Batch update Agent Observability dataset records
https://api.datadoghq.com/api/v2/llm-obs/v1/{project_id}/datasets/{dataset_id}/batch_updatehttps://api.us3.datadoghq.com/api/v2/llm-obs/v1/{project_id}/datasets/{dataset_id}/batch_updatehttps://api.us5.datadoghq.com/api/v2/llm-obs/v1/{project_id}/datasets/{dataset_id}/batch_updatehttps://api.datadoghq.eu/api/v2/llm-obs/v1/{project_id}/datasets/{dataset_id}/batch_updatehttps://api.ap1.datadoghq.com/api/v2/llm-obs/v1/{project_id}/datasets/{dataset_id}/batch_updatehttps://api.ap2.datadoghq.com/api/v2/llm-obs/v1/{project_id}/datasets/{dataset_id}/batch_updatehttps://api.uk1.datadoghq.com/api/v2/llm-obs/v1/{project_id}/datasets/{dataset_id}/batch_updatehttps://api.ddog-gov.com/api/v2/llm-obs/v1/{project_id}/datasets/{dataset_id}/batch_updatehttps://api.us2.ddog-gov.com/api/v2/llm-obs/v1/{project_id}/datasets/{dataset_id}/batch_updateDescripción general
Insert, update, and delete records in a single dataset operation. By default, a new dataset version is created when the batch is applied.
Argumentos
Parámetros de ruta
project_id [required]The ID of the Agent Observability project.
dataset_id [required]The ID of the Agent Observability dataset.
Solicitud
Body Data (required)
Batch update payload.
data [required]Data object for batch-updating records in an Agent Observability dataset.
attributes [required]Attributes for batch-updating records in an Agent Observability dataset.
create_new_versionWhether to create a new dataset version when applying the batch update. Defaults to true.
delete_recordsRecord IDs to delete.
insert_recordsRecords to insert.
expected_outputRepresents any valid JSON value.
Object 1A scalar value represented as a string.
Object 2A scalar numeric value.
Object 3An arbitrary object value with additional properties.
Object 4An array of arbitrary values.
Object 1A scalar value represented as a string.
Object 2A scalar numeric value.
Object 3An arbitrary object value with additional properties.
Object 4A scalar boolean value.
Object 5A scalar boolean value.
idOptional user-provided identifier for the record. If omitted, the server generates an identifier.
input [required]Represents any valid JSON value.
Object 1A scalar value represented as a string.
Object 2A scalar numeric value.
Object 3An arbitrary object value with additional properties.
Object 4An array of arbitrary values.
Object 1A scalar value represented as a string.
Object 2A scalar numeric value.
Object 3An arbitrary object value with additional properties.
Object 4A scalar boolean value.
Object 5A scalar boolean value.
metadataArbitrary metadata associated with the record.
tag_operationsExplicit tag operations for updating records. Operations are applied in order, Remove then Add then Set. set is the final override; if specified, the result of remove and add is discarded.
addList of tag strings.
removeList of tag strings.
setList of tag strings.
tagsList of tag strings.
tagsList of tag strings.
update_recordsRecords to update by ID.
expected_outputRepresents any valid JSON value.
Object 1A scalar value represented as a string.
Object 2A scalar numeric value.
Object 3An arbitrary object value with additional properties.
Object 4An array of arbitrary values.
Object 1A scalar value represented as a string.
Object 2A scalar numeric value.
Object 3An arbitrary object value with additional properties.
Object 4A scalar boolean value.
Object 5A scalar boolean value.
id [required]Unique identifier of the record to update.
inputRepresents any valid JSON value.
Object 1A scalar value represented as a string.
Object 2A scalar numeric value.
Object 3An arbitrary object value with additional properties.
Object 4An array of arbitrary values.
Object 1A scalar value represented as a string.
Object 2A scalar numeric value.
Object 3An arbitrary object value with additional properties.
Object 4A scalar boolean value.
