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Refactoring Inference Management UI (#193380)
## Summary This PR includes: - Adding header links and text - Restructure of columns - Increased pagination limit  ### Checklist Delete any items that are not applicable to this PR. - [X] Any text added follows [EUI's writing guidelines](https://elastic.github.io/eui/#/guidelines/writing), uses sentence case text and includes [i18n support](https://github.com/elastic/kibana/blob/main/packages/kbn-i18n/README.md) - [X] [Unit or functional tests](https://www.elastic.co/guide/en/kibana/master/development-tests.html) were updated or added to match the most common scenarios --------- Co-authored-by: Elastic Machine <elasticmachine@users.noreply.github.com>
This commit is contained in:
Samiul Monir
GitHub
parent
885dfe3017
commit
fd149a5ab2
21 changed files with 433 additions and 814 deletions
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@ -10,7 +10,7 @@ import { i18n } from '@kbn/i18n';
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export const INFERENCE_ENDPOINT_LABEL = i18n.translate(
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'xpack.searchInferenceEndpoints.inferenceEndpointsLabel',
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{
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defaultMessage: 'Inference Endpoints',
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defaultMessage: 'Inference endpoints',
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}
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);
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@ -21,7 +21,8 @@ export const CANCEL = i18n.translate('xpack.searchInferenceEndpoints.cancel', {
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export const MANAGE_INFERENCE_ENDPOINTS_LABEL = i18n.translate(
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'xpack.searchInferenceEndpoints.allInferenceEndpoints.description',
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{
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defaultMessage: 'View and manage your deployed inference endpoints.',
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defaultMessage:
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'Inference endpoints streamline the deployment and management of machine\nlearning models in Elasticsearch. Set up and manage NLP tasks using unique\nendpoints, to build AI-powered search.',
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}
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);
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@ -69,9 +70,16 @@ export const SEMANTIC_SEARCH_WITH_E5_LINK = i18n.translate(
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);
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export const VIEW_YOUR_MODELS_LINK = i18n.translate(
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'xpack.searchInferenceEndpoints.addEmptyPrompt.viewYourModels',
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'xpack.searchInferenceEndpoints.viewYourModels',
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{
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defaultMessage: 'View your models',
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defaultMessage: 'ML Trained Models',
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}
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);
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export const API_DOCUMENTATION_LINK = i18n.translate(
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'xpack.searchInferenceEndpoints.apiDocumentationLink',
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{
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defaultMessage: 'API Documentation',
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}
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);
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@ -14,7 +14,7 @@ import {
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} from './types';
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export const DEFAULT_TABLE_ACTIVE_PAGE = 1;
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export const DEFAULT_TABLE_LIMIT = 10;
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export const DEFAULT_TABLE_LIMIT = 25;
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export const DEFAULT_QUERY_PARAMS: QueryParams = {
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page: DEFAULT_TABLE_ACTIVE_PAGE,
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@ -28,7 +28,7 @@ export const DeleteAction: React.FC<DeleteActionProps> = ({ selectedEndpoint })
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deleteEndpoint({
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type: selectedEndpoint.type,
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id: selectedEndpoint.endpoint.inference_id,
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id: selectedEndpoint.endpoint,
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});
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};
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@ -37,7 +37,7 @@ export const DeleteAction: React.FC<DeleteActionProps> = ({ selectedEndpoint })
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<EuiButtonIcon
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aria-label={i18n.translate('xpack.searchInferenceEndpoints.actions.deleteEndpoint', {
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defaultMessage: 'Delete inference endpoint {selectedEndpointName}',
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values: { selectedEndpointName: selectedEndpoint?.endpoint.inference_id },
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values: { selectedEndpointName: selectedEndpoint?.endpoint },
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})}
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key="delete"
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iconType="trash"
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@ -1,33 +0,0 @@
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/*
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* Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
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* or more contributor license agreements. Licensed under the Elastic License
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* 2.0; you may not use this file except in compliance with the Elastic License
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* 2.0.
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*/
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import { render, screen } from '@testing-library/react';
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import React from 'react';
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import { DeploymentStatus } from './deployment_status';
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import { DeploymentState } from '@kbn/ml-trained-models-utils';
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describe('DeploymentStatus component', () => {
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it('starting renders with warning status', () => {
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render(<DeploymentStatus status={'starting' as DeploymentState} />);
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const healthComponent = screen.getByTestId(`table-column-deployment-starting`);
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expect(healthComponent).toBeInTheDocument();
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expect(healthComponent).toHaveAttribute('color', 'warning');
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});
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it('stopping renders with danger status', () => {
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render(<DeploymentStatus status={'stopping' as DeploymentState} />);
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const healthComponent = screen.getByTestId(`table-column-deployment-stopping`);
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expect(healthComponent).toBeInTheDocument();
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expect(healthComponent).toHaveAttribute('color', 'danger');
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});
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it('started renders with success status', () => {
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render(<DeploymentStatus status={'started' as DeploymentState} />);
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const healthComponent = screen.getByTestId(`table-column-deployment-started`);
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expect(healthComponent).toBeInTheDocument();
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expect(healthComponent).toHaveAttribute('color', 'success');
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});
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});
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@ -1,62 +0,0 @@
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/*
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* Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
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* or more contributor license agreements. Licensed under the Elastic License
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* 2.0; you may not use this file except in compliance with the Elastic License
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* 2.0.
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*/
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import React from 'react';
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import { EuiIcon, EuiToolTip } from '@elastic/eui';
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import { DeploymentState } from '@kbn/ml-trained-models-utils';
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import * as i18n from './translations';
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interface DeploymentStatusProps {
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status: DeploymentState | undefined;
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}
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function getStatus(status: DeploymentState | undefined) {
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switch (status) {
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case 'started':
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return {
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statusColor: 'success',
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type: 'dot',
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tooltip: i18n.MODEL_DEPLOYED,
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};
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case 'starting':
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return {
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statusColor: 'warning',
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type: 'warning',
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tooltip: i18n.MODEL_STARTING,
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};
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case 'stopping':
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return {
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statusColor: 'danger',
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type: 'dot',
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tooltip: i18n.MODEL_STOPPING,
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};
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case undefined:
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return {
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statusColor: 'danger',
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type: 'dot',
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tooltip: i18n.MODEL_NOT_DEPLOYED,
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};
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}
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}
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export const DeploymentStatus: React.FC<DeploymentStatusProps> = ({ status }) => {
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const { statusColor, type, tooltip } = getStatus(status);
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return (
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<EuiToolTip content={tooltip}>
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<EuiIcon
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aria-label={tooltip}
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type={type}
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data-test-subj={`table-column-deployment-${status}`}
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color={statusColor}
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/>
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</EuiToolTip>
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);
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};
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@ -1,36 +0,0 @@
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/*
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* Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
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* or more contributor license agreements. Licensed under the Elastic License
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* 2.0; you may not use this file except in compliance with the Elastic License
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* 2.0.
