コードを使用したテンプレートからホストされたカスタム指標の作成¶

import datarobot as dr
from datarobot.enums import HostedCustomMetricsTemplateMetricTypeQueryParams
from datarobot.models.deployment.custom_metrics import HostedCustomMetricTemplate, HostedCustomMetric, \
    HostedCustomMetricBlueprint, CustomMetric, MetricTimestampSpoofing, ValueField, SampleCountField, BatchField
from datarobot.models.registry import JobRun
from datarobot.models.registry.job import Job
from datarobot import Deployment
from datarobot.models.runtime_parameters import RuntimeParameterValue
from datarobot.models.types import Schedule

DataRobotClient(token="<DataRobot API Token>", endpoint="<DataRobot URL>")
gen_ai_deployment_1 = Deployment.get('<Deployment Id>')

templates = HostedCustomMetricTemplate.list(
    search="[JP] Character Count",
    metric_type=HostedCustomMetricsTemplateMetricTypeQueryParams.LLM,
    limit=1,
    offset=0,
)

hosted_custom_metric = HostedCustomMetric.create_from_template(
    template_id=templates[0].id,
    deployment_id=gen_ai_deployment_1.id,
    job_name="Hosted Custom Metric Character Count",
    custom_metric_name="Character Count",
    job_description="Hosted Custom Metric",
    custom_metric_description="LLM Character Count",
    baseline_value=10,
    timestamp=MetricTimestampSpoofing(
        column_name="timestamp",
        time_format="%Y-%m-%d %H:%M:%S",
    ),
    value = ValueField(column_name="value"),
    sample_count=SampleCountField(column_name='Sample Count'),
    batch=BatchField(column_name='Batch'),
    schedule=Schedule(
        day_of_week=[0],
        hour=['*'],
        minute=['*'],
        day_of_month=[12],
        month=[1],
    ),
    parameter_overrides=[RuntimeParameterValue(field_name='DRY_RUN', value="0", type="string")]
)

job_run = JobRun.create(
        job_id=hosted_custom_metric.custom_job_id
        runtime_parameter_values=[
            RuntimeParameterValue(field_name='DRY_RUN', value="1", type="string"),
            RuntimeParameterValue(field_name='DEPLOYMENT_ID', value=gen_ai_deployment_1.id, type="deployment"),
            RuntimeParameterValue(field_name='CUSTOM_METRIC_ID', value=hosted_custom_metric.id, type="customMetric"),
        ]
    )
    print(job_run.status)

job = Job.create_from_custom_metric_gallery_template(
    template_id=templates[0].id,
    name="Job created from template",
    description="Job created from template"
)

blueprint = HostedCustomMetricBlueprint.get(job.id)
print(f"Original directionality: {blueprint.directionality}")

updated_blueprint = blueprint.update(
    directionality='lowerIsBetter',
    units='characters',
    type='gauge',
    time_step='hour',
    is_model_specific=False
)
print(f"Updated directionality: {updated_blueprint.directionality}")

another_hosted_custom_metric = HostedCustomMetric.create_from_custom_job(
    custom_job_id=job.id,
    deployment_id=gen_ai_deployment_1.id,
    name="Custom metric created in 2 steps",
)

another_custom_metric = CustomMetric.get(custom_metric_id=another_hosted_custom_metric.id, deployment_id=gen_ai_deployment_1.id)
print(f"Directionality of another custom metric: {another_custom_metric.directionality}")

job_run = JobRun.create(
    job_id=job.id,
    runtime_parameter_values=[
        RuntimeParameterValue(field_name='DRY_RUN', value="1", type="string"),
        RuntimeParameterValue(field_name='DEPLOYMENT_ID', value=gen_ai_deployment_1.id, type="deployment"),
        RuntimeParameterValue(field_name='CUSTOM_METRIC_ID', value=another_hosted_custom_metric.id, type="customMetric"),
    ]
)
print(job_run.status)

hosted_custom_metrics = HostedCustomMetric.list(deployment_id=hosted_custom_metric.custom_job_id)
for metric in hosted_custom_metrics:
    print(metric.name)

hosted_custom_metric.delete()
another_hosted_custom_metric.delete()

job.delete()