Update annotation queue label schema
https://api.datadoghq.com/api/v2/llm-obs/v1/annotation-queues/{queue_id}/label-schemahttps://api.us3.datadoghq.com/api/v2/llm-obs/v1/annotation-queues/{queue_id}/label-schemahttps://api.us5.datadoghq.com/api/v2/llm-obs/v1/annotation-queues/{queue_id}/label-schemahttps://api.datadoghq.eu/api/v2/llm-obs/v1/annotation-queues/{queue_id}/label-schemahttps://api.ap1.datadoghq.com/api/v2/llm-obs/v1/annotation-queues/{queue_id}/label-schemahttps://api.ap2.datadoghq.com/api/v2/llm-obs/v1/annotation-queues/{queue_id}/label-schemahttps://api.uk1.datadoghq.com/api/v2/llm-obs/v1/annotation-queues/{queue_id}/label-schemahttps://api.ddog-gov.com/api/v2/llm-obs/v1/annotation-queues/{queue_id}/label-schemahttps://api.us2.ddog-gov.com/api/v2/llm-obs/v1/annotation-queues/{queue_id}/label-schemaOverview
Create or replace the label schema for a given annotation queue.
The label schema defines the labels annotators can apply to interactions in the queue.
Label names must be unique within the queue and match the pattern ^[a-zA-Z0-9_-]+$.
Each label must have a valid type: score, categorical, boolean, or text.
Arguments
Path Parameters
queue_id [required]The ID of the Agent Observability annotation queue.
Request
Body Data (required)
Update label schema payload.
data [required]Data object for updating an annotation queue label schema.
attributes [required]Attributes for updating an annotation queue label schema.
annotation_schema [required]Schema defining the labels for an annotation queue.
label_schemas [required]List of label schema definitions.
descriptionDescription of the label.
has_assessmentWhether this label includes an assessment field.
has_reasoningWhether this label includes a reasoning field.
idUnique identifier of the label schema. Assigned by the server if not provided.
is_assessmentWhether the boolean label represents an assessment. Requires has_assessment to be true.
is_integerWhether score values must be integers. Applicable to score-type labels.
is_requiredWhether this label is required for an annotation.
maxMaximum value for score-type labels.
minMinimum value for score-type labels.
name [required]Name of the label. Must match the pattern ^[a-zA-Z0-9_-]+$ and be unique within the queue.
type [required]Type of a label in an annotation queue label schema.
score, categorical, boolean, textvaluesAllowed values for categorical-type labels. Must contain at least one non-empty, unique value.
type [required]Resource type of an Agent Observability annotation queue.
queues{
"data": {
"attributes": {
"annotation_schema": {
"label_schemas": [
{
"has_assessment": true,
"is_assessment": true,
"is_required": true,
"name": "is_correct",
"type": "boolean"
}
]
}
},
"type": "queues"
}
}{
"data": {
"attributes": {
"annotation_schema": {
"label_schemas": [
{
"is_required": true,
"name": "sentiment",
"type": "categorical",
"values": [
"positive",
"negative",
"neutral"
]
}
]
}
},
"type": "queues"
}
}{
"data": {
"attributes": {
"annotation_schema": {
"label_schemas": [
{
"is_required": true,
"max": 5,
"min": 0,
"name": "quality",
"type": "score"
}
]
}
},
"type": "queues"
}
}{
"data": {
"attributes": {
"annotation_schema": {
"label_schemas": [
{
"has_reasoning": true,
"is_required": true,
"max": 5,
"min": 0,
"name": "quality",
"type": "score"
}
]
}
},
"type": "queues"
}
}{
"data": {
"attributes": {
"annotation_schema": {
"label_schemas": [
{
"is_required": false,
"name": "feedback",
"type": "text"
}
]
}
},
"type": "queues"
}
}Response
OK
Response containing the label schema of an annotation queue.
data [required]Data object for an annotation queue label schema.
attributes [required]Attributes of an annotation queue label schema.
annotation_schema [required]Schema defining the labels for an annotation queue.
label_schemas [required]List of label schema definitions.