Object 5A scalar boolean value.
metadataUpdated metadata associated with the record.
tag_operationsExplicit tag operations for updating records. Operations are applied in order, Remove then Add then Set. set is the final override; if specified, the result of remove and add is discarded.
addList of tag strings.
removeList of tag strings.
setList of tag strings.
id [required]Unique identifier of the dataset.
type [required]Resource type of an Agent Observability dataset.
datasets{
"data": {
"attributes": {
"create_new_version": true,
"delete_records": [],
"insert_records": [
{
"expected_output": {
"description": "undefined",
"type": "undefined"
},
"id": "rec-7c3f5a1b-9e2d-4f8a-b1c6-3d7e9f0a2b4c",
"input": {
"description": "undefined",
"type": "undefined"
},
"metadata": {},
"tag_operations": {
"add": [],
"remove": [],
"set": []
},
"tags": []
}
],
"tags": [],
"update_records": [
{
"expected_output": {
"description": "undefined",
"type": "undefined"
},
"id": "rec-7c3f5a1b-9e2d-4f8a-b1c6-3d7e9f0a2b4c",
"input": {
"description": "undefined",
"type": "undefined"
},
"metadata": {},
"tag_operations": {
"add": [],
"remove": [],
"set": []
}
}
]
},
"id": "9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d",
"type": "datasets"
}
}Respuesta
OK
Response containing records after a create or update operation.
data [required]List of affected dataset records.
records [required]List of affected dataset records.
created_at [required]Timestamp when the record was created.
dataset_id [required]Identifier of the dataset this record belongs to.
expected_output [required]Represents any valid JSON value.
Object 1A scalar value represented as a string.
Object 2A scalar numeric value.
Object 3An arbitrary object value with additional properties.
Object 4An array of arbitrary values.
Object 1A scalar value represented as a string.
Object 2A scalar numeric value.
Object 3An arbitrary object value with additional properties.
Object 4A scalar boolean value.
Object 5A scalar boolean value.
id [required]Unique identifier of the record.
input [required]Represents any valid JSON value.
Object 1A scalar value represented as a string.
Object 2A scalar numeric value.
Object 3An arbitrary object value with additional properties.
Object 4An array of arbitrary values.
Object 1A scalar value represented as a string.
Object 2A scalar numeric value.
Object 3An arbitrary object value with additional properties.
Object 4A scalar boolean value.
Object 5A scalar boolean value.
metadata [required]Arbitrary metadata associated with the record.
updated_at [required]Timestamp when the record was last updated.
{
"data": [
{
"records": [
{
"created_at": "2024-01-15T10:30:00Z",
"dataset_id": "9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d",
"expected_output": {
"description": "undefined",
"type": "undefined"
},
"id": "rec-7c3f5a1b-9e2d-4f8a-b1c6-3d7e9f0a2b4c",
"input": {
"description": "undefined",
"type": "undefined"
},
"metadata": {},
"updated_at": "2024-01-15T10:30:00Z"
}
]
}
]
}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"
}
]
}Payload Too Large
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"
}
]
}Ejemplo de código
# Path parameters
export project_id="a33671aa-24fd-4dcd-9b33-a8ec7dde7751"
export dataset_id="9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d"
# 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 POST "https://api.${DD_SITE}/api/v2/llm-obs/v1/${project_id}/datasets/${dataset_id}/batch_update" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"create_new_version": true,
"delete_records": [
"rec-old-record-1"
],
"insert_records": [
{
"expected_output": {
"answer": "Paris"
},
"input": {
"question": "What is the capital of France?"
