1",
"connectionType": "PostgreSQL",
"database": "analytics",
"schema": "public",
"table": "orders"
},
"primaryKey": [
"order_id"
],
"uniqueKeys": [
[
"order_number"
]
],
"primaryDateField": "order_date",
"fields": {
"identifiers": [
{
"name": "amount",
"label": "Amount",
"description": "string",
"aiContext": "Revenue is net of refunds. Use order_date for time questions.",
"dataType": "number",
"nativeDataType": "numeric(12,2)",
"sourceField": "amount",
"hidden": true,
"tags": [
"string"
],
"type": "primary"
}
],
"facts": [
{
"name": "amount",
"label": "Amount",
"description": "string",
"aiContext": "Revenue is net of refunds. Use order_date for time questions.",
"dataType": "number",
"nativeDataType": "numeric(12,2)",
"sourceField": "amount",
"hidden": true,
"tags": [
"string"
],
"expression": "amount_cents / 100",
"defaultAggregate": "SUM",
"filters": [
{
"field": "string",
"operator": "string",
"value": null
}
],
"format": null,
"unit": "USD",
"comparisonPolarity": "higher_is_better",
"isDefault": true
}
],
"dimensions": [
{
"name": "amount",
"label": "Amount",
"description": "string",
"aiContext": "Revenue is net of refunds. Use order_date for time questions.",
"dataType": "number",
"nativeDataType": "numeric(12,2)",
"sourceField": "amount",
"hidden": true,
"tags": [
"string"
],
"expression": "string",
"isDisplayField": true,
"granularity": "second",
"format": {
"type": "temporal_bucket",
"presentation": {
"mode": "auto"
}
}
}
]
}
}
],
"relationships": [
{
"id": "string",
"name": "orders_to_customers",
"description": "string",
"aiContext": "Revenue is net of refunds. Use order_date for time questions.",
"from": {
"dataset": "orders",
"fields": [
"customer_id"
]
},
"to": {
"dataset": "orders",
"fields": [
"customer_id"
]
},
"cardinality": "many_to_one",
"defaultJoinType": "LEFT",
"isAutoJoin": true,
"joinPriority": 10,
"isActive": true,
"discoveredBy": "user",
"confidence": "high"
}
],
"metrics": [
{
"name": "revenue",
"dataset": "orders",
"expression": "SUM(amount)",
"label": "Revenue",
"description": "string",
"aiContext": "Revenue is net of refunds. Use order_date for time questions.",
"dataType": "number",
"nativeDataType": "string",
"format": null,
"unit": "string",
"comparisonPolarity": "higher_is_better",
"isDefault": true,
"hidden": true,
"tags": [
"string"
]
}
],
"composedDimensions": [
{
"name": "order_month",
"label": "Order Month",
"description": "string",
"aiContext": "Revenue is net of refunds. Use order_date for time questions.",
"expression": "DATE_TRUNC('month', {order_date})",
"inputs": {
"order_date": {
"dataset": "orders",
"field": "order_date"
}
},
"dataType": "string",
"granularity": "second",
"format": {
"type": "temporal_bucket",
"presentation": {
"mode": "auto"
}
},
"grainMapping": {
"property1": "string",
"property2": "string"
}
}
],
"grainMappings": [
{
"sourceDimension": "order_month",
"targetDataset": "returns",
"targetColumn": "return_date"
}
]
}
}{
"error": "string",
"details": {},
"errors": [
{
"code": "row_expression_in_dataset_metric",
"message": "margin works row by row. Add it as a fact (to aggregate) or a dimension (to group by).",
"severity": "error",
"hint": "string",
"context": {}
}
],
"warnings": [
{
"code": "row_expression_in_dataset_metric",
"message": "margin works row by row. Add it as a fact (to aggregate) or a dimension (to group by).",
"severity": "error",
"hint": "string",
"context": {}
}
]
}{
"error": "string",
"details": {},
"errors": [
{
"code": "row_expression_in_dataset_metric",
"message": "margin works row by row. Add it as a fact (to aggregate) or a dimension (to group by).",
"severity": "error",
"hint": "string",
"context": {}
}
],
"warnings": [
{
"code": "row_expression_in_dataset_metric",
"message": "margin works row by row. Add it as a fact (to aggregate) or a dimension (to group by).",
"severity": "error",
"hint": "string",
"context": {}
}
]
}{
"error": "string",
"details": {},
"errors": [
{
"code": "row_expression_in_dataset_metric",
"message": "margin works row by row. Add it as a fact (to aggregate) or a dimension (to group by).",
"severity": "error",
"hint": "string",
"context": {}
}
],
"warnings": [
{
"code": "row_expression_in_dataset_metric",
"message": "margin works row by row. Add it as a fact (to aggregate) or a dimension (to group by).",
"severity": "error",
"hint": "string",
"context": {}
}
]
}{
"error": "string",
"details": {},
"errors": [
{
"code": "row_expression_in_dataset_metric",
"message": "margin works row by row. Add it as a fact (to aggregate) or a dimension (to group by).",
"severity": "error",
"hint": "string",
"context": {}
}
],
"warnings": [
{
"code": "row_expression_in_dataset_metric",
"message": "margin works row by row. Add it as a fact (to aggregate) or a dimension (to group by).",
"severity": "error",
"hint": "string",
"context": {}
}
]
}