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*/
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import { i18n } from '@kbn/i18n';
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export const MODEL_DEPLOYED = i18n.translate(
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'xpack.searchInferenceEndpoints.deploymentStatus.tooltip.modelDeployed',
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{
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defaultMessage: 'Model is deployed',
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}
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);
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export const MODEL_STARTING = i18n.translate(
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'xpack.searchInferenceEndpoints.deploymentStatus.tooltip.modelNotDeployed',
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{
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defaultMessage: 'Model starting',
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}
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);
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export const MODEL_NOT_DEPLOYED = i18n.translate(
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'xpack.searchInferenceEndpoints.deploymentStatus.tooltip.modelNotDeployed',
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{
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defaultMessage: 'Model is not deployed',
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}
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);
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export const MODEL_STOPPING = i18n.translate(
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'xpack.searchInferenceEndpoints.deploymentStatus.tooltip.modelStopped',
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{
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defaultMessage: 'Model stopping',
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}
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);
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@ -9,315 +9,10 @@ import { render, screen } from '@testing-library/react';
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import React from 'react';
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import { EndpointInfo } from './endpoint_info';
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jest.mock('@kbn/ml-trained-models-utils', () => ({
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...jest.requireActual('@kbn/ml-trained-models-utils'),
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ELASTIC_MODEL_DEFINITIONS: {
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'model-with-mit-license': {
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license: 'MIT',
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licenseUrl: 'https://abc.com',
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},
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},
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}));
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describe('RenderEndpoint component tests', () => {
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describe('with cohere service', () => {
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const mockEndpoint = {
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inference_id: 'cohere-2',
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service: 'cohere',
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service_settings: {
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similarity: 'cosine',
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dimensions: 384,
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model_id: 'embed-english-light-v3.0',
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rate_limit: {
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requests_per_minute: 10000,
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},
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embedding_type: 'byte',
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},
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task_settings: {},
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} as any;
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it('renders the component with inference id', () => {
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render(<EndpointInfo inferenceId={'cohere-2'} />);
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it('renders the component with endpoint details for Cohere service', () => {
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render(<EndpointInfo endpoint={mockEndpoint} />);
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expect(screen.getByText('cohere-2')).toBeInTheDocument();
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expect(screen.getByText('byte')).toBeInTheDocument();
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expect(screen.getByText('embed-english-light-v3.0')).toBeInTheDocument();
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});
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it('does not render model_id badge if serviceSettings.model_id is not provided for Cohere service', () => {
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const modifiedEndpoint = {
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...mockEndpoint,
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service_settings: { ...mockEndpoint.service_settings, model_id: undefined },
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};
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render(<EndpointInfo endpoint={modifiedEndpoint} />);
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expect(screen.queryByText('embed-english-light-v3.0')).not.toBeInTheDocument();
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});
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it('renders only model_id if other settings are not provided for Cohere service', () => {
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const modifiedEndpoint = {
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...mockEndpoint,
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service_settings: { model_id: 'embed-english-light-v3.0' },
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};
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render(<EndpointInfo endpoint={modifiedEndpoint} />);
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expect(screen.getByText('embed-english-light-v3.0')).toBeInTheDocument();
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expect(screen.queryByText(',')).not.toBeInTheDocument();
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});
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});
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describe('with elasticsearch service', () => {
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const mockEndpoint = {
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inference_id: 'model-123',
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service: 'elasticsearch',
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service_settings: {
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num_allocations: 5,
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num_threads: 10,
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model_id: 'settings-model-123',
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},
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} as any;
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it('renders the component with endpoint model_id and model settings', () => {
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render(<EndpointInfo endpoint={mockEndpoint} />);
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expect(screen.getByText('model-123')).toBeInTheDocument();
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expect(screen.getByText('settings-model-123')).toBeInTheDocument();
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expect(screen.getByText('Threads: 10 | Allocations: 5')).toBeInTheDocument();
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});
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it('renders the component with only model_id if num_threads and num_allocations are not provided', () => {
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const modifiedSettings = {
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...mockEndpoint.service_settings,
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num_threads: undefined,
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num_allocations: undefined,
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};
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const modifiedEndpoint = { ...mockEndpoint, service_settings: modifiedSettings };
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render(<EndpointInfo endpoint={modifiedEndpoint} />);
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expect(screen.getByText('model-123')).toBeInTheDocument();
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expect(screen.getByText('settings-model-123')).toBeInTheDocument();
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expect(screen.queryByText('Threads: 10 | Allocations: 5')).not.toBeInTheDocument();
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});
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});
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describe('with azureaistudio service', () => {
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const mockEndpoint = {
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inference_id: 'azure-ai-1',
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service: 'azureaistudio',
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service_settings: {
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target: 'westus',
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provider: 'microsoft_phi',
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endpoint_type: 'realtime',
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},
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} as any;
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it('renders the component with endpoint details', () => {
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render(<EndpointInfo endpoint={mockEndpoint} />);
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expect(screen.getByText('azure-ai-1')).toBeInTheDocument();
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expect(screen.getByText('microsoft_phi, realtime, westus')).toBeInTheDocument();
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});
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it('renders correctly when some service settings are missing', () => {
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const modifiedEndpoint = {
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...mockEndpoint,
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service_settings: { target: 'westus', provider: 'microsoft_phi' },
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};
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render(<EndpointInfo endpoint={modifiedEndpoint} />);
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expect(screen.getByText('microsoft_phi, westus')).toBeInTheDocument();
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});
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it('does not render a comma when only one service setting is provided', () => {
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const modifiedEndpoint = {
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...mockEndpoint,
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service_settings: { target: 'westus' },
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};
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render(<EndpointInfo endpoint={modifiedEndpoint} />);
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expect(screen.getByText('westus')).toBeInTheDocument();
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expect(screen.queryByText(',')).not.toBeInTheDocument();
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});
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it('renders nothing related to service settings when all are missing', () => {
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const modifiedEndpoint = {
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...mockEndpoint,
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service_settings: {},
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};
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render(<EndpointInfo endpoint={modifiedEndpoint} />);
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expect(screen.getByText('azure-ai-1')).toBeInTheDocument();
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expect(screen.queryByText('westus')).not.toBeInTheDocument();
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expect(screen.queryByText('microsoft_phi')).not.toBeInTheDocument();
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expect(screen.queryByText('realtime')).not.toBeInTheDocument();
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});
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});
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describe('with azureopenai service', () => {
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const mockEndpoint = {
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inference_id: 'azure-openai-1',
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service: 'azureopenai',
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service_settings: {
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resource_name: 'resource-xyz',
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deployment_id: 'deployment-123',
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api_version: 'v1',
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},
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} as any;
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it('renders the component with all required endpoint details', () => {
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render(<EndpointInfo endpoint={mockEndpoint} />);
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expect(screen.getByText('azure-openai-1')).toBeInTheDocument();
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expect(screen.getByText('resource-xyz, deployment-123, v1')).toBeInTheDocument();
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});
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});
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describe('with mistral service', () => {
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const mockEndpoint = {
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inference_id: 'mistral-ai-1',
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service: 'mistral',
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service_settings: {
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model: 'model-xyz',
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max_input_tokens: 512,
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rate_limit: {
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requests_per_minute: 1000,
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},
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},
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} as any;
