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[ML] API integration tests for PUT /internal/ml/trained_models/:modelId endpoint (#178124)

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Dima Arnautov 2024-03-07 06:47:31 +01:00 • committed by GitHub
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1
x-pack/test/api_integration/apis/ml/trained_models/index.ts
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@ -13,6 +13,7 @@ export default function ({ loadTestFile }: FtrProviderContext) {
loadTestFile(require.resolve('./get_model_stats'));
loadTestFile(require.resolve('./get_model_pipelines'));
loadTestFile(require.resolve('./delete_model'));
loadTestFile(require.resolve('./put_model'));
loadTestFile(require.resolve('./start_stop_deployment'));
});
}

82
x-pack/test/api_integration/apis/ml/trained_models/put_model.ts Normal file
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@ -0,0 +1,82 @@
/*
* 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 expect from '@kbn/expect';
import { omit } from 'lodash';
import { FtrProviderContext } from '../../../ftr_provider_context';
import { USER } from '../../../../functional/services/ml/security_common';
import { getCommonRequestHeader } from '../../../../functional/services/ml/common_api';
export default ({ getService }: FtrProviderContext) => {
const supertest = getService('supertestWithoutAuth');
const ml = getService('ml');
describe('PUT trained_models', () => {
before(async () => {
await ml.api.initSavedObjects();
await ml.testResources.setKibanaTimeZoneToUTC();
});
after(async () => {
await ml.api.cleanMlIndices();
await ml.testResources.cleanMLSavedObjects();
});
it('puts trained model by id', async () => {
const testModelId = 'dfa_regression_model_n_0';
const requestBody = ml.api.createTestTrainedModelConfig(testModelId, 'regression').body;
const { body: putResponseBody, status: putResponseStatus } = await supertest
.put(`/internal/ml/trained_models/${testModelId}`)
.auth(USER.ML_POWERUSER, ml.securityCommon.getPasswordForUser(USER.ML_POWERUSER))
.set(getCommonRequestHeader('1'))
.send(requestBody);
ml.api.assertResponseStatusCode(200, putResponseStatus, putResponseBody);
expect(omit(putResponseBody, 'create_time')).to.eql({
model_id: 'dfa_regression_model_n_0',
model_type: 'tree_ensemble',
created_by: 'api_user',
version: '12.0.0',
model_size_bytes: 304,
estimated_operations: 1,
license_level: 'platinum',
tags: [],
input: { field_names: ['common_field'] },
inference_config: {
regression: { results_field: 'predicted_value', num_top_feature_importance_values: 0 },
},
});
// verify that model is actually created
const { body: getResponseBody, status: getResponseStatus } = await supertest
.get(`/internal/ml/trained_models/${testModelId}`)
.auth(USER.ML_POWERUSER, ml.securityCommon.getPasswordForUser(USER.ML_POWERUSER))
.set(getCommonRequestHeader('1'));
ml.api.assertResponseStatusCode(200, getResponseStatus, getResponseBody);
});
it('does not allow to put trained model if the user does not have required permissions', async () => {
const testModelId = 'dfa_regression_model_n_1';
const requestBody = ml.api.createTestTrainedModelConfig(testModelId, 'regression').body;
const { body: putResponseBody, status: putResponseStatus } = await supertest
.put(`/internal/ml/trained_models/${testModelId}`)
.auth(USER.ML_VIEWER, ml.securityCommon.getPasswordForUser(USER.ML_VIEWER))
.set(getCommonRequestHeader('1'))
.send(requestBody);
ml.api.assertResponseStatusCode(403, putResponseStatus, putResponseBody);
// verify that model has not been created
const { body, status } = await supertest
.get(`/internal/ml/trained_models/${testModelId}`)
.auth(USER.ML_POWERUSER, ml.securityCommon.getPasswordForUser(USER.ML_POWERUSER))
.set(getCommonRequestHeader('1'));
ml.api.assertResponseStatusCode(404, status, body);
});
});
};