descriptionDescription of the label.
has_assessmentWhether this label includes an assessment field.
has_reasoningWhether this label includes a reasoning field.
idUnique identifier of the label schema. Assigned by the server if not provided.
is_assessmentWhether the boolean label represents an assessment. Requires has_assessment to be true.
is_integerWhether score values must be integers. Applicable to score-type labels.
is_requiredWhether this label is required for an annotation.
maxMaximum value for score-type labels.
minMinimum value for score-type labels.
name [required]Name of the label. Must match the pattern ^[a-zA-Z0-9_-]+$ and be unique within the queue.
type [required]Type of a label in an annotation queue label schema.
score, categorical, boolean, textvaluesAllowed values for categorical-type labels. Must contain at least one non-empty, unique value.
id [required]Unique identifier of the annotation queue.
type [required]Resource type of an Agent Observability annotation queue.
queues{
"data": {
"attributes": {
"annotation_schema": {
"label_schemas": [
{
"description": "Rating of the response quality.",
"has_assessment": false,
"has_reasoning": false,
"id": "abc-123",
"is_assessment": false,
"is_integer": false,
"is_required": true,
"max": 5,
"min": 0,
"name": "quality",
"type": "score",
"values": [
"good",
"bad",
"neutral"
]
}
]
}
},
"id": "00000000-0000-0000-0000-000000000001",
"type": "queues"
}
}Bad Request
API error response.
errors [required]A list of errors.
detailA human-readable explanation specific to this occurrence of the error.
metaNon-standard meta-information about the error
sourceReferences to the source of the error.
headerA string indicating the name of a single request header which caused the error.
parameterA string indicating which URI query parameter caused the error.
pointerA JSON pointer to the value in the request document that caused the error.
statusStatus code of the response.
titleShort human-readable summary of the error.
{
"errors": [
{
"detail": "Missing required attribute in body",
"meta": {},
"source": {
"header": "Authorization",
"parameter": "limit",
"pointer": "/data/attributes/title"
},
"status": "400",
"title": "Bad Request"
}
]
}Unauthorized
API error response.
errors [required]A list of errors.
detailA human-readable explanation specific to this occurrence of the error.
metaNon-standard meta-information about the error
sourceReferences to the source of the error.
headerA string indicating the name of a single request header which caused the error.
parameterA string indicating which URI query parameter caused the error.
pointerA JSON pointer to the value in the request document that caused the error.
statusStatus code of the response.
titleShort human-readable summary of the error.
{
"errors": [
{
"detail": "Missing required attribute in body",
"meta": {},
"source": {
"header": "Authorization",
"parameter": "limit",
"pointer": "/data/attributes/title"
},
"status": "400",
"title": "Bad Request"
}
]
}Forbidden
API error response.
errors [required]A list of errors.
detailA human-readable explanation specific to this occurrence of the error.
metaNon-standard meta-information about the error
sourceReferences to the source of the error.
headerA string indicating the name of a single request header which caused the error.
parameterA string indicating which URI query parameter caused the error.
pointerA JSON pointer to the value in the request document that caused the error.
statusStatus code of the response.
titleShort human-readable summary of the error.
{
"errors": [
{
"detail": "Missing required attribute in body",
"meta": {},
"source": {
"header": "Authorization",
"parameter": "limit",
"pointer": "/data/attributes/title"
},
"status": "400",
"title": "Bad Request"
}
]
}Not Found
API error response.
errors [required]A list of errors.
detailA human-readable explanation specific to this occurrence of the error.
metaNon-standard meta-information about the error
sourceReferences to the source of the error.
headerA string indicating the name of a single request header which caused the error.
parameterA string indicating which URI query parameter caused the error.
pointerA JSON pointer to the value in the request document that caused the error.
statusStatus code of the response.
titleShort human-readable summary of the error.
{
"errors": [
{
"detail": "Missing required attribute in body",
"meta": {},
"source": {
"header": "Authorization",
"parameter": "limit",
"pointer": "/data/attributes/title"
},
"status": "400",
"title": "Bad Request"
}
]
}Too many requests
API error response.
errors [required]A list of errors.