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it('renders the component with endpoint details', () => {
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render(<EndpointInfo endpoint={mockEndpoint} />);
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expect(screen.getByText('mistral-ai-1')).toBeInTheDocument();
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expect(screen.getByText('model-xyz')).toBeInTheDocument();
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expect(screen.getByText('max_input_tokens: 512, rate_limit: 1000')).toBeInTheDocument();
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});
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it('renders correctly when some service settings are missing', () => {
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const modifiedEndpoint = {
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...mockEndpoint,
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service_settings: {
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model: 'model-xyz',
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max_input_tokens: 512,
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},
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};
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render(<EndpointInfo endpoint={modifiedEndpoint} />);
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expect(screen.getByText('max_input_tokens: 512')).toBeInTheDocument();
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});
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it('does not render a comma when only one service setting is provided', () => {
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const modifiedEndpoint = {
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...mockEndpoint,
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service_settings: { model: 'model-xyz' },
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};
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render(<EndpointInfo endpoint={modifiedEndpoint} />);
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expect(screen.getByText('model-xyz')).toBeInTheDocument();
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expect(screen.queryByText(',')).not.toBeInTheDocument();
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});
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it('renders nothing related to service settings when all are missing', () => {
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const modifiedEndpoint = {
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...mockEndpoint,
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service_settings: {},
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};
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render(<EndpointInfo endpoint={modifiedEndpoint} />);
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expect(screen.getByText('mistral-ai-1')).toBeInTheDocument();
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expect(screen.queryByText('model-xyz')).not.toBeInTheDocument();
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expect(screen.queryByText('max_input_tokens: 512')).not.toBeInTheDocument();
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expect(screen.queryByText('rate_limit: 1000')).not.toBeInTheDocument();
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});
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});
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describe('with googleaistudio service', () => {
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const mockEndpoint = {
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inference_id: 'google-ai-1',
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service: 'googleaistudio',
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service_settings: {
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model_id: 'model-abc',
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rate_limit: {
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requests_per_minute: 500,
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},
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},
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} as any;
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it('renders the component with endpoint details', () => {
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render(<EndpointInfo endpoint={mockEndpoint} />);
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expect(screen.getByText('model-abc')).toBeInTheDocument();
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expect(screen.getByText('rate_limit: 500')).toBeInTheDocument();
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});
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it('renders correctly when rate limit is missing', () => {
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const modifiedEndpoint = {
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...mockEndpoint,
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service_settings: {
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model_id: 'model-abc',
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},
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};
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render(<EndpointInfo endpoint={modifiedEndpoint} />);
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expect(screen.getByText('model-abc')).toBeInTheDocument();
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expect(screen.queryByText('Rate limit:')).not.toBeInTheDocument();
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});
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});
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describe('with amazonbedrock service', () => {
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const mockEndpoint = {
|
||||
inference_id: 'amazon-bedrock-1',
|
||||
service: 'amazonbedrock',
|
||||
service_settings: {
|
||||
region: 'us-west-1',
|
||||
provider: 'AMAZONTITAN',
|
||||
model: 'model-bedrock-xyz',
|
||||
},
|
||||
} as any;
|
||||
|
||||
it('renders the component with endpoint details', () => {
|
||||
render(<EndpointInfo endpoint={mockEndpoint} />);
|
||||
|
||||
expect(screen.getByText('amazon-bedrock-1')).toBeInTheDocument();
|
||||
expect(screen.getByText('model-bedrock-xyz')).toBeInTheDocument();
|
||||
expect(screen.getByText('region: us-west-1, provider: amazontitan')).toBeInTheDocument();
|
||||
});
|
||||
});
|
||||
|
||||
describe('for MIT licensed models', () => {
|
||||
const mockEndpointWithMitLicensedModel = {
|
||||
inference_id: 'model-123',
|
||||
service: 'elasticsearch',
|
||||
service_settings: {
|
||||
num_allocations: 5,
|
||||
num_threads: 10,
|
||||
model_id: 'model-with-mit-license',
|
||||
},
|
||||
} as any;
|
||||
|
||||
it('renders the MIT license badge if the model is eligible', () => {
|
||||
render(<EndpointInfo endpoint={mockEndpointWithMitLicensedModel} />);
|
||||
|
||||
const mitBadge = screen.getByTestId('mit-license-badge');
|
||||
expect(mitBadge).toBeInTheDocument();
|
||||
expect(mitBadge).toHaveAttribute('href', 'https://abc.com');
|
||||
});
|
||||
|
||||
it('does not render the MIT license badge if the model is not eligible', () => {
|
||||
const mockEndpointWithNonMitLicensedModel = {
|
||||
inference_id: 'model-123',
|
||||
service: 'elasticsearch',
|
||||
service_settings: {
|
||||
num_allocations: 5,
|
||||
num_threads: 10,
|
||||
model_id: 'model-without-mit-license',
|
||||
},
|
||||
} as any;
|
||||
|
||||
render(<EndpointInfo endpoint={mockEndpointWithNonMitLicensedModel} />);
|
||||
|
||||
expect(screen.queryByTestId('mit-license-badge')).not.toBeInTheDocument();
|
||||
});
|
||||
expect(screen.getByText('cohere-2')).toBeInTheDocument();
|
||||
});
|
||||
});
|
||||
|
|
|
|||
|
|
@ -6,184 +6,13 @@
|
|||
*/
|
||||
|
||||
import React from 'react';
|
||||
import {
|
||||
InferenceAPIConfigResponse,
|
||||
ELASTIC_MODEL_DEFINITIONS,
|
||||
} from '@kbn/ml-trained-models-utils';
|
||||
import { EuiFlexGroup, EuiFlexItem, EuiText, EuiBadge } from '@elastic/eui';
|
||||
import { ServiceProviderKeys } from '../../types';
|
||||
import { ModelBadge } from './model_badge';
|
||||
import * as i18n from './translations';
|
||||
|
||||
export interface EndpointInfoProps {
|
||||
endpoint: InferenceAPIConfigResponse;
|
||||
inferenceId: string;
|
||||
}
|
||||
|
||||
export const EndpointInfo: React.FC<EndpointInfoProps> = ({ endpoint }) => {
|
||||
return (
|
||||
<EuiFlexGroup gutterSize="xs" direction="column">
|
||||
<EuiFlexItem>
|
||||
<strong>{endpoint.inference_id}</strong>
|
||||
</EuiFlexItem>
|
||||
<EuiFlexItem css={{ textWrap: 'wrap' }}>
|
||||
<EndpointModelInfo endpoint={endpoint} />
|
||||
</EuiFlexItem>
|
||||
</EuiFlexGroup>
|
||||
);
|
||||
};
|
||||
|
||||
const EndpointModelInfo: React.FC<EndpointInfoProps> = ({ endpoint }) => {
|
||||
const serviceSettings = endpoint.service_settings;
|
||||
const modelId =
|
||||
'model_id' in serviceSettings
|
||||
? serviceSettings.model_id
|
||||
: 'model' in serviceSettings
|
||||
? serviceSettings.model
|
||||
: undefined;
|
||||
|
||||
const isEligibleForMITBadge = modelId && ELASTIC_MODEL_DEFINITIONS[modelId]?.license === 'MIT';
|
||||
|
||||
return (
|
||||
<>
|
||||
<EuiText color="subdued" size="xs">
|
||||
{modelId && <ModelBadge model={modelId} />}
|
||||
{isEligibleForMITBadge ? (
|
||||
<EuiBadge
|
||||
color="hollow"
|
||||
iconType="popout"
|
||||
iconSide="right"
|
||||
href={ELASTIC_MODEL_DEFINITIONS[modelId].licenseUrl ?? ''}
|
||||
target="_blank"
|
||||
data-test-subj={'mit-license-badge'}
|
||||
>
|
||||
{i18n.MIT_LICENSE}
|
||||
</EuiBadge>
|
||||
) : null}{' '}
|
||||
{endpointModelAtrributes(endpoint)}
|
||||
</EuiText>
|
||||
</>
|
||||
);
|
||||
};
|
||||
|
||||
function endpointModelAtrributes(endpoint: InferenceAPIConfigResponse) {
|
||||
switch (endpoint.service) {
|
||||
case ServiceProviderKeys.elser:
|
||||
case ServiceProviderKeys.elasticsearch:
|
||||
return elasticsearchAttributes(endpoint);
|
||||
case ServiceProviderKeys.cohere:
|
||||
return cohereAttributes(endpoint);
|
||||
case ServiceProviderKeys.hugging_face:
|
||||
return huggingFaceAttributes(endpoint);
|
||||
case ServiceProviderKeys.openai:
|
||||
return openAIAttributes(endpoint);
|
||||
case ServiceProviderKeys.azureaistudio:
|
||||
return azureOpenAIStudioAttributes(endpoint);
|
||||
case ServiceProviderKeys.azureopenai:
|
||||
return azureOpenAIAttributes(endpoint);
|
||||
case ServiceProviderKeys.mistral:
|
||||
return mistralAttributes(endpoint);
|
||||
case ServiceProviderKeys.googleaistudio:
|
||||
return googleAIStudioAttributes(endpoint);
|
||||
case ServiceProviderKeys.amazonbedrock:
|
||||
return amazonBedrockAttributes(endpoint);
|
||||
default:
|
||||
return null;
|
||||
}
|
||||
}
|
||||
|
||||
function elasticsearchAttributes(endpoint: InferenceAPIConfigResponse) {
|
||||
const serviceSettings = endpoint.service_settings;
|
||||
|
||||
const numAllocations =
|
||||
'num_allocations' in serviceSettings ? serviceSettings.num_allocations : undefined;
|
||||
const numThreads = 'num_threads' in serviceSettings ? serviceSettings.num_threads : undefined;
|
||||
|
||||
return `${numThreads ? i18n.THREADS(numThreads) : ''}${
|
||||
numThreads && numAllocations ? ' | ' : ''
|
||||
}${numAllocations ? i18n.ALLOCATIONS(numAllocations) : ''}`;
|
||||
}
|
||||
|
||||
function cohereAttributes(endpoint: InferenceAPIConfigResponse) {
|
||||
const serviceSettings = endpoint.service_settings;
|
||||
const embeddingType =
|
||||
'embedding_type' in serviceSettings ? serviceSettings.embedding_type : undefined;
|
||||
|
||||
const taskSettings = endpoint.task_settings;
|
||||
const inputType = 'input_type' in taskSettings ? taskSettings.input_type : undefined;
|
||||
const truncate = 'truncate' in taskSettings ? taskSettings.truncate : undefined;
|
||||
|
||||
return [embeddingType, inputType, truncate && `truncate: ${truncate}`].filter(Boolean).join(', ');
|
||||
}
|
||||
|
||||
function huggingFaceAttributes(endpoint: InferenceAPIConfigResponse) {
|
||||
const serviceSettings = endpoint.service_settings;
|
||||
const url = 'url' in serviceSettings ? serviceSettings.url : null;
|
||||
|
||||
return url;
|
||||
}
|
||||
|
||||
function openAIAttributes(endpoint: InferenceAPIConfigResponse) {
|
||||
const serviceSettings = endpoint.service_settings;
|
||||
const url = 'url' in serviceSettings ? serviceSettings.url : null;
|
||||
|
||||
return url;
|
||||
}
|
||||
|
||||
function azureOpenAIStudioAttributes(endpoint: InferenceAPIConfigResponse) {
|
||||
const serviceSettings = endpoint.service_settings;
|
||||
const provider = 'provider' in serviceSettings ? serviceSettings?.provider : undefined;
|
||||
const endpointType =
|
||||
'endpoint_type' in serviceSettings ? serviceSettings.endpoint_type : undefined;
|
||||
const target = 'target' in serviceSettings ? serviceSettings.target : undefined;
|
||||
|
||||
return [provider, endpointType, target].filter(Boolean).join(', ');
|
||||
}
|
||||
|
||||
function azureOpenAIAttributes(endpoint: InferenceAPIConfigResponse) {
|
||||
const serviceSettings = endpoint.service_settings;
|
||||
|
||||
const resourceName =
|
||||
'resource_name' in serviceSettings ? serviceSettings.resource_name : undefined;
|
||||
const deploymentId =
|
||||
'deployment_id' in serviceSettings ? serviceSettings.deployment_id : undefined;
|
||||
const apiVersion = 'api_version' in serviceSettings ? serviceSettings.api_version : undefined;
|
||||
|
||||
return [resourceName, deploymentId, apiVersion].filter(Boolean).join(', ');
|
||||
}
|
||||
|
||||
function mistralAttributes(endpoint: InferenceAPIConfigResponse) {
|
||||
const serviceSettings = endpoint.service_settings;
|
||||
|
||||
const maxInputTokens =
|
||||
'max_input_tokens' in serviceSettings ? serviceSettings.max_input_tokens : undefined;
|
||||
const rateLimit =
|
||||
'rate_limit' in serviceSettings ? serviceSettings.rate_limit.requests_per_minute : undefined;
|
||||
|
||||
return [
|
||||
maxInputTokens && `max_input_tokens: ${maxInputTokens}`,
|
||||
rateLimit && `rate_limit: ${rateLimit}`,
|
||||
]
|
||||
.filter(Boolean)
|
||||
.join(', ');
|
||||
}
|
||||
|
||||
function amazonBedrockAttributes(endpoint: InferenceAPIConfigResponse) {
|
||||
const serviceSettings = endpoint.service_settings;
|
||||
|
||||
const region = 'region' in serviceSettings ? serviceSettings.region : undefined;
|
||||
const provider =
|
||||
'provider' in serviceSettings ? serviceSettings.provider.toLocaleLowerCase() : undefined;
|
||||
|
||||
return [region && `region: ${region}`, provider && `provider: ${provider}`]
|
||||
.filter(Boolean)
|
||||
.join(', ');
|
||||
}
|
||||
|
||||
function googleAIStudioAttributes(endpoint: InferenceAPIConfigResponse) {
|
||||
const serviceSettings = endpoint.service_settings;
|
||||
|
||||
const rateLimit =
|
||||
'rate_limit' in serviceSettings ? serviceSettings.rate_limit.requests_per_minute : undefined;
|
||||
|
||||
return rateLimit && `rate_limit: ${rateLimit}`;
|
||||
}
|
||||
export const EndpointInfo: React.FC<EndpointInfoProps> = ({ inferenceId }) => (
|
||||
<span>
|
||||
<strong>{inferenceId}</strong>
|
||||
</span>
|
||||
);
|
||||
|
|
|
|||
|
|
@ -1,21 +0,0 @@
|
|||
/*
|
||||
* Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
|
||||
* or more contributor license agreements. Licensed under the Elastic License
|
||||
* 2.0; you may not use this file except in compliance with the Elastic License
|
||||
* 2.0.