},
"tags": [
"topic:geography"
]
}
],
"update_records": [
{
"expected_output": {
"answer": "Paris, France"
},
"id": "rec-7c3f5a1b-9e2d-4f8a-b1c6-3d7e9f0a2b4c"
}
]
},
"id": "9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d",
"type": "datasets"
}
}
EOF# Path parameters
export project_id="a33671aa-24fd-4dcd-9b33-a8ec7dde7751"
export dataset_id="9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d"
# Set your Datadog site and credentials
export DD_SITE="us3.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X POST "https://api.${DD_SITE}/api/v2/llm-obs/v1/${project_id}/datasets/${dataset_id}/batch_update" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"create_new_version": true,
"delete_records": [
"rec-old-record-1"
],
"insert_records": [
{
"expected_output": {
"answer": "Paris"
},
"input": {
"question": "What is the capital of France?"
},
"tags": [
"topic:geography"
]
}
],
"update_records": [
{
"expected_output": {
"answer": "Paris, France"
},
"id": "rec-7c3f5a1b-9e2d-4f8a-b1c6-3d7e9f0a2b4c"
}
]
},
"id": "9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d",
"type": "datasets"
}
}
EOF# Path parameters
export project_id="a33671aa-24fd-4dcd-9b33-a8ec7dde7751"
export dataset_id="9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d"
# Set your Datadog site and credentials
export DD_SITE="us5.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X POST "https://api.${DD_SITE}/api/v2/llm-obs/v1/${project_id}/datasets/${dataset_id}/batch_update" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"create_new_version": true,
"delete_records": [
"rec-old-record-1"
],
"insert_records": [
{
"expected_output": {
"answer": "Paris"
},
"input": {
"question": "What is the capital of France?"
},
"tags": [
"topic:geography"
]
}
],
"update_records": [
{
"expected_output": {
"answer": "Paris, France"
},
"id": "rec-7c3f5a1b-9e2d-4f8a-b1c6-3d7e9f0a2b4c"
}
]
},
"id": "9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d",
"type": "datasets"
}
}
EOF# Path parameters
export project_id="a33671aa-24fd-4dcd-9b33-a8ec7dde7751"
export dataset_id="9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d"
# Set your Datadog site and credentials
export DD_SITE="datadoghq.eu"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X POST "https://api.${DD_SITE}/api/v2/llm-obs/v1/${project_id}/datasets/${dataset_id}/batch_update" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"create_new_version": true,
"delete_records": [
"rec-old-record-1"
],
"insert_records": [
{
"expected_output": {
"answer": "Paris"
},
"input": {
"question": "What is the capital of France?"
},
"tags": [
"topic:geography"
]
}
],
"update_records": [
{
"expected_output": {
"answer": "Paris, France"
},
"id": "rec-7c3f5a1b-9e2d-4f8a-b1c6-3d7e9f0a2b4c"
}
]
},
"id": "9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d",
"type": "datasets"
}
}
EOF# Path parameters
export project_id="a33671aa-24fd-4dcd-9b33-a8ec7dde7751"
export dataset_id="9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d"
# Set your Datadog site and credentials
export DD_SITE="ap1.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X POST "https://api.${DD_SITE}/api/v2/llm-obs/v1/${project_id}/datasets/${dataset_id}/batch_update" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"create_new_version": true,
"delete_records": [
"rec-old-record-1"
],
"insert_records": [
{
"expected_output": {
"answer": "Paris"
},
"input": {
"question": "What is the capital of France?"
},
"tags": [
"topic:geography"
]
}
],
"update_records": [
{
"expected_output": {
"answer": "Paris, France"
},
"id": "rec-7c3f5a1b-9e2d-4f8a-b1c6-3d7e9f0a2b4c"
}
]
},
"id": "9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d",
"type": "datasets"
}
}
EOF# Path parameters
export project_id="a33671aa-24fd-4dcd-9b33-a8ec7dde7751"
export dataset_id="9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d"
# Set your Datadog site and credentials
export DD_SITE="ap2.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X POST "https://api.${DD_SITE}/api/v2/llm-obs/v1/${project_id}/datasets/${dataset_id}/batch_update" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"create_new_version": true,
"delete_records": [
"rec-old-record-1"
],
"insert_records": [
{
"expected_output": {
"answer": "Paris"
},
"input": {
"question": "What is the capital of France?"