{
"errors": [
"Bad Request"
]
}Internal Server Error
API error response.
errors [required]A list of errors.
detailA human-readable explanation specific to this occurrence of the error.
metaNon-standard meta-information about the error
sourceReferences to the source of the error.
headerA string indicating the name of a single request header which caused the error.
parameterA string indicating which URI query parameter caused the error.
pointerA JSON pointer to the value in the request document that caused the error.
statusStatus code of the response.
titleShort human-readable summary of the error.
{
"errors": [
{
"detail": "Missing required attribute in body",
"meta": {},
"source": {
"header": "Authorization",
"parameter": "limit",
"pointer": "/data/attributes/title"
},
"status": "400",
"title": "Bad Request"
}
]
}Code Example
# Path parameters
export queue_id="00000000-0000-0000-0000-000000000001"
# Set your Datadog site and credentials
export DD_SITE="datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X PUT "https://api.${DD_SITE}/api/v2/llm-obs/v1/annotation-queues/${queue_id}/label-schema" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"annotation_schema": {
"label_schemas": [
{
"has_assessment": true,
"is_assessment": true,
"is_required": true,
"name": "is_correct",
"type": "boolean"
}
]
}
},
"type": "queues"
}
}
EOF# Path parameters
export queue_id="00000000-0000-0000-0000-000000000001"
# Set your Datadog site and credentials
export DD_SITE="us3.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X PUT "https://api.${DD_SITE}/api/v2/llm-obs/v1/annotation-queues/${queue_id}/label-schema" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"annotation_schema": {
"label_schemas": [
{
"has_assessment": true,
"is_assessment": true,
"is_required": true,
"name": "is_correct",
"type": "boolean"
}
]
}
},
"type": "queues"
}
}
EOF# Path parameters
export queue_id="00000000-0000-0000-0000-000000000001"
# Set your Datadog site and credentials
export DD_SITE="us5.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X PUT "https://api.${DD_SITE}/api/v2/llm-obs/v1/annotation-queues/${queue_id}/label-schema" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"annotation_schema": {
"label_schemas": [
{
"has_assessment": true,
"is_assessment": true,
"is_required": true,
"name": "is_correct",
"type": "boolean"
}
]
}
},
"type": "queues"
}
}
EOF# Path parameters
export queue_id="00000000-0000-0000-0000-000000000001"
# Set your Datadog site and credentials
export DD_SITE="datadoghq.eu"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X PUT "https://api.${DD_SITE}/api/v2/llm-obs/v1/annotation-queues/${queue_id}/label-schema" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"annotation_schema": {
"label_schemas": [
{
"has_assessment": true,
"is_assessment": true,
"is_required": true,
"name": "is_correct",
"type": "boolean"
}
]
}
},
"type": "queues"
}
}
EOF# Path parameters
export queue_id="00000000-0000-0000-0000-000000000001"
# Set your Datadog site and credentials
export DD_SITE="ap1.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X PUT "https://api.${DD_SITE}/api/v2/llm-obs/v1/annotation-queues/${queue_id}/label-schema" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"annotation_schema": {
"label_schemas": [
{
"has_assessment": true,
"is_assessment": true,
"is_required": true,
"name": "is_correct",
"type": "boolean"
}
]
}
},
"type": "queues"
}
}
EOF# Path parameters
export queue_id="00000000-0000-0000-0000-000000000001"
# Set your Datadog site and credentials
export DD_SITE="ap2.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X PUT "https://api.${DD_SITE}/api/v2/llm-obs/v1/annotation-queues/${queue_id}/label-schema" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"annotation_schema": {
"label_schemas": [
{
"has_assessment": true,
"is_assessment": true,
"is_required": true,
"name": "is_correct",
"type": "boolean"
}
]
}
},
"type": "queues"
}
}
EOF# Path parameters
export queue_id="00000000-0000-0000-0000-000000000001"