|
||||
*/
|
||||
|
||||
import React from 'react';
|
||||
import { EuiBadge, useEuiTheme } from '@elastic/eui';
|
||||
|
||||
interface ModelBadgeProps {
|
||||
model?: string;
|
||||
}
|
||||
|
||||
export const ModelBadge: React.FC<ModelBadgeProps> = ({ model }) => {
|
||||
const { euiTheme } = useEuiTheme();
|
||||
|
||||
if (!model) return null;
|
||||
|
||||
return <EuiBadge color={euiTheme.colors.body}>{model}</EuiBadge>;
|
||||
};
|
||||
|
|
@ -8,25 +8,264 @@
|
|||
import { render, screen } from '@testing-library/react';
|
||||
import React from 'react';
|
||||
import { ServiceProvider } from './service_provider';
|
||||
import { ServiceProviderKeys } from '../../types';
|
||||
|
||||
jest.mock('../../../../assets/images/providers/elastic.svg', () => 'elasticIcon.svg');
|
||||
jest.mock('../../../../assets/images/providers/hugging_face.svg', () => 'huggingFaceIcon.svg');
|
||||
jest.mock('../../../../assets/images/providers/cohere.svg', () => 'cohereIcon.svg');
|
||||
jest.mock('../../../../assets/images/providers/open_ai.svg', () => 'openAIIcon.svg');
|
||||
jest.mock('@kbn/ml-trained-models-utils', () => ({
|
||||
...jest.requireActual('@kbn/ml-trained-models-utils'),
|
||||
ELASTIC_MODEL_DEFINITIONS: {
|
||||
'model-with-mit-license': {
|
||||
license: 'MIT',
|
||||
licenseUrl: 'https://abc.com',
|
||||
},
|
||||
},
|
||||
}));
|
||||
|
||||
describe('ServiceProvider component', () => {
|
||||
it('renders Hugging Face icon and name when providerKey is hugging_face', () => {
|
||||
render(<ServiceProvider providerKey={ServiceProviderKeys.hugging_face} />);
|
||||
expect(screen.getByText('Hugging Face')).toBeInTheDocument();
|
||||
const icon = screen.getByTestId('table-column-service-provider-hugging_face');
|
||||
expect(icon).toBeInTheDocument();
|
||||
describe('with HuggingFace service', () => {
|
||||
const mockEndpoint = {
|
||||
inference_id: 'my-hugging-face',
|
||||
service: 'hugging_face',
|
||||
service_settings: {
|
||||
api_key: 'aaaa',
|
||||
url: 'https://dummy.huggingface.com',
|
||||
},
|
||||
task_settings: {},
|
||||
} as any;
|
||||
it('renders the component with service and model details', () => {
|
||||
render(<ServiceProvider providerEndpoint={mockEndpoint} />);
|
||||
|
||||
expect(screen.getByText('Hugging Face')).toBeInTheDocument();
|
||||
const icon = screen.getByTestId('table-column-service-provider-hugging_face');
|
||||
expect(icon).toBeInTheDocument();
|
||||
expect(screen.getByText('https://dummy.huggingface.com')).toBeInTheDocument();
|
||||
});
|
||||
});
|
||||
|
||||
it('renders Open AI icon and name when providerKey is openai', () => {
|
||||
render(<ServiceProvider providerKey={ServiceProviderKeys.openai} />);
|
||||
expect(screen.getByText('OpenAI')).toBeInTheDocument();
|
||||
const icon = screen.getByTestId('table-column-service-provider-openai');
|
||||
expect(icon).toBeInTheDocument();
|
||||
describe('with openai service', () => {
|
||||
const mockEndpoint = {
|
||||
inference_id: 'my-openai-endpoint',
|
||||
service: 'openai',
|
||||
service_settings: {
|
||||
api_key: 'aaaa',
|
||||
model_id: 'text-embedding-3-small',
|
||||
},
|
||||
task_settings: {},
|
||||
} as any;
|
||||
it('renders the component with service and model details', () => {
|
||||
render(<ServiceProvider providerEndpoint={mockEndpoint} />);
|
||||
|
||||
expect(screen.getByText('OpenAI')).toBeInTheDocument();
|
||||
const icon = screen.getByTestId('table-column-service-provider-openai');
|
||||
expect(icon).toBeInTheDocument();
|
||||
expect(screen.getByText('text-embedding-3-small')).toBeInTheDocument();
|
||||
});
|
||||
});
|
||||
|
||||
describe('with cohere service', () => {
|
||||
const mockEndpoint = {
|
||||
inference_id: 'cohere-2',
|
||||
service: 'cohere',
|
||||
service_settings: {
|
||||
similarity: 'cosine',
|
||||
dimensions: 384,
|
||||
model_id: 'embed-english-light-v3.0',
|
||||
rate_limit: {
|
||||
requests_per_minute: 10000,
|
||||
},
|
||||
embedding_type: 'byte',
|
||||
},
|
||||
task_settings: {},
|
||||
} as any;
|
||||
|
||||
it('renders the component with service and model details', () => {
|
||||
render(<ServiceProvider providerEndpoint={mockEndpoint} />);
|
||||
|
||||
expect(screen.getByText('Cohere')).toBeInTheDocument();
|
||||
const icon = screen.getByTestId('table-column-service-provider-cohere');
|
||||
expect(icon).toBeInTheDocument();
|
||||
expect(screen.getByText('embed-english-light-v3.0')).toBeInTheDocument();
|
||||
});
|
||||
|
||||
it('does not render model_id badge if serviceSettings.model_id is not provided', () => {
|
||||
const modifiedEndpoint = {
|
||||
...mockEndpoint,
|
||||
service_settings: { ...mockEndpoint.service_settings, model_id: undefined },
|
||||
};
|
||||
render(<ServiceProvider providerEndpoint={modifiedEndpoint} />);
|
||||
|
||||
expect(screen.queryByText('embed-english-light-v3.0')).not.toBeInTheDocument();
|
||||
});
|
||||
});
|
||||
|
||||
describe('with azureaistudio service', () => {
|
||||
const mockEndpoint = {
|
||||
inference_id: 'azure-ai-1',
|
||||
service: 'azureaistudio',
|
||||
service_settings: {
|
||||
target: 'westus',
|
||||
provider: 'microsoft_phi',
|
||||
endpoint_type: 'realtime',
|
||||
},
|
||||
} as any;
|
||||
|
||||
it('renders the component with endpoint details', () => {
|
||||
render(<ServiceProvider providerEndpoint={mockEndpoint} />);
|
||||
|
||||
expect(screen.getByText('Azure AI Studio')).toBeInTheDocument();
|
||||
const icon = screen.getByTestId('table-column-service-provider-azureaistudio');
|
||||
expect(icon).toBeInTheDocument();
|
||||
expect(screen.getByText('microsoft_phi')).toBeInTheDocument();
|
||||
});
|
||||
|
||||
