Add curation_enabled to LLM Obs Patterns spec

.generator/schemas/v2/openapi.yaml

@@ -31063,9 +31063,17 @@ components:
           type: string
         values:
           description: |-
-            Column values in row order. The element type matches the column's `type`;
-            for example a `VARCHAR` column carries strings, a `TIMESTAMP` column carries
-            Unix-millisecond integers. `null` is allowed for missing values.
+            Column values in row order, one entry per result row. The element type
+            follows the column's `type`. The following serialization rules should be
+            taken into account:
+
+            - `BIGINT` values are encoded as JSON numbers in the signed 64-bit integer range.
+            - `DECIMAL` values are encoded as JSON numbers with 64-bit double precision.
+            - `TIMESTAMP` and `DATE` values are encoded as Unix-millisecond integers; a
+              `DATE` resolves to midnight UTC.
+            - `JSON` values are returned as a JSON-encoded string.
+
+            `null` is allowed for any column type where a value is missing.
           example:
             - web-store
             - checkout
@@ -55956,6 +55964,10 @@ components:
           example: "2024-01-15T10:30:00Z"
           format: date-time
           type: string
+        curation_enabled:
+          description: Whether automatic dataset curation is enabled for this configuration.
+          example: true
+          type: boolean
         evp_query:
           description: Query that selects the spans the patterns run analyzes.
           example: "@ml_app:support-bot"
@@ -56028,6 +56040,10 @@ components:
           example: "2024-01-15T10:30:00Z"
           format: date-time
           type: string
+        curation_enabled:
+          description: Whether automatic dataset curation is enabled for this configuration.
+          example: true
+          type: boolean
         evp_query:
           description: Query that selects the spans the patterns run analyzes.
           example: "@ml_app:support-bot"
@@ -56185,6 +56201,13 @@ components:
           description: The ID of an existing configuration to update. If omitted, a new configuration is created.
           example: "a7c8d9e0-1234-5678-9abc-def012345678"
           type: string
+        curation_enabled:
+          description: |-
+            When true, Datadog automatically provisions a managed project and dataset
+            (`{pattern-name}-pattern-curated`) to receive suggested interactions after
+            each run. Defaults to true for new patterns.
+          example: true
+          type: boolean
         evp_query:
           description: Query that selects the spans the patterns run analyzes.
           example: "@ml_app:support-bot"
@@ -135602,9 +135625,6 @@ paths:
       summary: Execute a tabular DDSQL query
       tags:
         - DDSQL
-      x-unstable: |-
-        **Note**: This endpoint is in preview and is subject to change.
-        If you have any feedback, contact [Datadog support](https://docs.datadoghq.com/help/).
   /api/v2/ddsql/query/tabular/fetch:
     post:
       description: |-
@@ -135713,9 +135733,6 @@ paths:
       summary: Fetch the result of a DDSQL query
       tags:
         - DDSQL
-      x-unstable: |-
-        **Note**: This endpoint is in preview and is subject to change.
-        If you have any feedback, contact [Datadog support](https://docs.datadoghq.com/help/).
   /api/v2/deletion/data/{product}:
     post:
       description: Creates a data deletion request by providing a query and a timeframe targeting the proper data.
@@ -154572,6 +154589,7 @@ paths:
                       attributes:
                         configs:
                           - created_at: "2024-01-15T10:30:00Z"
+                            curation_enabled: true
                             evp_query: "@ml_app:support-bot"
                             hierarchy_depth: 2
                             id: a7c8d9e0-1234-5678-9abc-def012345678
@@ -154651,6 +154669,7 @@ paths:
                     data:
                       attributes:
                         created_at: "2024-01-15T10:30:00Z"
+                        curation_enabled: true
                         evp_query: "@ml_app:support-bot"
                         hierarchy_depth: 2
                         name: Support chatbot topics
@@ -154687,6 +154706,12 @@ paths:
               schema:
                 $ref: "#/components/schemas/JSONAPIErrorResponse"
           description: Not Found
+        "409":
+          content:
+            application/json:
+              schema:
+                $ref: "#/components/schemas/JSONAPIErrorResponse"
+          description: Conflict
         "429":
           $ref: "#/components/responses/TooManyRequestsResponse"
         "500":
@@ -154718,6 +154743,7 @@ paths:
                     data:
                       attributes:
                         created_at: "2024-01-15T10:30:00Z"
+                        curation_enabled: true
                         evp_query: "@ml_app:support-bot"
                         hierarchy_depth: 2
                         name: Support chatbot topics