# Set your Datadog site and credentials
export DD_SITE="uk1.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X PUT "https://api.${DD_SITE}/api/v2/llm-obs/v1/annotation-queues/${queue_id}/label-schema" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"annotation_schema": {
"label_schemas": [
{
"has_assessment": true,
"is_assessment": true,
"is_required": true,
"name": "is_correct",
"type": "boolean"
}
]
}
},
"type": "queues"
}
}
EOF# Path parameters
export queue_id="00000000-0000-0000-0000-000000000001"
# Set your Datadog site and credentials
export DD_SITE="ddog-gov.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X PUT "https://api.${DD_SITE}/api/v2/llm-obs/v1/annotation-queues/${queue_id}/label-schema" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"annotation_schema": {
"label_schemas": [
{
"has_assessment": true,
"is_assessment": true,
"is_required": true,
"name": "is_correct",
"type": "boolean"
}
]
}
},
"type": "queues"
}
}
EOF# Path parameters
export queue_id="00000000-0000-0000-0000-000000000001"
# Set your Datadog site and credentials
export DD_SITE="us2.ddog-gov.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X PUT "https://api.${DD_SITE}/api/v2/llm-obs/v1/annotation-queues/${queue_id}/label-schema" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"annotation_schema": {
"label_schemas": [
{
"has_assessment": true,
"is_assessment": true,
"is_required": true,
"name": "is_correct",
"type": "boolean"
}
]
}
},
"type": "queues"
}
}
EOF// Update annotation queue label schema returns "OK" response
package main
import (
"context"
"encoding/json"
"fmt"
"os"
"github.com/DataDog/datadog-api-client-go/v2/api/datadog"
"github.com/DataDog/datadog-api-client-go/v2/api/datadogV2"
)
func main() {
body := datadogV2.LLMObsAnnotationQueueLabelSchemaUpdateRequest{
Data: datadogV2.LLMObsAnnotationQueueLabelSchemaUpdateData{
Attributes: datadogV2.LLMObsAnnotationQueueLabelSchemaUpdateAttributes{
AnnotationSchema: datadogV2.LLMObsAnnotationSchema{
LabelSchemas: []datadogV2.LLMObsLabelSchema{
{
Description: datadog.PtrString("Rating of the response quality."),
HasAssessment: datadog.PtrBool(false),
HasReasoning: datadog.PtrBool(false),
Id: datadog.PtrString("abc-123"),
IsAssessment: datadog.PtrBool(false),
IsInteger: datadog.PtrBool(false),
IsRequired: datadog.PtrBool(true),
Max: datadog.PtrFloat64(5.0),
Min: datadog.PtrFloat64(0.0),
Name: "quality",
Type: datadogV2.LLMOBSLABELSCHEMATYPE_SCORE,
Values: []string{
"good",
"bad",
"neutral",
},
},
},
},
},
Type: datadogV2.LLMOBSANNOTATIONQUEUETYPE_QUEUES,
},
}
ctx := datadog.NewDefaultContext(context.Background())
ctx = context.WithValue(ctx, datadog.ContextAccessToken, os.Getenv("DD_BEARER_TOKEN"))
configuration := datadog.NewConfiguration()
configuration.SetUnstableOperationEnabled("v2.UpdateLLMObsAnnotationQueueLabelSchema", true)
apiClient := datadog.NewAPIClient(configuration)
api := datadogV2.NewAgentObservabilityApi(apiClient)
resp, r, err := api.UpdateLLMObsAnnotationQueueLabelSchema(ctx, "queue_id", body)
if err != nil {
fmt.Fprintf(os.Stderr, "Error when calling `AgentObservabilityApi.UpdateLLMObsAnnotationQueueLabelSchema`: %v\n", err)
fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
}
responseContent, _ := json.MarshalIndent(resp, "", " ")
fmt.Fprintf(os.Stdout, "Response from `AgentObservabilityApi.UpdateLLMObsAnnotationQueueLabelSchema`:\n%s\n", responseContent)
}
Instructions
First install the library and its dependencies and then save the example to main.go and run following commands:
DD_SITE="datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"DD_SITE="us3.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"DD_SITE="us5.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"DD_SITE="datadoghq.eu" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"DD_SITE="ap1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"DD_SITE="ap2.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"DD_SITE="uk1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"DD_SITE="ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"DD_SITE="us2.ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"// Update annotation queue label schema returns "OK" response