it('renders nothing related to service settings when all are missing', () => {
|
||||
const modifiedEndpoint = {
|
||||
...mockEndpoint,
|
||||
service_settings: {},
|
||||
};
|
||||
render(<ServiceProvider providerEndpoint={modifiedEndpoint} />);
|
||||
|
||||
expect(screen.getByText('Azure AI Studio')).toBeInTheDocument();
|
||||
const icon = screen.getByTestId('table-column-service-provider-azureaistudio');
|
||||
expect(icon).toBeInTheDocument();
|
||||
expect(screen.queryByText('microsoft_phi')).not.toBeInTheDocument();
|
||||
});
|
||||
});
|
||||
|
||||
describe('with azureopenai service', () => {
|
||||
const mockEndpoint = {
|
||||
inference_id: 'azure-openai-1',
|
||||
service: 'azureopenai',
|
||||
service_settings: {
|
||||
resource_name: 'resource-xyz',
|
||||
deployment_id: 'deployment-123',
|
||||
api_version: 'v1',
|
||||
},
|
||||
} as any;
|
||||
|
||||
it('renders the component with all required endpoint details', () => {
|
||||
render(<ServiceProvider providerEndpoint={mockEndpoint} />);
|
||||
|
||||
expect(screen.getByText('Azure OpenAI')).toBeInTheDocument();
|
||||
const icon = screen.getByTestId('table-column-service-provider-azureopenai');
|
||||
expect(icon).toBeInTheDocument();
|
||||
expect(screen.getByText('resource-xyz')).toBeInTheDocument();
|
||||
});
|
||||
});
|
||||
|
||||
describe('with mistral service', () => {
|
||||
const mockEndpoint = {
|
||||
inference_id: 'mistral-ai-1',
|
||||
service: 'mistral',
|
||||
service_settings: {
|
||||
model: 'model-xyz',
|
||||
max_input_tokens: 512,
|
||||
rate_limit: {
|
||||
requests_per_minute: 1000,
|
||||
},
|
||||
},
|
||||
} as any;
|
||||
|
||||
it('renders the component with endpoint details', () => {
|
||||
render(<ServiceProvider providerEndpoint={mockEndpoint} />);
|
||||
|
||||
expect(screen.getByText('Mistral')).toBeInTheDocument();
|
||||
const icon = screen.getByTestId('table-column-service-provider-mistral');
|
||||
expect(icon).toBeInTheDocument();
|
||||
expect(screen.getByText('model-xyz')).toBeInTheDocument();
|
||||
});
|
||||
|
||||
it('does not render model id if not provided', () => {
|
||||
const modifiedEndpoint = {
|
||||
...mockEndpoint,
|
||||
service_settings: {},
|
||||
};
|
||||
render(<ServiceProvider providerEndpoint={modifiedEndpoint} />);
|
||||
|
||||
const icon = screen.getByTestId('table-column-service-provider-mistral');
|
||||
expect(icon).toBeInTheDocument();
|
||||
expect(screen.getByText('Mistral')).toBeInTheDocument();
|
||||
expect(screen.queryByText('model-xyz')).not.toBeInTheDocument();
|
||||
});
|
||||
});
|
||||
|
||||
describe('with elasticsearch service', () => {
|
||||
const mockEndpoint = {
|
||||
inference_id: 'model-123',
|
||||
service: 'elasticsearch',
|
||||
service_settings: {
|
||||
num_allocations: 5,
|
||||
num_threads: 10,
|
||||
model_id: 'settings-model-123',
|
||||
},
|
||||
} as any;
|
||||
|
||||
it('renders the component with endpoint model_id', () => {
|
||||
render(<ServiceProvider providerEndpoint={mockEndpoint} />);
|
||||
|
||||
expect(screen.getByText('Elasticsearch')).toBeInTheDocument();
|
||||
const icon = screen.getByTestId('table-column-service-provider-elasticsearch');
|
||||
expect(icon).toBeInTheDocument();
|
||||
expect(screen.getByText('settings-model-123')).toBeInTheDocument();
|
||||
});
|
||||
|
||||
it('renders the MIT license badge if the model is eligible', () => {
|
||||
const modifiedEndpoint = {
|
||||
...mockEndpoint,
|
||||
service_settings: { ...mockEndpoint.service_settings, model_id: 'model-with-mit-license' },
|
||||
};
|
||||
render(<ServiceProvider providerEndpoint={modifiedEndpoint} />);
|
||||
|
||||
const mitBadge = screen.getByTestId('mit-license-badge');
|
||||
expect(mitBadge).toBeInTheDocument();
|
||||
expect(mitBadge).toHaveAttribute('href', 'https://abc.com');
|
||||
});
|
||||
|
||||
it('does not render the MIT license badge if the model is not eligible', () => {
|
||||
render(<ServiceProvider providerEndpoint={mockEndpoint} />);
|
||||
|
||||
expect(screen.queryByTestId('mit-license-badge')).not.toBeInTheDocument();
|
||||
});
|
||||
});
|
||||
|
||||
describe('with googleaistudio service', () => {
|
||||
const mockEndpoint = {
|
||||
inference_id: 'google-ai-1',
|
||||
service: 'googleaistudio',
|
||||
service_settings: {
|
||||
model_id: 'model-abc',
|
||||
rate_limit: {
|
||||
requests_per_minute: 500,
|
||||
},
|
||||
},
|
||||
} as any;
|
||||
|
||||
it('renders the component with service and model details', () => {
|
||||
render(<ServiceProvider providerEndpoint={mockEndpoint} />);
|
||||
|
||||
expect(screen.getByText('Google AI Studio')).toBeInTheDocument();
|
||||
const icon = screen.getByTestId('table-column-service-provider-googleaistudio');
|
||||
expect(icon).toBeInTheDocument();
|
||||
expect(screen.getByText('model-abc')).toBeInTheDocument();
|
||||
});
|
||||
});
|
||||
|
||||
describe('with amazonbedrock service', () => {
|
||||
const mockEndpoint = {
|
||||
inference_id: 'amazon-bedrock-1',
|
||||
service: 'amazonbedrock',
|
||||
service_settings: {
|
||||
region: 'us-west-1',
|
||||
provider: 'AMAZONTITAN',
|
||||
model: 'model-bedrock-xyz',
|
||||
},
|
||||
} as any;
|
||||
|
||||
it('renders the component with model and service details', () => {
|
||||
render(<ServiceProvider providerEndpoint={mockEndpoint} />);
|
||||
|
||||
expect(screen.getByText('Amazon Bedrock')).toBeInTheDocument();
|
||||
const icon = screen.getByTestId('table-column-service-provider-amazonbedrock');
|
||||
expect(icon).toBeInTheDocument();
|
||||
expect(screen.getByText('model-bedrock-xyz')).toBeInTheDocument();
|
||||
});
|
||||
});
|
||||
});
|
||||
|
|
|
|||
|
|
@ -5,8 +5,12 @@
|
|||
* 2.0.