examples/v2/llm-observability/UpsertLLMObsPatternsConfig.py

@@ -18,6 +18,7 @@
         attributes=LLMObsPatternsConfigUpsertRequestAttributes(
             account_id="1000000001",
             config_id="a7c8d9e0-1234-5678-9abc-def012345678",
+            curation_enabled=True,
             evp_query="@ml_app:support-bot",
             hierarchy_depth=2,
             integration_provider="openai",

src/datadog_api_client/configuration.py

@@ -490,8 +490,6 @@ def __init__(
                 "v2.get_all_datasets": False,
                 "v2.get_dataset": False,
                 "v2.update_dataset": False,
-                "v2.execute_ddsql_tabular_query": False,
-                "v2.fetch_ddsql_tabular_query": False,
                 "v2.cancel_data_deletion_request": False,
                 "v2.create_data_deletion_request": False,
                 "v2.get_data_deletion_requests": False,

src/datadog_api_client/v2/model/ddsql_tabular_query_column.py

@@ -44,9 +44,17 @@ def __init__(self_, name: str, type: str, values: List[Any], **kwargs):
             for the full, up-to-date list.
         :type type: str
 
-        :param values: Column values in row order. The element type matches the column's ``type`` ;
-            for example a ``VARCHAR`` column carries strings, a ``TIMESTAMP`` column carries
-            Unix-millisecond integers. ``null`` is allowed for missing values.
+        :param values: Column values in row order, one entry per result row. The element type
+            follows the column's ``type``. The following serialization rules should be
+            taken into account:
+
+            * ``BIGINT`` values are encoded as JSON numbers in the signed 64-bit integer range.
+            * ``DECIMAL`` values are encoded as JSON numbers with 64-bit double precision.
+            * ``TIMESTAMP`` and ``DATE`` values are encoded as Unix-millisecond integers; a
+              ``DATE`` resolves to midnight UTC.
+            * ``JSON`` values are returned as a JSON-encoded string.
+
+            ``null`` is allowed for any column type where a value is missing.
         :type values: [bool, date, datetime, dict, float, int, list, str, UUID, none_type]
         """
         super().__init__(kwargs)

src/datadog_api_client/v2/model/llm_obs_patterns_config_attributes.py

@@ -30,6 +30,7 @@ def openapi_types(_):
         return {
             "account_id": (str, none_type),
             "created_at": (datetime,),
+            "curation_enabled": (bool,),
             "evp_query": (str,),
             "hierarchy_depth": (int,),
             "integration_provider": (str, none_type),
@@ -45,6 +46,7 @@ def openapi_types(_):
     attribute_map = {
         "account_id": "account_id",
         "created_at": "created_at",
+        "curation_enabled": "curation_enabled",
         "evp_query": "evp_query",
         "hierarchy_depth": "hierarchy_depth",
         "integration_provider": "integration_provider",
@@ -68,6 +70,7 @@ def __init__(
         scope: str,
         updated_at: datetime,
         account_id: Union[str, none_type, UnsetType] = unset,
+        curation_enabled: Union[bool, UnsetType] = unset,
         integration_provider: Union[str, none_type, UnsetType] = unset,
         model_name: Union[str, none_type, UnsetType] = unset,
         template: Union[str, none_type, UnsetType] = unset,
@@ -82,6 +85,9 @@ def __init__(
         :param created_at: Timestamp when the configuration was created.
         :type created_at: datetime
 
+        :param curation_enabled: Whether automatic dataset curation is enabled for this configuration.
+        :type curation_enabled: bool, optional
+
         :param evp_query: Query that selects the spans the patterns run analyzes.
         :type evp_query: str
 