import com.datadog.api.client.ApiClient;
import com.datadog.api.client.ApiException;
import com.datadog.api.client.v2.api.AgentObservabilityApi;
import com.datadog.api.client.v2.model.LLMObsAnnotationQueueLabelSchemaResponse;
import com.datadog.api.client.v2.model.LLMObsAnnotationQueueLabelSchemaUpdateAttributes;
import com.datadog.api.client.v2.model.LLMObsAnnotationQueueLabelSchemaUpdateData;
import com.datadog.api.client.v2.model.LLMObsAnnotationQueueLabelSchemaUpdateRequest;
import com.datadog.api.client.v2.model.LLMObsAnnotationQueueType;
import com.datadog.api.client.v2.model.LLMObsAnnotationSchema;
import com.datadog.api.client.v2.model.LLMObsLabelSchema;
import com.datadog.api.client.v2.model.LLMObsLabelSchemaType;
import java.util.Arrays;
import java.util.Collections;
public class Example {
public static void main(String[] args) {
ApiClient defaultClient = ApiClient.getDefaultApiClient();
defaultClient.setAccessToken(System.getenv("DD_BEARER_TOKEN"));
defaultClient.setUnstableOperationEnabled("v2.updateLLMObsAnnotationQueueLabelSchema", true);
AgentObservabilityApi apiInstance = new AgentObservabilityApi(defaultClient);
LLMObsAnnotationQueueLabelSchemaUpdateRequest body =
new LLMObsAnnotationQueueLabelSchemaUpdateRequest()
.data(
new LLMObsAnnotationQueueLabelSchemaUpdateData()
.attributes(
new LLMObsAnnotationQueueLabelSchemaUpdateAttributes()
.annotationSchema(
new LLMObsAnnotationSchema()
.labelSchemas(
Collections.singletonList(
new LLMObsLabelSchema()
.description("Rating of the response quality.")
.hasAssessment(false)
.hasReasoning(false)
.id("abc-123")
.isAssessment(false)
.isInteger(false)
.isRequired(true)
.max(5.0)
.name("quality")
.type(LLMObsLabelSchemaType.SCORE)
.values(Arrays.asList("good", "bad", "neutral"))))))
.type(LLMObsAnnotationQueueType.QUEUES));
try {
LLMObsAnnotationQueueLabelSchemaResponse result =
apiInstance.updateLLMObsAnnotationQueueLabelSchema(
"00000000-0000-0000-0000-000000000001", body);
System.out.println(result);
} catch (ApiException e) {
System.err.println(
"Exception when calling AgentObservabilityApi#updateLLMObsAnnotationQueueLabelSchema");
System.err.println("Status code: " + e.getCode());
System.err.println("Reason: " + e.getResponseBody());
System.err.println("Response headers: " + e.getResponseHeaders());
e.printStackTrace();
}
}
}
Instructions
First install the library and its dependencies and then save the example to Example.java and run following commands:
DD_SITE="datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"DD_SITE="us3.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"DD_SITE="us5.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"DD_SITE="datadoghq.eu" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"DD_SITE="ap1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"DD_SITE="ap2.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"DD_SITE="uk1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"DD_SITE="ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"DD_SITE="us2.ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java""""
Update annotation queue label schema returns "OK" response
"""
from os import environ
from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.agent_observability_api import AgentObservabilityApi
from datadog_api_client.v2.model.llm_obs_annotation_queue_label_schema_update_attributes import (
LLMObsAnnotationQueueLabelSchemaUpdateAttributes,
)
from datadog_api_client.v2.model.llm_obs_annotation_queue_label_schema_update_data import (
LLMObsAnnotationQueueLabelSchemaUpdateData,
)
from datadog_api_client.v2.model.llm_obs_annotation_queue_label_schema_update_request import (
LLMObsAnnotationQueueLabelSchemaUpdateRequest,
)
from datadog_api_client.v2.model.llm_obs_annotation_queue_type import LLMObsAnnotationQueueType
from datadog_api_client.v2.model.llm_obs_annotation_schema import LLMObsAnnotationSchema
from datadog_api_client.v2.model.llm_obs_label_schema import LLMObsLabelSchema