},
"tags": [
"topic:geography"
]
}
],
"update_records": [
{
"expected_output": {
"answer": "Paris, France"
},
"id": "rec-7c3f5a1b-9e2d-4f8a-b1c6-3d7e9f0a2b4c"
}
]
},
"id": "9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d",
"type": "datasets"
}
}
EOF# Path parameters
export project_id="a33671aa-24fd-4dcd-9b33-a8ec7dde7751"
export dataset_id="9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d"
# Set your Datadog site and credentials
export DD_SITE="uk1.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X POST "https://api.${DD_SITE}/api/v2/llm-obs/v1/${project_id}/datasets/${dataset_id}/batch_update" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"create_new_version": true,
"delete_records": [
"rec-old-record-1"
],
"insert_records": [
{
"expected_output": {
"answer": "Paris"
},
"input": {
"question": "What is the capital of France?"
},
"tags": [
"topic:geography"
]
}
],
"update_records": [
{
"expected_output": {
"answer": "Paris, France"
},
"id": "rec-7c3f5a1b-9e2d-4f8a-b1c6-3d7e9f0a2b4c"
}
]
},
"id": "9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d",
"type": "datasets"
}
}
EOF# Path parameters
export project_id="a33671aa-24fd-4dcd-9b33-a8ec7dde7751"
export dataset_id="9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d"
# Set your Datadog site and credentials
export DD_SITE="ddog-gov.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X POST "https://api.${DD_SITE}/api/v2/llm-obs/v1/${project_id}/datasets/${dataset_id}/batch_update" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"create_new_version": true,
"delete_records": [
"rec-old-record-1"
],
"insert_records": [
{
"expected_output": {
"answer": "Paris"
},
"input": {
"question": "What is the capital of France?"
},
"tags": [
"topic:geography"
]
}
],
"update_records": [
{
"expected_output": {
"answer": "Paris, France"
},
"id": "rec-7c3f5a1b-9e2d-4f8a-b1c6-3d7e9f0a2b4c"
}
]
},
"id": "9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d",
"type": "datasets"
}
}
EOF# Path parameters
export project_id="a33671aa-24fd-4dcd-9b33-a8ec7dde7751"
export dataset_id="9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d"
# Set your Datadog site and credentials
export DD_SITE="us2.ddog-gov.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X POST "https://api.${DD_SITE}/api/v2/llm-obs/v1/${project_id}/datasets/${dataset_id}/batch_update" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"create_new_version": true,
"delete_records": [
"rec-old-record-1"
],
"insert_records": [
{
"expected_output": {
"answer": "Paris"
},
"input": {
"question": "What is the capital of France?"
