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[Search][Index Management] Removing Model deployment from Kibana (#19…
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…8409)

## Summary

Clicking on the `Try Again` button tries to redeploy and receives an
error. We tried to disable the `Try Again` button if there are no errors
in deployment stage.

### Before

https://github.com/user-attachments/assets/b1c7b7ce-afba-42ba-a958-d9ad7cbc8777

### After

https://github.com/user-attachments/assets/15ca3a78-a1fc-4079-8ab6-f4b54e7ed333

---------

Co-authored-by: Elastic Machine <[email protected]>
(cherry picked from commit bc313f4)
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Samiul-TheSoccerFan committed Nov 6, 2024
1 parent d040cc4 commit ea1525d
Showing 1 changed file with 1 addition and 39 deletions.
Original file line number Diff line number Diff line change
Expand Up @@ -26,10 +26,8 @@ import React from 'react';
import { EuiLink } from '@elastic/eui';
import { useEffect, useMemo, useState } from 'react';
import { i18n } from '@kbn/i18n';
import { ModelIdMapEntry } from '../../../../components/mappings_editor/components/document_fields/fields';
import { isSemanticTextField } from '../../../../components/mappings_editor/lib/utils';
import { deNormalize } from '../../../../components/mappings_editor/lib';
import { useMLModelNotificationToasts } from '../../../../../hooks/use_ml_model_status_toasts';
import { useMappingsState } from '../../../../components/mappings_editor/mappings_state_context';
import { useAppContext } from '../../../../app_context';

Expand All @@ -55,15 +53,11 @@ export function TrainedModelsDeploymentModal({
}: TrainedModelsDeploymentModalProps) {
const modalTitleId = useGeneratedHtmlId();
const { fields, inferenceToModelIdMap } = useMappingsState();
const {
plugins: { ml },
url,
} = useAppContext();
const { url } = useAppContext();
const [isModalVisible, setIsModalVisible] = useState<boolean>(false);
const closeModal = () => setIsModalVisible(false);
const [mlManagementPageUrl, setMlManagementPageUrl] = useState<string>('');
const [allowForceSaveMappings, setAllowForceSaveMappings] = useState<boolean>(false);
const { showErrorToasts, showSuccessfullyDeployedToast } = useMLModelNotificationToasts();

useEffect(() => {
const mlLocator = url?.locators.get(ML_APP_LOCATOR);
Expand All @@ -86,25 +80,6 @@ export function TrainedModelsDeploymentModal({

const [pendingDeployments, setPendingDeployments] = useState<string[]>([]);

const startModelAllocation = async (entry: ModelIdMapEntry & { inferenceId: string }) => {
try {
await ml?.mlApi?.trainedModels.startModelAllocation(entry.trainedModelId, {
number_of_allocations: 1,
threads_per_allocation: 1,
priority: 'normal',
deployment_id: entry.inferenceId,
});
showSuccessfullyDeployedToast(entry.trainedModelId);
} catch (error) {
setErrorsInTrainedModelDeployment((previousState) => ({
...previousState,
[entry.inferenceId]: error.message,
}));
showErrorToasts(error);
setIsModalVisible(true);
}
};

useEffect(() => {
const models = inferenceIdsInPendingList.map((inferenceId) =>
inferenceToModelIdMap?.[inferenceId]
Expand All @@ -114,18 +89,6 @@ export function TrainedModelsDeploymentModal({
}
: undefined
); // filter out third-party models
for (const model of models) {
if (
model?.trainedModelId &&
model.isDeployable &&
!model.isDownloading &&
!model.isDeployed
) {
// Sometimes the model gets stuck in a ready to deploy state, so we need to trigger deployment manually
// This is currently the only way to surface a specific error message to the user
startModelAllocation(model);
}
}
const allPendingDeployments = models
.map((model) => {
return model?.trainedModelId && !model?.isDeployed ? model?.inferenceId : '';
Expand All @@ -135,7 +98,6 @@ export function TrainedModelsDeploymentModal({
(deployment, index) => allPendingDeployments.indexOf(deployment) === index
);
setPendingDeployments(uniqueDeployments);
// eslint-disable-next-line react-hooks/exhaustive-deps
}, [inferenceIdsInPendingList, inferenceToModelIdMap]);

const erroredDeployments = pendingDeployments.filter(
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