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[ML] Trained models list: disables 'View training data' action if data frame analytics job no longer exists #171061

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merged 8 commits into from Nov 21, 2023
Merged

[ML] Trained models list: disables 'View training data' action if data frame analytics job no longer exists #171061

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a407ee2
disable View Training Data if original job no longer exists
alvarezmelissa87 Nov 10, 2023
7c06abd
check all jobs exist at once. check permissions
alvarezmelissa87 Nov 13, 2023
6d8a4e5
create ViewTrainingData to wrap disabled action in tooltip
alvarezmelissa87 Nov 13, 2023
12f1a01
Merge branch 'main' into ml-dfa-view-training
kibanamachine Nov 13, 2023
50ffcfd
refactor origin_job_exists check
alvarezmelissa87 Nov 15, 2023
8c7094d
update types and fix action in column
alvarezmelissa87 Nov 15, 2023
3bc2c8d
Merge branch 'main' into ml-dfa-view-training
kibanamachine Nov 15, 2023
73216d0
ensure job id string is corrrect
alvarezmelissa87 Nov 16, 2023
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1 change: 1 addition & 0 deletions x-pack/plugins/ml/common/types/trained_models.ts
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Expand Up @@ -98,6 +98,7 @@ export type TrainedModelConfigResponse = estypes.MlTrainedModelConfig & {
* Associated pipelines. Extends response from the ES endpoint.
*/
pipelines?: Record<string, PipelineDefinition> | null;
origin_job_exists?: boolean;
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I don't think this needs to be optional route param. We should always perform this check when retrieving the models as it's useful information.

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Updated in 7c06abd


metadata?: {
analytics_config: DataFrameAnalyticsConfig;
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1 change: 1 addition & 0 deletions x-pack/plugins/ml/public/application/model_management/model_actions.tsx
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Expand Up @@ -142,6 +142,7 @@ export function useModelActions({
icon: 'visTable',
type: 'icon',
available: (item) => !!item.metadata?.analytics_config?.id,
enabled: (item) => item.origin_job_exists === true,
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Can you add a tooltip to show why the action is disabled.

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Added in 6d8a4e5
Happy to get suggestions on the copy to use.
image

onClick: async (item) => {
if (item.metadata?.analytics_config === undefined) return;

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2 changes: 2 additions & 0 deletions x-pack/plugins/ml/public/application/model_management/models_list.tsx
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Expand Up @@ -79,6 +79,7 @@ export type ModelItem = TrainedModelConfigResponse & {
type?: string[];
stats?: Stats & { deployment_stats: TrainedModelDeploymentStatsResponse[] };
pipelines?: ModelPipelines['pipelines'] | null;
origin_job_exists?: boolean;
deployment_ids: string[];
putModelConfig?: object;
state: ModelState;
Expand Down Expand Up @@ -214,6 +215,7 @@ export const ModelsList: FC<Props> = ({
const response = await trainedModelsApiService.getTrainedModels(undefined, {
with_pipelines: true,
with_indices: true,
with_origin_job_check: true,
});

const newItems: ModelItem[] = [];
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1 change: 1 addition & 0 deletions x-pack/plugins/ml/public/application/services/ml_api_service/trained_models.ts
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Expand Up @@ -33,6 +33,7 @@ export interface InferenceQueryParams {
// Custom kibana endpoint query params
with_pipelines?: boolean;
with_indices?: boolean;
with_origin_job_check?: boolean;
include?: 'total_feature_importance' | 'feature_importance_baseline' | string;
}

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1 change: 1 addition & 0 deletions x-pack/plugins/ml/server/routes/schemas/inference_schema.ts
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Expand Up @@ -49,6 +49,7 @@ export const getInferenceQuerySchema = schema.object({
size: schema.maybe(schema.string()),
with_pipelines: schema.maybe(schema.string()),
with_indices: schema.maybe(schema.oneOf([schema.string(), schema.boolean()])),
with_origin_job_check: schema.maybe(schema.oneOf([schema.string(), schema.boolean()])),
include: schema.maybe(schema.string()),
});

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21 changes: 19 additions & 2 deletions x-pack/plugins/ml/server/routes/trained_models.ts
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Expand Up @@ -90,6 +90,7 @@ export function trainedModelsRoutes(
const {
with_pipelines: withPipelines,
with_indices: withIndicesRaw,
with_origin_job_check: withOriginJobCheck,
...getTrainedModelsRequestParams
} = request.query;

Expand Down Expand Up @@ -191,10 +192,26 @@ export function trainedModelsRoutes(
mlLog.debug(e);
}

const body = filterForEnabledFeatureModels(result, getEnabledFeatures());
try {
if (withOriginJobCheck) {
for (const model of result) {
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if (typeof model.metadata?.analytics_config?.id === 'string') {
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const jobExistsResult = await mlClient.getDataFrameAnalytics({
id: model.metadata?.analytics_config?.id,
size: 1,
});
model.origin_job_exists = jobExistsResult.count === 1;
}
}
}
} catch (e) {
// Swallow error to prevent blocking trained models result
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}

const filteredModels = filterForEnabledFeatureModels(result, getEnabledFeatures());

return response.ok({
body,
body: filteredModels,
});
} catch (e) {
return response.customError(wrapError(e));
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