from datadog_api_client.v2.model.llm_obs_label_schema_type import LLMObsLabelSchemaType
body = LLMObsAnnotationQueueLabelSchemaUpdateRequest(
data=LLMObsAnnotationQueueLabelSchemaUpdateData(
attributes=LLMObsAnnotationQueueLabelSchemaUpdateAttributes(
annotation_schema=LLMObsAnnotationSchema(
label_schemas=[
LLMObsLabelSchema(
description="Rating of the response quality.",
has_assessment=False,
has_reasoning=False,
id="abc-123",
is_assessment=False,
is_integer=False,
is_required=True,
max=5.0,
min=0.0,
name="quality",
type=LLMObsLabelSchemaType.SCORE,
values=[
"good",
"bad",
"neutral",
],
),
],
),
),
type=LLMObsAnnotationQueueType.QUEUES,
),
)
configuration = Configuration()
configuration.access_token = environ["DD_BEARER_TOKEN"]
configuration.unstable_operations["update_llm_obs_annotation_queue_label_schema"] = True
with ApiClient(configuration) as api_client:
api_instance = AgentObservabilityApi(api_client)
response = api_instance.update_llm_obs_annotation_queue_label_schema(queue_id="queue_id", body=body)
print(response)
Instructions
First install the library and its dependencies and then save the example to example.py and run following commands:
DD_SITE="datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"DD_SITE="us3.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"DD_SITE="us5.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"DD_SITE="datadoghq.eu" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"DD_SITE="ap1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"DD_SITE="ap2.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"DD_SITE="uk1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"DD_SITE="ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"DD_SITE="us2.ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"# Update annotation queue label schema returns "OK" response
require "datadog_api_client"
DatadogAPIClient.configure do |config|
config.access_token = ENV["DD_BEARER_TOKEN"]
config.unstable_operations["v2.update_llm_obs_annotation_queue_label_schema".to_sym] = true
end
api_instance = DatadogAPIClient::V2::AgentObservabilityAPI.new
body = DatadogAPIClient::V2::LLMObsAnnotationQueueLabelSchemaUpdateRequest.new({
data: DatadogAPIClient::V2::LLMObsAnnotationQueueLabelSchemaUpdateData.new({
attributes: DatadogAPIClient::V2::LLMObsAnnotationQueueLabelSchemaUpdateAttributes.new({
annotation_schema: DatadogAPIClient::V2::LLMObsAnnotationSchema.new({
label_schemas: [
DatadogAPIClient::V2::LLMObsLabelSchema.new({
description: "Rating of the response quality.",
has_assessment: false,
has_reasoning: false,
id: "abc-123",
is_assessment: false,
is_integer: false,
is_required: true,
max: 5.0,
min: 0.0,
name: "quality",
type: DatadogAPIClient::V2::LLMObsLabelSchemaType::SCORE,
values: [
"good",
"bad",
"neutral",
],
}),
],
}),
}),
type: DatadogAPIClient::V2::LLMObsAnnotationQueueType::QUEUES,
}),
})
p api_instance.update_llm_obs_annotation_queue_label_schema("queue_id", body)
Instructions
First install the library and its dependencies and then save the example to example.rb and run following commands:
DD_SITE="datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"DD_SITE="us3.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"DD_SITE="us5.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"DD_SITE="datadoghq.eu" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"DD_SITE="ap1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"DD_SITE="ap2.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"DD_SITE="uk1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"DD_SITE="ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"DD_SITE="us2.ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"// Update annotation queue label schema returns "OK" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_agent_observability::AgentObservabilityAPI;
use datadog_api_client::datadogV2::model::LLMObsAnnotationQueueLabelSchemaUpdateAttributes;
use datadog_api_client::datadogV2::model::LLMObsAnnotationQueueLabelSchemaUpdateData;
use datadog_api_client::datadogV2::model::LLMObsAnnotationQueueLabelSchemaUpdateRequest;