|
||||
*/
|
||||
|
||||
import { EuiIcon } from '@elastic/eui';
|
||||
import { EuiBadge, EuiFlexGroup, EuiFlexItem, EuiIcon, EuiText } from '@elastic/eui';
|
||||
import React from 'react';
|
||||
import {
|
||||
ELASTIC_MODEL_DEFINITIONS,
|
||||
InferenceAPIConfigResponse,
|
||||
} from '@kbn/ml-trained-models-utils';
|
||||
import elasticIcon from '../../../../assets/images/providers/elastic.svg';
|
||||
import huggingFaceIcon from '../../../../assets/images/providers/hugging_face.svg';
|
||||
import cohereIcon from '../../../../assets/images/providers/cohere.svg';
|
||||
|
|
@ -17,9 +21,10 @@ import googleAIStudioIcon from '../../../../assets/images/providers/google_ai_st
|
|||
import mistralIcon from '../../../../assets/images/providers/mistral.svg';
|
||||
import amazonBedrockIcon from '../../../../assets/images/providers/amazon_bedrock.svg';
|
||||
import { ServiceProviderKeys } from '../../types';
|
||||
import * as i18n from './translations';
|
||||
|
||||
interface ServiceProviderProps {
|
||||
providerKey: ServiceProviderKeys;
|
||||
providerEndpoint: InferenceAPIConfigResponse;
|
||||
}
|
||||
|
||||
interface ServiceProviderRecord {
|
||||
|
|
@ -50,7 +55,7 @@ export const SERVICE_PROVIDERS: Record<ServiceProviderKeys, ServiceProviderRecor
|
|||
},
|
||||
[ServiceProviderKeys.elser]: {
|
||||
icon: elasticIcon,
|
||||
name: 'ELSER',
|
||||
name: 'Elasticsearch',
|
||||
},
|
||||
[ServiceProviderKeys.googleaistudio]: {
|
||||
icon: googleAIStudioIcon,
|
||||
|
|
@ -70,19 +75,107 @@ export const SERVICE_PROVIDERS: Record<ServiceProviderKeys, ServiceProviderRecor
|
|||
},
|
||||
};
|
||||
|
||||
export const ServiceProvider: React.FC<ServiceProviderProps> = ({ providerKey }) => {
|
||||
const provider = SERVICE_PROVIDERS[providerKey];
|
||||
export const ServiceProvider: React.FC<ServiceProviderProps> = ({ providerEndpoint }) => {
|
||||
const { service } = providerEndpoint;
|
||||
const provider = SERVICE_PROVIDERS[service];
|
||||
|
||||
return provider ? (
|
||||
<>
|
||||
<EuiIcon
|
||||
data-test-subj={`table-column-service-provider-${providerKey}`}
|
||||
type={provider.icon}
|
||||
style={{ marginRight: '8px' }}
|
||||
/>
|
||||
<span>{provider.name}</span>
|
||||
</>
|
||||
<EuiFlexGroup gutterSize="xs" direction="row" alignItems="center">
|
||||
<EuiFlexItem grow={0}>
|
||||
<EuiIcon
|
||||
data-test-subj={`table-column-service-provider-${service}`}
|
||||
type={provider.icon}
|
||||
style={{ marginRight: '8px' }}
|
||||
/>
|
||||
</EuiFlexItem>
|
||||
<EuiFlexItem>
|
||||
<EuiFlexGroup gutterSize="xs" direction="column">
|
||||
<EuiFlexItem>
|
||||
<EuiText size="s" color="subdued">
|
||||
{provider.name}
|
||||
</EuiText>
|
||||
</EuiFlexItem>
|
||||
<EuiFlexItem>
|
||||
<EndpointModelInfo providerEndpoint={providerEndpoint} />
|
||||
</EuiFlexItem>
|
||||
</EuiFlexGroup>
|
||||
</EuiFlexItem>
|
||||
</EuiFlexGroup>
|
||||
) : (
|
||||
<span>{providerKey}</span>
|
||||
<span>{service}</span>
|
||||
);
|
||||
};
|
||||
|
||||
const EndpointModelInfo: React.FC<ServiceProviderProps> = ({ providerEndpoint }) => {
|
||||
const serviceSettings = providerEndpoint.service_settings;
|
||||
const modelId =
|
||||
'model_id' in serviceSettings
|
||||
? serviceSettings.model_id
|
||||
: 'model' in serviceSettings
|
||||
? serviceSettings.model
|
||||
: undefined;
|
||||
|
||||
const isEligibleForMITBadge = modelId && ELASTIC_MODEL_DEFINITIONS[modelId]?.license === 'MIT';
|
||||
|
||||
return (
|
||||
<EuiFlexGroup gutterSize="xs" direction="column">
|
||||
<EuiFlexItem>
|
||||
<EuiFlexGroup gutterSize="xs" direction="row">
|
||||
<EuiFlexItem grow={0}>
|
||||
{modelId && (
|
||||
<EuiText size="s" color="subdued">
|
||||
{modelId}
|
||||
</EuiText>
|
||||
)}
|
||||
</EuiFlexItem>
|
||||
<EuiFlexItem grow={0}>
|
||||
{isEligibleForMITBadge ? (
|
||||
<EuiBadge
|
||||
color="hollow"
|
||||
iconType="popout"
|
||||
iconSide="right"
|
||||
href={ELASTIC_MODEL_DEFINITIONS[modelId].licenseUrl ?? ''}
|
||||
target="_blank"
|
||||
data-test-subj={'mit-license-badge'}
|
||||
>
|
||||
{i18n.MIT_LICENSE}
|
||||
</EuiBadge>
|
||||
) : null}{' '}
|
||||
</EuiFlexItem>
|
||||
</EuiFlexGroup>
|
||||
</EuiFlexItem>
|
||||
<EuiFlexItem>{endpointModelAtrributes(providerEndpoint)}</EuiFlexItem>
|
||||
</EuiFlexGroup>
|
||||
);
|
||||
};
|
||||
|
||||
function endpointModelAtrributes(endpoint: InferenceAPIConfigResponse) {
|
||||
switch (endpoint.service) {
|
||||
case ServiceProviderKeys.hugging_face:
|
||||
return huggingFaceAttributes(endpoint);
|
||||
case ServiceProviderKeys.azureaistudio:
|
||||
return azureOpenAIStudioAttributes(endpoint);
|
||||
case ServiceProviderKeys.azureopenai:
|
||||
return azureOpenAIAttributes(endpoint);
|
||||
default:
|
||||
return null;
|
||||
}
|
||||
}
|
||||
|
||||
function huggingFaceAttributes(endpoint: InferenceAPIConfigResponse) {
|
||||
const serviceSettings = endpoint.service_settings;
|
||||
const url = 'url' in serviceSettings ? serviceSettings.url : null;
|
||||
|
||||
return url;
|
||||
}
|
||||
|
||||
function azureOpenAIStudioAttributes(endpoint: InferenceAPIConfigResponse) {
|
||||
const serviceSettings = endpoint.service_settings;
|
||||
return 'provider' in serviceSettings ? serviceSettings?.provider : undefined;
|
||||
}
|
||||
|
||||
function azureOpenAIAttributes(endpoint: InferenceAPIConfigResponse) {
|
||||
const serviceSettings = endpoint.service_settings;
|
||||
|
||||
return 'resource_name' in serviceSettings ? serviceSettings.resource_name : undefined;
|
||||
}
|
||||
|
|
|
|||
|
|
@ -7,18 +7,6 @@
|
|||
|
||||
import { i18n } from '@kbn/i18n';
|
||||
|
||||
export const THREADS = (numThreads: number) =>
|
||||
i18n.translate('xpack.searchInferenceEndpoints.elasticsearch.threads', {
|
||||
defaultMessage: 'Threads: {numThreads}',
|
||||
values: { numThreads },
|
||||
});
|
||||
|
||||
export const ALLOCATIONS = (numAllocations: number) =>
|
||||
i18n.translate('xpack.searchInferenceEndpoints.elasticsearch.allocations', {
|
||||
defaultMessage: 'Allocations: {numAllocations}',
|
||||
values: { numAllocations },
|
||||
});
|
||||
|
||||
export const MIT_LICENSE = i18n.translate(
|
||||
'xpack.searchInferenceEndpoints.elasticsearch.mitLicense',
|
||||
{
|
||||
|
|
@ -10,8 +10,6 @@ import { screen } from '@testing-library/react';
|
|||
import { render } from '@testing-library/react';
|
||||
import { TabularPage } from './tabular_page';
|
||||
import { InferenceAPIConfigResponse } from '@kbn/ml-trained-models-utils';
|
||||
import { TRAINED_MODEL_STATS_QUERY_KEY } from '../../../common/constants';
|
||||
import { QueryClient, QueryClientProvider } from '@tanstack/react-query';
|
||||
|
||||
const inferenceEndpoints = [
|
||||
{
|
||||
|
|
@ -56,39 +54,26 @@ jest.mock('../../hooks/use_delete_endpoint', () => ({