},
"tags": [
"topic:geography"
]
}
],
"update_records": [
{
"expected_output": {
"answer": "Paris, France"
},
"id": "rec-7c3f5a1b-9e2d-4f8a-b1c6-3d7e9f0a2b4c"
}
]
},
"id": "9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d",
"type": "datasets"
}
}
EOF// Batch update Agent Observability dataset records 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.LLMObsDatasetBatchUpdateRequest{
Data: datadogV2.LLMObsDatasetBatchUpdateDataRequest{
Attributes: datadogV2.LLMObsDatasetBatchUpdateDataAttributesRequest{
CreateNewVersion: datadog.PtrBool(true),
DeleteRecords: []string{},
InsertRecords: []datadogV2.LLMObsDatasetBatchUpdateInsertRecord{
{
ExpectedOutput: *datadogV2.NewNullableAnyValue(nil),
Id: datadog.PtrString("rec-7c3f5a1b-9e2d-4f8a-b1c6-3d7e9f0a2b4c"),
Input: *datadogV2.NewNullableAnyValue(nil),
TagOperations: &datadogV2.LLMObsDatasetRecordTagOperations{
Add: []string{},
Remove: []string{},
Set: []string{},
},
Tags: []string{},
},
},
Tags: []string{},
UpdateRecords: []datadogV2.LLMObsDatasetBatchUpdateUpdateRecord{
{
ExpectedOutput: *datadogV2.NewNullableAnyValue(nil),
Id: "rec-7c3f5a1b-9e2d-4f8a-b1c6-3d7e9f0a2b4c",
Input: *datadogV2.NewNullableAnyValue(nil),
TagOperations: &datadogV2.LLMObsDatasetRecordTagOperations{
Add: []string{},
Remove: []string{},
Set: []string{},
},
},
},
},
Id: "9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d",
Type: datadogV2.LLMOBSDATASETTYPE_DATASETS,
},
}
ctx := datadog.NewDefaultContext(context.Background())
ctx = context.WithValue(ctx, datadog.ContextAccessToken, os.Getenv("DD_BEARER_TOKEN"))
configuration := datadog.NewConfiguration()
configuration.SetUnstableOperationEnabled("v2.BatchUpdateLLMObsDataset", true)
apiClient := datadog.NewAPIClient(configuration)
api := datadogV2.NewAgentObservabilityApi(apiClient)
resp, r, err := api.BatchUpdateLLMObsDataset(ctx, "project_id", "dataset_id", body)
if err != nil {
fmt.Fprintf(os.Stderr, "Error when calling `AgentObservabilityApi.BatchUpdateLLMObsDataset`: %v\n", err)
fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
}
responseContent, _ := json.MarshalIndent(resp, "", " ")
fmt.Fprintf(os.Stdout, "Response from `AgentObservabilityApi.BatchUpdateLLMObsDataset`:\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"// Batch update Agent Observability dataset records 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.LLMObsDatasetBatchUpdateDataAttributesRequest;
import com.datadog.api.client.v2.model.LLMObsDatasetBatchUpdateDataRequest;
import com.datadog.api.client.v2.model.LLMObsDatasetBatchUpdateInsertRecord;
import com.datadog.api.client.v2.model.LLMObsDatasetBatchUpdateRequest;
import com.datadog.api.client.v2.model.LLMObsDatasetBatchUpdateUpdateRecord;
import com.datadog.api.client.v2.model.LLMObsDatasetRecordTagOperations;
import com.datadog.api.client.v2.model.LLMObsDatasetRecordsMutationResponse;
import com.datadog.api.client.v2.model.LLMObsDatasetType;
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.batchUpdateLLMObsDataset", true);
AgentObservabilityApi apiInstance = new AgentObservabilityApi(defaultClient);
LLMObsDatasetBatchUpdateRequest body =
new LLMObsDatasetBatchUpdateRequest()
.data(
new LLMObsDatasetBatchUpdateDataRequest()
.attributes(
new LLMObsDatasetBatchUpdateDataAttributesRequest()
.createNewVersion(true)
.insertRecords(
Collections.singletonList(
new LLMObsDatasetBatchUpdateInsertRecord()
.expectedOutput(null)
.id("rec-7c3f5a1b-9e2d-4f8a-b1c6-3d7e9f0a2b4c")
.input(null)
.tagOperations(new LLMObsDatasetRecordTagOperations())))
.updateRecords(