use datadog_api_client::datadogV2::model::LLMObsAnnotationQueueType;
use datadog_api_client::datadogV2::model::LLMObsAnnotationSchema;
use datadog_api_client::datadogV2::model::LLMObsLabelSchema;
use datadog_api_client::datadogV2::model::LLMObsLabelSchemaType;
#[tokio::main]
async fn main() {
let body = LLMObsAnnotationQueueLabelSchemaUpdateRequest::new(
LLMObsAnnotationQueueLabelSchemaUpdateData::new(
LLMObsAnnotationQueueLabelSchemaUpdateAttributes::new(LLMObsAnnotationSchema::new(
vec![
LLMObsLabelSchema::new("quality".to_string(), LLMObsLabelSchemaType::SCORE)
.description("Rating of the response quality.".to_string())
.has_assessment(false)
.has_reasoning(false)
.id("abc-123".to_string())
.is_assessment(false)
.is_integer(false)
.is_required(true)
.max(5.0 as f64)
.min(0.0 as f64)
.values(vec![
"good".to_string(),
"bad".to_string(),
"neutral".to_string(),
]),
],
)),
LLMObsAnnotationQueueType::QUEUES,
),
);
let mut configuration = datadog::Configuration::new();
configuration
.set_unstable_operation_enabled("v2.update_llm_obs_annotation_queue_label_schema", true);
let api = AgentObservabilityAPI::with_config(configuration);
let resp = api
.update_llm_obs_annotation_queue_label_schema("queue_id".to_string(), body)
.await;
if let Ok(value) = resp {
println!("{:#?}", value);
} else {
println!("{:#?}", resp.unwrap_err());
}
}
Instructions
First install the library and its dependencies and then save the example to src/main.rs and run following commands:
DD_SITE="datadoghq.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo runDD_SITE="us3.datadoghq.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo runDD_SITE="us5.datadoghq.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo runDD_SITE="datadoghq.eu" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo runDD_SITE="ap1.datadoghq.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo runDD_SITE="ap2.datadoghq.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo runDD_SITE="uk1.datadoghq.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo runDD_SITE="ddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo runDD_SITE="us2.ddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo run/**
* Update annotation queue label schema returns "OK" response
*/
import { client, v2 } from "@datadog/datadog-api-client";
const configuration = client.createConfiguration({
authMethods: {
AuthZ: {
accessToken: process.env.DD_BEARER_TOKEN as string,
},
},
});
configuration.unstableOperations["v2.updateLLMObsAnnotationQueueLabelSchema"] =
true;
const apiInstance = new v2.AgentObservabilityApi(configuration);
const params: v2.AgentObservabilityApiUpdateLLMObsAnnotationQueueLabelSchemaRequest =
{
body: {
data: {
attributes: {
annotationSchema: {
labelSchemas: [
{
description: "Rating of the response quality.",
hasAssessment: false,
hasReasoning: false,
id: "abc-123",
isAssessment: false,
isInteger: false,
isRequired: true,
max: 5.0,
min: 0.0,
name: "quality",
type: "score",
values: ["good", "bad", "neutral"],
},
],
},
},
type: "queues",
},
},
queueId: "queue_id",
};
apiInstance
.updateLLMObsAnnotationQueueLabelSchema(params)
.then((data: v2.LLMObsAnnotationQueueLabelSchemaResponse) => {
console.log(
"API called successfully. Returned data: " + JSON.stringify(data)
);
})
.catch((error: any) => console.error(error));
Instructions
First install the library and its dependencies and then save the example to example.ts and run following commands:
DD_SITE="datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"DD_SITE="us3.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"DD_SITE="us5.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"DD_SITE="datadoghq.eu" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"DD_SITE="ap1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"DD_SITE="ap2.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"DD_SITE="uk1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"DD_SITE="ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"DD_SITE="us2.ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"