|
|||
}));
|
||||
|
||||
describe('When the tabular page is loaded', () => {
|
||||
beforeEach(() => {
|
||||
const queryClient = new QueryClient();
|
||||
queryClient.setQueryData([TRAINED_MODEL_STATS_QUERY_KEY], {
|
||||
trained_model_stats: [
|
||||
{
|
||||
model_id: '.elser_model_2',
|
||||
deployment_stats: { deployment_id: 'my-elser-model-05', state: 'started' },
|
||||
},
|
||||
{
|
||||
model_id: '.own_model',
|
||||
deployment_stats: { deployment_id: 'local-model', state: 'started' },
|
||||
},
|
||||
],
|
||||
});
|
||||
const wrapper = ({ children }: { children: React.ReactNode }) => {
|
||||
return <QueryClientProvider client={queryClient}>{children}</QueryClientProvider>;
|
||||
};
|
||||
render(wrapper({ children: <TabularPage inferenceEndpoints={inferenceEndpoints} /> }));
|
||||
});
|
||||
it('should display all inference ids in the table', () => {
|
||||
render(<TabularPage inferenceEndpoints={inferenceEndpoints} />);
|
||||
|
||||
it('should display all model_ids in the table', () => {
|
||||
const rows = screen.getAllByRole('row');
|
||||
expect(rows[1]).toHaveTextContent('local-model');
|
||||
expect(rows[2]).toHaveTextContent('my-elser-model-05');
|
||||
expect(rows[3]).toHaveTextContent('third-party-model');
|
||||
});
|
||||
it('should render deployment status for inference endpoints with local trained models', () => {
|
||||
const deploymentStatusStarted = screen.getAllByTestId('table-column-deployment-started');
|
||||
expect(deploymentStatusStarted).toHaveLength(2);
|
||||
});
|
||||
it('should not render deployment status for third-party endpoints', () => {
|
||||
expect(screen.queryByTestId('table-column-deployment-undefined')).not.toBeInTheDocument();
|
||||
expect(screen.queryByTestId('table-column-deployment-starting')).not.toBeInTheDocument();
|
||||
expect(screen.queryByTestId('table-column-deployment-stopping')).not.toBeInTheDocument();
|
||||
|
||||
it('should display all service and model ids in the table', () => {
|
||||
render(<TabularPage inferenceEndpoints={inferenceEndpoints} />);
|
||||
|
||||
const rows = screen.getAllByRole('row');
|
||||
expect(rows[1]).toHaveTextContent('Elasticsearch');
|
||||
expect(rows[1]).toHaveTextContent('.own_model');
|
||||
|
||||
expect(rows[2]).toHaveTextContent('Elasticsearch');
|
||||
expect(rows[2]).toHaveTextContent('.elser_model_2');
|
||||
|
||||
expect(rows[3]).toHaveTextContent('OpenAI');
|
||||
expect(rows[3]).toHaveTextContent('.own_model');
|
||||
});
|
||||
});
|
||||
|
|
|
|||
|
|
@ -7,26 +7,18 @@
|
|||
|
||||
import React, { useCallback } from 'react';
|
||||
|
||||
import {
|
||||
EuiBasicTable,
|
||||
EuiBasicTableColumn,
|
||||
EuiFlexGroup,
|
||||
EuiFlexItem,
|
||||
HorizontalAlignment,
|
||||
} from '@elastic/eui';
|
||||
import { EuiBasicTable, EuiBasicTableColumn, EuiFlexGroup, EuiFlexItem } from '@elastic/eui';
|
||||
import { InferenceAPIConfigResponse } from '@kbn/ml-trained-models-utils';
|
||||
import { isLocalModel } from '@kbn/ml-trained-models-utils/src/constants/trained_models';
|
||||
import { TaskTypes } from '../../../common/types';
|
||||
import * as i18n from '../../../common/translations';
|
||||
|
||||
import { useTableData } from '../../hooks/use_table_data';
|
||||
import { FilterOptions, InferenceEndpointUI, ServiceProviderKeys } from './types';
|
||||
import { FilterOptions, InferenceEndpointUI } from './types';
|
||||
|
||||
import { useAllInferenceEndpointsState } from '../../hooks/use_all_inference_endpoints_state';
|
||||
import { ServiceProviderFilter } from './filter/service_provider_filter';
|
||||
import { TaskTypeFilter } from './filter/task_type_filter';
|
||||
import { TableSearch } from './search/table_search';
|
||||
import { DeploymentStatus } from './render_table_columns/render_deployment_status/deployment_status';
|
||||
import { EndpointInfo } from './render_table_columns/render_endpoint/endpoint_info';
|
||||
import { ServiceProvider } from './render_table_columns/render_service_provider/service_provider';
|
||||
import { TaskType } from './render_table_columns/render_task_type/task_type';
|
||||
|
|
@ -57,38 +49,32 @@ export const TabularPage: React.FC<TabularPageProps> = ({ inferenceEndpoints })
|
|||
);
|
||||
|
||||
const tableColumns: Array<EuiBasicTableColumn<InferenceEndpointUI>> = [
|
||||
{
|
||||
name: '',
|
||||
render: ({ endpoint, deployment }: InferenceEndpointUI) =>
|
||||
isLocalModel(endpoint) ? <DeploymentStatus status={deployment} /> : null,
|
||||
align: 'center' as HorizontalAlignment,
|
||||
width: '64px',
|
||||
},
|
||||
{
|
||||
field: 'endpoint',
|
||||
name: i18n.ENDPOINT,
|
||||
render: (endpoint: InferenceAPIConfigResponse) => {
|
||||
render: (endpoint: string) => {
|
||||
if (endpoint) {
|
||||
return <EndpointInfo endpoint={endpoint} />;
|
||||
return <EndpointInfo inferenceId={endpoint} />;
|
||||
}
|
||||
|
||||
return null;
|
||||
},
|
||||
sortable: true,
|
||||
truncateText: true,
|
||||
width: '400px',
|
||||
},
|
||||
{
|
||||
field: 'provider',
|
||||
name: i18n.SERVICE_PROVIDER,
|
||||
render: (provider: ServiceProviderKeys) => {
|
||||
render: (provider: InferenceAPIConfigResponse) => {
|
||||
if (provider) {
|
||||
return <ServiceProvider providerKey={provider} />;
|
||||
return <ServiceProvider providerEndpoint={provider} />;
|
||||
}
|
||||
|
||||
return null;
|
||||
},
|
||||
sortable: false,
|
||||
width: '185px',
|
||||
width: '592px',
|
||||
},
|
||||
{
|
||||
field: 'type',
|
||||
|
|
@ -107,7 +93,7 @@ export const TabularPage: React.FC<TabularPageProps> = ({ inferenceEndpoints })
|
|||
actions: [
|
||||
{
|
||||
render: (inferenceEndpoint: InferenceEndpointUI) => (
|
||||
<CopyIDAction inferenceId={inferenceEndpoint.endpoint.inference_id} />
|
||||
<CopyIDAction inferenceId={inferenceEndpoint.endpoint} />
|
||||
),
|
||||
},
|
||||
{
|
||||
|
|
|
|||
|
|
@ -5,9 +5,9 @@
|
|||
* 2.0.
|
||||
*/
|
||||
|
||||
import { DeploymentState, InferenceAPIConfigResponse } from '@kbn/ml-trained-models-utils';
|
||||
import { InferenceAPIConfigResponse } from '@kbn/ml-trained-models-utils';
|
||||
import { TaskTypes } from '../../types';
|
||||
export const INFERENCE_ENDPOINTS_TABLE_PER_PAGE_VALUES = [10, 25, 50, 100];
|
||||
export const INFERENCE_ENDPOINTS_TABLE_PER_PAGE_VALUES = [25, 50, 100];
|
||||
|
||||
export enum ServiceProviderKeys {
|
||||
amazonbedrock = 'amazonbedrock',
|
||||
|
|
@ -56,8 +56,7 @@ export interface EuiBasicTableSortTypes {
|
|||
}
|
||||
|
||||
export interface InferenceEndpointUI {
|
||||
deployment: DeploymentState | undefined;
|
||||
endpoint: InferenceAPIConfigResponse;
|
||||
provider: string;
|
||||
endpoint: string;
|
||||
provider: InferenceAPIConfigResponse;
|
||||
type: string;
|
||||
}
|
||||
|
|
|
|||
|
|
@ -5,7 +5,7 @@
|
|||
* 2.0.