Collections.singletonList(
new LLMObsDatasetBatchUpdateUpdateRecord()
.expectedOutput(null)
.id("rec-7c3f5a1b-9e2d-4f8a-b1c6-3d7e9f0a2b4c")
.input(null)
.tagOperations(new LLMObsDatasetRecordTagOperations()))))
.id("9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d")
.type(LLMObsDatasetType.DATASETS));
try {
LLMObsDatasetRecordsMutationResponse result =
apiInstance.batchUpdateLLMObsDataset(
"a33671aa-24fd-4dcd-9b33-a8ec7dde7751", "9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d", body);
System.out.println(result);
} catch (ApiException e) {
System.err.println("Exception when calling AgentObservabilityApi#batchUpdateLLMObsDataset");
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""""
Batch update Agent Observability dataset records 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_dataset_batch_update_data_attributes_request import (
LLMObsDatasetBatchUpdateDataAttributesRequest,
)
from datadog_api_client.v2.model.llm_obs_dataset_batch_update_data_request import LLMObsDatasetBatchUpdateDataRequest
from datadog_api_client.v2.model.llm_obs_dataset_batch_update_insert_record import LLMObsDatasetBatchUpdateInsertRecord
from datadog_api_client.v2.model.llm_obs_dataset_batch_update_request import LLMObsDatasetBatchUpdateRequest
from datadog_api_client.v2.model.llm_obs_dataset_batch_update_update_record import LLMObsDatasetBatchUpdateUpdateRecord
from datadog_api_client.v2.model.llm_obs_dataset_record_tag_operations import LLMObsDatasetRecordTagOperations
from datadog_api_client.v2.model.llm_obs_dataset_type import LLMObsDatasetType
body = LLMObsDatasetBatchUpdateRequest(
data=LLMObsDatasetBatchUpdateDataRequest(
attributes=LLMObsDatasetBatchUpdateDataAttributesRequest(
create_new_version=True,
delete_records=[],
insert_records=[
LLMObsDatasetBatchUpdateInsertRecord(
expected_output=None,
id="rec-7c3f5a1b-9e2d-4f8a-b1c6-3d7e9f0a2b4c",
input=None,
tag_operations=LLMObsDatasetRecordTagOperations(
add=[],
remove=[],
set=[],
),
tags=[],
),
],
tags=[],
update_records=[
LLMObsDatasetBatchUpdateUpdateRecord(
expected_output=None,
id="rec-7c3f5a1b-9e2d-4f8a-b1c6-3d7e9f0a2b4c",
input=None,
tag_operations=LLMObsDatasetRecordTagOperations(
add=[],
remove=[],
set=[],
),
),
],
),
id="9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d",
type=LLMObsDatasetType.DATASETS,
),
)
configuration = Configuration()
configuration.access_token = environ["DD_BEARER_TOKEN"]
configuration.unstable_operations["batch_update_llm_obs_dataset"] = True
with ApiClient(configuration) as api_client:
api_instance = AgentObservabilityApi(api_client)
response = api_instance.batch_update_llm_obs_dataset(project_id="project_id", dataset_id="dataset_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"# Batch update Agent Observability dataset records returns "OK" response
require "datadog_api_client"
DatadogAPIClient.configure do |config|
config.access_token = ENV["DD_BEARER_TOKEN"]
config.unstable_operations["v2.batch_update_llm_obs_dataset".to_sym] = true
end
api_instance = DatadogAPIClient::V2::AgentObservabilityAPI.new
body = DatadogAPIClient::V2::LLMObsDatasetBatchUpdateRequest.new({
data: DatadogAPIClient::V2::LLMObsDatasetBatchUpdateDataRequest.new({
attributes: DatadogAPIClient::V2::LLMObsDatasetBatchUpdateDataAttributesRequest.new({
create_new_version: true,
delete_records: [],
insert_records: [
DatadogAPIClient::V2::LLMObsDatasetBatchUpdateInsertRecord.new({
expected_output: nil,
id: "rec-7c3f5a1b-9e2d-4f8a-b1c6-3d7e9f0a2b4c",
input: nil,
tag_operations: DatadogAPIClient::V2::LLMObsDatasetRecordTagOperations.new({
add: [],
remove: [],
set: [],
}),
tags: [],
}),
],
tags: [],
update_records: [
DatadogAPIClient::V2::LLMObsDatasetBatchUpdateUpdateRecord.new({
expected_output: nil,
id: "rec-7c3f5a1b-9e2d-4f8a-b1c6-3d7e9f0a2b4c",
input: nil,
tag_operations: DatadogAPIClient::V2::LLMObsDatasetRecordTagOperations.new({
add: [],
remove: [],
set: [],
}),
}),
],
}),
id: "9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d",
type: DatadogAPIClient::V2::LLMObsDatasetType::DATASETS,
}),
})
p api_instance.batch_update_llm_obs_dataset("project_id", "dataset_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"// Batch update Agent Observability dataset records returns "OK" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_agent_observability::AgentObservabilityAPI;
use datadog_api_client::datadogV2::model::LLMObsDatasetBatchUpdateDataAttributesRequest;
use datadog_api_client::datadogV2::model::LLMObsDatasetBatchUpdateDataRequest;
use datadog_api_client::datadogV2::model::LLMObsDatasetBatchUpdateInsertRecord;
use datadog_api_client::datadogV2::model::LLMObsDatasetBatchUpdateRequest;
use datadog_api_client::datadogV2::model::LLMObsDatasetBatchUpdateUpdateRecord;
use datadog_api_client::datadogV2::model::LLMObsDatasetRecordTagOperations;
use datadog_api_client::datadogV2::model::LLMObsDatasetType;
#[tokio::main]
async fn main() {
let body = LLMObsDatasetBatchUpdateRequest::new(LLMObsDatasetBatchUpdateDataRequest::new(
LLMObsDatasetBatchUpdateDataAttributesRequest::new()
.create_new_version(true)
.delete_records(vec![])
.insert_records(vec![LLMObsDatasetBatchUpdateInsertRecord::new(None)
.expected_output(None)
.id("rec-7c3f5a1b-9e2d-4f8a-b1c6-3d7e9f0a2b4c".to_string())
.tag_operations(
LLMObsDatasetRecordTagOperations::new()
.add(vec![])
.remove(vec![])
.set(vec![]),
)
.tags(vec![])])
.tags(vec![])
.update_records(vec![LLMObsDatasetBatchUpdateUpdateRecord::new(
"rec-7c3f5a1b-9e2d-4f8a-b1c6-3d7e9f0a2b4c".to_string(),
)
.expected_output(None)
.input(None)
.tag_operations(
LLMObsDatasetRecordTagOperations::new()
.add(vec![])
.remove(vec![])
.set(vec![]),
)]),
"9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d".to_string(),
LLMObsDatasetType::DATASETS,
));
let mut configuration = datadog::Configuration::new();
configuration.set_unstable_operation_enabled("v2.batch_update_llm_obs_dataset", true);
let api = AgentObservabilityAPI::with_config(configuration);
let resp = api
.batch_update_llm_obs_dataset("project_id".to_string(), "dataset_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/**
* Batch update Agent Observability dataset records 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.batchUpdateLLMObsDataset"] = true;
const apiInstance = new v2.AgentObservabilityApi(configuration);
const params: v2.AgentObservabilityApiBatchUpdateLLMObsDatasetRequest = {
body: {
data: {
attributes: {
createNewVersion: true,
deleteRecords: [],
insertRecords: [
{
expectedOutput: undefined,
id: "rec-7c3f5a1b-9e2d-4f8a-b1c6-3d7e9f0a2b4c",
input: null,
tagOperations: {
add: [],
remove: [],
set: [],
},
tags: [],
},
],
tags: [],
updateRecords: [
{
expectedOutput: undefined,
id: "rec-7c3f5a1b-9e2d-4f8a-b1c6-3d7e9f0a2b4c",
input: undefined,
tagOperations: {
add: [],
remove: [],
set: [],
},
},
],
},
id: "9f64e5c7-dc5a-45c8-a17c-1b85f0bec97d",
type: "datasets",
},
},
projectId: "project_id",
datasetId: "dataset_id",
};
apiInstance
.batchUpdateLLMObsDataset(params)
.then((data: v2.LLMObsDatasetRecordsMutationResponse) => {
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"