@@ -114,6 +120,8 @@ def __init__(
         """
         if account_id is not unset:
             kwargs["account_id"] = account_id
+        if curation_enabled is not unset:
+            kwargs["curation_enabled"] = curation_enabled
         if integration_provider is not unset:
             kwargs["integration_provider"] = integration_provider
         if model_name is not unset:

src/datadog_api_client/v2/model/llm_obs_patterns_config_item.py

@@ -30,6 +30,7 @@ def openapi_types(_):
         return {
             "account_id": (str, none_type),
             "created_at": (datetime,),
+            "curation_enabled": (bool,),
             "evp_query": (str,),
             "hierarchy_depth": (int,),
             "id": (str,),
@@ -46,6 +47,7 @@ def openapi_types(_):
     attribute_map = {
         "account_id": "account_id",
         "created_at": "created_at",
+        "curation_enabled": "curation_enabled",
         "evp_query": "evp_query",
         "hierarchy_depth": "hierarchy_depth",
         "id": "id",
@@ -71,6 +73,7 @@ def __init__(
         scope: str,
         updated_at: datetime,
         account_id: Union[str, none_type, UnsetType] = unset,
+        curation_enabled: Union[bool, UnsetType] = unset,
         integration_provider: Union[str, none_type, UnsetType] = unset,
         model_name: Union[str, none_type, UnsetType] = unset,
         template: Union[str, none_type, UnsetType] = unset,
@@ -85,6 +88,9 @@ def __init__(
         :param created_at: Timestamp when the configuration was created.
         :type created_at: datetime
 
+        :param curation_enabled: Whether automatic dataset curation is enabled for this configuration.
+        :type curation_enabled: bool, optional
+
         :param evp_query: Query that selects the spans the patterns run analyzes.
         :type evp_query: str
 
@@ -120,6 +126,8 @@ def __init__(
         """
         if account_id is not unset:
             kwargs["account_id"] = account_id
+        if curation_enabled is not unset:
+            kwargs["curation_enabled"] = curation_enabled
         if integration_provider is not unset:
             kwargs["integration_provider"] = integration_provider
         if model_name is not unset:

src/datadog_api_client/v2/model/llm_obs_patterns_config_upsert_request_attributes.py

@@ -28,6 +28,7 @@ def openapi_types(_):
         return {
             "account_id": (str,),
             "config_id": (str,),
+            "curation_enabled": (bool,),
             "evp_query": (str,),
             "hierarchy_depth": (int,),
             "integration_provider": (str,),
@@ -42,6 +43,7 @@ def openapi_types(_):
     attribute_map = {
         "account_id": "account_id",
         "config_id": "config_id",
+        "curation_enabled": "curation_enabled",
         "evp_query": "evp_query",
         "hierarchy_depth": "hierarchy_depth",
         "integration_provider": "integration_provider",
@@ -62,6 +64,7 @@ def __init__(
         sampling_ratio: float,
         account_id: Union[str, UnsetType] = unset,
         config_id: Union[str, UnsetType] = unset,
+        curation_enabled: Union[bool, UnsetType] = unset,
         integration_provider: Union[str, UnsetType] = unset,
         model_name: Union[str, UnsetType] = unset,
         scope: Union[str, UnsetType] = unset,
@@ -77,6 +80,11 @@ def __init__(
         :param config_id: The ID of an existing configuration to update. If omitted, a new configuration is created.
         :type config_id: str, optional
 
+        :param curation_enabled: When true, Datadog automatically provisions a managed project and dataset
+            ( ``{pattern-name}-pattern-curated`` ) to receive suggested interactions after
+            each run. Defaults to true for new patterns.
+        :type curation_enabled: bool, optional
+
         :param evp_query: Query that selects the spans the patterns run analyzes.
         :type evp_query: str
 
@@ -108,6 +116,8 @@ def __init__(
             kwargs["account_id"] = account_id
         if config_id is not unset:
             kwargs["config_id"] = config_id
+        if curation_enabled is not unset:
+            kwargs["curation_enabled"] = curation_enabled
         if integration_provider is not unset:
             kwargs["integration_provider"] = integration_provider
         if model_name is not unset:

tests/v2/features/llm_observability.feature

@@ -373,23 +373,31 @@ Feature: LLM Observability
   Scenario: Create or update a patterns configuration returns "Bad Request" response
     Given operation "UpsertLLMObsPatternsConfig" enabled
     And new "UpsertLLMObsPatternsConfig" request
-    And body with value {"data": {"attributes": {"account_id": "1000000001", "config_id": "a7c8d9e0-1234-5678-9abc-def012345678", "evp_query": "@ml_app:support-bot", "hierarchy_depth": 2, "integration_provider": "openai", "model_name": "gpt-4o", "name": "Support chatbot topics", "num_records": 1000, "sampling_ratio": 0.1, "scope": "", "template": ""}, "type": "topic_discovery_configs"}}
+    And body with value {"data": {"attributes": {"account_id": "1000000001", "config_id": "a7c8d9e0-1234-5678-9abc-def012345678", "curation_enabled": true, "evp_query": "@ml_app:support-bot", "hierarchy_depth": 2, "integration_provider": "openai", "model_name": "gpt-4o", "name": "Support chatbot topics", "num_records": 1000, "sampling_ratio": 0.1, "scope": "", "template": ""}, "type": "topic_discovery_configs"}}
     When the request is sent
     Then the response status is 400 Bad Request
 
+  @generated @skip @team:DataDog/ml-observability
+  Scenario: Create or update a patterns configuration returns "Conflict" response
+    Given operation "UpsertLLMObsPatternsConfig" enabled
+    And new "UpsertLLMObsPatternsConfig" request
+    And body with value {"data": {"attributes": {"account_id": "1000000001", "config_id": "a7c8d9e0-1234-5678-9abc-def012345678", "curation_enabled": true, "evp_query": "@ml_app:support-bot", "hierarchy_depth": 2, "integration_provider": "openai", "model_name": "gpt-4o", "name": "Support chatbot topics", "num_records": 1000, "sampling_ratio": 0.1, "scope": "", "template": ""}, "type": "topic_discovery_configs"}}
+    When the request is sent
+    Then the response status is 409 Conflict
+
   @generated @skip @team:DataDog/ml-observability
   Scenario: Create or update a patterns configuration returns "Not Found" response
     Given operation "UpsertLLMObsPatternsConfig" enabled
     And new "UpsertLLMObsPatternsConfig" request
-    And body with value {"data": {"attributes": {"account_id": "1000000001", "config_id": "a7c8d9e0-1234-5678-9abc-def012345678", "evp_query": "@ml_app:support-bot", "hierarchy_depth": 2, "integration_provider": "openai", "model_name": "gpt-4o", "name": "Support chatbot topics", "num_records": 1000, "sampling_ratio": 0.1, "scope": "", "template": ""}, "type": "topic_discovery_configs"}}
+    And body with value {"data": {"attributes": {"account_id": "1000000001", "config_id": "a7c8d9e0-1234-5678-9abc-def012345678", "curation_enabled": true, "evp_query": "@ml_app:support-bot", "hierarchy_depth": 2, "integration_provider": "openai", "model_name": "gpt-4o", "name": "Support chatbot topics", "num_records": 1000, "sampling_ratio": 0.1, "scope": "", "template": ""}, "type": "topic_discovery_configs"}}
     When the request is sent
     Then the response status is 404 Not Found
 
   @generated @skip @team:DataDog/ml-observability
   Scenario: Create or update a patterns configuration returns "OK" response
     Given operation "UpsertLLMObsPatternsConfig" enabled
     And new "UpsertLLMObsPatternsConfig" request
-    And body with value {"data": {"attributes": {"account_id": "1000000001", "config_id": "a7c8d9e0-1234-5678-9abc-def012345678", "evp_query": "@ml_app:support-bot", "hierarchy_depth": 2, "integration_provider": "openai", "model_name": "gpt-4o", "name": "Support chatbot topics", "num_records": 1000, "sampling_ratio": 0.1, "scope": "", "template": ""}, "type": "topic_discovery_configs"}}
+    And body with value {"data": {"attributes": {"account_id": "1000000001", "config_id": "a7c8d9e0-1234-5678-9abc-def012345678", "curation_enabled": true, "evp_query": "@ml_app:support-bot", "hierarchy_depth": 2, "integration_provider": "openai", "model_name": "gpt-4o", "name": "Support chatbot topics", "num_records": 1000, "sampling_ratio": 0.1, "scope": "", "template": ""}, "type": "topic_discovery_configs"}}
     When the request is sent
     Then the response status is 200 OK