|
||||
*/
|
||||
|
||||
import { EuiPageTemplate, EuiLink, EuiText, EuiSpacer } from '@elastic/eui';
|
||||
import { EuiPageTemplate, EuiLink } from '@elastic/eui';
|
||||
import React from 'react';
|
||||
import * as i18n from '../../common/translations';
|
||||
import { docLinks } from '../../common/doc_links';
|
||||
|
|
@ -18,21 +18,16 @@ export const InferenceEndpointsHeader: React.FC = () => {
|
|||
<EuiPageTemplate.Header
|
||||
data-test-subj="allInferenceEndpointsPage"
|
||||
pageTitle={i18n.INFERENCE_ENDPOINT_LABEL}
|
||||
description={
|
||||
<EuiText>
|
||||
{i18n.MANAGE_INFERENCE_ENDPOINTS_LABEL}
|
||||
<EuiSpacer size="s" />
|
||||
<EuiLink
|
||||
href={docLinks.createInferenceEndpoint}
|
||||
target="_blank"
|
||||
data-test-subj="learn-how-to-create-inference-endpoints"
|
||||
>
|
||||
{i18n.LEARN_HOW_TO_CREATE_INFERENCE_ENDPOINTS_LINK}
|
||||
</EuiLink>
|
||||
</EuiText>
|
||||
}
|
||||
description={i18n.MANAGE_INFERENCE_ENDPOINTS_LABEL}
|
||||
bottomBorder={true}
|
||||
rightSideItems={[
|
||||
<EuiLink
|
||||
href={docLinks.createInferenceEndpoint}
|
||||
target="_blank"
|
||||
data-test-subj="api-documentation"
|
||||
>
|
||||
{i18n.API_DOCUMENTATION_LINK}
|
||||
</EuiLink>,
|
||||
<EuiLink href={trainedModelPageUrl} target="_blank" data-test-subj="view-your-models">
|
||||
{i18n.VIEW_YOUR_MODELS_LINK}
|
||||
</EuiLink>,
|
||||
|
|
|
|||
|
|
@ -118,9 +118,7 @@ describe('useTableData', () => {
|
|||
b.inference_id.localeCompare(a.inference_id)
|
||||
);
|
||||
|
||||
const sortedEndpoints = result.current.sortedTableData.map(
|
||||
(item) => item.endpoint.inference_id
|
||||
);
|
||||
const sortedEndpoints = result.current.sortedTableData.map((item) => item.endpoint);
|
||||
const expectedModelIds = expectedSortedData.map((item) => item.inference_id);
|
||||
|
||||
expect(sortedEndpoints).toEqual(expectedModelIds);
|
||||
|
|
@ -153,19 +151,6 @@ describe('useTableData', () => {
|
|||
{ wrapper }
|
||||
);
|
||||
const filteredData = result.current.sortedTableData;
|
||||
expect(
|
||||
filteredData.every((item) => item.endpoint.inference_id.includes(searchKey))
|
||||
).toBeTruthy();
|
||||
});
|
||||
|
||||
it('should update deployment status based on deploymentStatus object', () => {
|
||||
const { result } = renderHook(
|
||||
() => useTableData(inferenceEndpoints, queryParams, filterOptions, searchKey),
|
||||
{ wrapper }
|
||||
);
|
||||
|
||||
const updatedData = result.current.sortedTableData;
|
||||
|
||||
expect(updatedData[2].deployment).toEqual('started');
|
||||
expect(filteredData.every((item) => item.endpoint.includes(searchKey))).toBeTruthy();
|
||||
});
|
||||
});
|
||||
|
|
|
|||
|
|
@ -7,7 +7,7 @@
|
|||
|
||||
import type { EuiTableSortingType } from '@elastic/eui';
|
||||
import { Pagination } from '@elastic/eui';
|
||||
import { DeploymentState, InferenceAPIConfigResponse } from '@kbn/ml-trained-models-utils';
|
||||
import { InferenceAPIConfigResponse } from '@kbn/ml-trained-models-utils';
|
||||
import { useMemo } from 'react';
|
||||
import { TaskTypes } from '../../common/types';
|
||||
import { DEFAULT_TABLE_LIMIT } from '../components/all_inference_endpoints/constants';
|
||||
|
|
@ -19,7 +19,6 @@ import {
|
|||
SortOrder,
|
||||
ServiceProviderKeys,
|
||||
} from '../components/all_inference_endpoints/types';
|
||||
import { useTrainedModelStats } from './use_trained_model_stats';
|
||||
|
||||
interface UseTableDataReturn {
|
||||
tableData: InferenceEndpointUI[];
|
||||
|
|
@ -35,15 +34,6 @@ export const useTableData = (
|
|||
filterOptions: FilterOptions,
|
||||
searchKey: string
|
||||
): UseTableDataReturn => {
|
||||
const { data: trainedModelStats } = useTrainedModelStats();
|
||||
|
||||
const deploymentStatus = trainedModelStats?.trained_model_stats.reduce((acc, modelStat) => {
|
||||
if (modelStat.deployment_stats?.deployment_id) {
|
||||
acc[modelStat.deployment_stats.deployment_id] = modelStat?.deployment_stats?.state;
|
||||
}
|
||||
return acc;
|
||||
}, {} as Record<string, DeploymentState | undefined>);
|
||||
|
||||
const tableData: InferenceEndpointUI[] = useMemo(() => {
|
||||
let filteredEndpoints = inferenceEndpoints;
|
||||
|
||||
|
|
@ -61,21 +51,12 @@ export const useTableData = (
|
|||
|
||||
return filteredEndpoints
|
||||
.filter((endpoint) => endpoint.inference_id.includes(searchKey))
|
||||
.map((endpoint) => {
|
||||
const isElasticService =
|
||||
endpoint.service === ServiceProviderKeys.elasticsearch ||
|
||||
endpoint.service === ServiceProviderKeys.elser;
|
||||
const deploymentId = isElasticService ? endpoint.inference_id : undefined;
|
||||
const deployment = (deploymentId && deploymentStatus?.[deploymentId]) || undefined;
|
||||
|
||||
return {
|
||||
deployment,
|
||||
endpoint,
|
||||
provider: endpoint.service,
|
||||
type: endpoint.task_type,
|
||||
};
|
||||
});
|
||||
}, [inferenceEndpoints, searchKey, filterOptions, deploymentStatus]);
|
||||
.map((endpoint) => ({
|
||||
endpoint: endpoint.inference_id,
|
||||
provider: endpoint,
|
||||
type: endpoint.task_type,
|
||||
}));
|
||||
}, [inferenceEndpoints, searchKey, filterOptions]);
|
||||
|
||||
const sortedTableData: InferenceEndpointUI[] = useMemo(() => {
|
||||
return [...tableData].sort((a, b) => {
|
||||
|
|
@ -83,9 +64,9 @@ export const useTableData = (
|
|||
const bValue = b[queryParams.sortField];
|
||||
|
||||
if (queryParams.sortOrder === SortOrder.asc) {
|
||||
return aValue.inference_id.localeCompare(bValue.inference_id);
|
||||
return aValue.localeCompare(bValue);
|
||||
} else {
|
||||
return bValue.inference_id.localeCompare(aValue.inference_id);
|
||||
return bValue.localeCompare(aValue);
|
||||
}
|
||||
});
|
||||
}, [tableData, queryParams]);
|
||||
|
|
|
|||
|
|
@ -34242,10 +34242,6 @@
|
|||
"xpack.searchInferenceEndpoints.confirmDeleteEndpoint.title": "Supprimer le point de terminaison d'inférence",
|
||||
"xpack.searchInferenceEndpoints.deleteEndpoint.deleteSuccess": "Le point de terminaison d’inférence a été supprimé avec succès.",
|
||||
"xpack.searchInferenceEndpoints.deleteEndpoint.endpointDeletionFailed": "Échec de la suppression du point de terminaison",
|
||||
"xpack.searchInferenceEndpoints.deploymentStatus.tooltip.modelDeployed": "Le modèle est déployé",
|
||||
"xpack.searchInferenceEndpoints.deploymentStatus.tooltip.modelNotDeployed": "Le modèle n’est pas déployé",
|
||||
"xpack.searchInferenceEndpoints.elasticsearch.allocations": "Allocations : {numAllocations}",
|
||||
"xpack.searchInferenceEndpoints.elasticsearch.threads": "Threads : {numThreads}",
|
||||
"xpack.searchInferenceEndpoints.endpoint": "Point de terminaison",
|
||||
"xpack.searchInferenceEndpoints.filter.emptyMessage": "Aucune option",
|
||||
"xpack.searchInferenceEndpoints.filter.options": "{totalCount, plural, one {# option} other {# options}}",
|
||||
|
|
|
|||
|
|
@ -34226,10 +34226,6 @@
|
|||
"xpack.searchInferenceEndpoints.confirmDeleteEndpoint.title": "推論エンドポイントを削除",
|
||||
"xpack.searchInferenceEndpoints.deleteEndpoint.deleteSuccess": "推論エンドポイントは正常に削除されました。",
|
||||
"xpack.searchInferenceEndpoints.deleteEndpoint.endpointDeletionFailed": "エンドポイントの削除が失敗しました",
|
||||
"xpack.searchInferenceEndpoints.deploymentStatus.tooltip.modelDeployed": "モデルはデプロイされます",
|
||||
"xpack.searchInferenceEndpoints.deploymentStatus.tooltip.modelNotDeployed": "モデルはデプロイされません",
|
||||
"xpack.searchInferenceEndpoints.elasticsearch.allocations": "割り当て：{numAllocations}",
|
||||
"xpack.searchInferenceEndpoints.elasticsearch.threads": "スレッド：{numThreads}",
|
||||
"xpack.searchInferenceEndpoints.endpoint": "エンドポイント",
|
||||
"xpack.searchInferenceEndpoints.filter.emptyMessage": "オプションなし",
|
||||
"xpack.searchInferenceEndpoints.filter.options": "{totalCount, plural, other {# オプション}}",
|
||||
|
|
|
|||
|
|
@ -34267,10 +34267,6 @@
|
|||
"xpack.searchInferenceEndpoints.confirmDeleteEndpoint.title": "删除推理终端",
|
||||
"xpack.searchInferenceEndpoints.deleteEndpoint.deleteSuccess": "推理终端已成功删除。",
|
||||
"xpack.searchInferenceEndpoints.deleteEndpoint.endpointDeletionFailed": "终端删除失败",
|
||||
"xpack.searchInferenceEndpoints.deploymentStatus.tooltip.modelDeployed": "已部署模型",
|
||||
"xpack.searchInferenceEndpoints.deploymentStatus.tooltip.modelNotDeployed": "未部署模型",
|
||||
"xpack.searchInferenceEndpoints.elasticsearch.allocations": "分配：{numAllocations}",
|
||||
"xpack.searchInferenceEndpoints.elasticsearch.threads": "线程：{numThreads}",
|
||||
"xpack.searchInferenceEndpoints.endpoint": "终端",
|
||||
"xpack.searchInferenceEndpoints.filter.emptyMessage": "无选项",
|
||||
"xpack.searchInferenceEndpoints.filter.options": "{totalCount, plural, other {# 个选项}}",
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue