[ML] Add integration tests for trained_models API

x-pack/test/api_integration/apis/ml/index.ts

@@ -82,5 +82,6 @@ export default function ({ getService, loadTestFile }: FtrProviderContext) {
     loadTestFile(require.resolve('./results'));
     loadTestFile(require.resolve('./saved_objects'));
     loadTestFile(require.resolve('./system'));
+    loadTestFile(require.resolve('./trained_models'));
   });
 }

x-pack/test/api_integration/apis/ml/trained_models/get_models.ts

@@ -0,0 +1,66 @@
+/*
+ * 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 { FtrProviderContext } from '../../../ftr_provider_context';
+import { USER } from '../../../../functional/services/ml/security_common';
+import { COMMON_REQUEST_HEADERS } from '../../../../functional/services/ml/common_api';
+
+export default ({ getService }: FtrProviderContext) => {
+  const supertest = getService('supertestWithoutAuth');
+  const ml = getService('ml');
+
+  describe('GET trained_models', () => {
+    let testModelIds: string[] = [];
+
+    before(async () => {
+      await ml.testResources.setKibanaTimeZoneToUTC();
+      testModelIds = await ml.api.createdTestTrainedModels('regression', 5, true);
+    });
+
+    after(async () => {
+      await ml.api.cleanMlIndices();
+      // delete created ingest pipelines
+      await Promise.all(testModelIds.map((modelId) => ml.api.deleteIngestPipeline(modelId)));
+    });
+
+    it('returns all trained models with associated pipelined', async () => {
+      const { body } = await supertest
+        .get(`/api/ml/trained_models?with_pipelines=true`)
+        .auth(USER.ML_POWERUSER, ml.securityCommon.getPasswordForUser(USER.ML_POWERUSER))
+        .set(COMMON_REQUEST_HEADERS)
+        .expect(200);
+      // Created models + system model
+      expect(body.length).to.eql(6);
+
+      const sampleModel = body.find((v: any) => v.model_id === 'dfa_regression_model_n_0');
+      expect(Object.keys(sampleModel.pipelines).length).to.eql(1);
+    });
+
+    it('returns models without pipeline in case user does not have required permission', async () => {
+      const { body } = await supertest
+        .get(`/api/ml/trained_models?with_pipelines=true`)
+        .auth(USER.ML_VIEWER, ml.securityCommon.getPasswordForUser(USER.ML_VIEWER))
+        .set(COMMON_REQUEST_HEADERS)
+        .expect(200);
+      // Created models + system model
+      expect(body.length).to.eql(6);
+      const sampleModel = body.find((v: any) => v.model_id === 'dfa_regression_model_n_0');
+      expect(sampleModel.pipelines).to.eql(undefined);
+    });
+
+    it('returns trained model by id', async () => {
+      const { body } = await supertest
+        .get(`/api/ml/trained_models/dfa_regression_model_n_1`)
+        .auth(USER.ML_VIEWER, ml.securityCommon.getPasswordForUser(USER.ML_VIEWER))
+        .set(COMMON_REQUEST_HEADERS)
+        .expect(200);
+      expect(body.length).to.eql(1);
+      expect(body[0].model_id).to.eql('dfa_regression_model_n_1');
+    });
+  });
+};

x-pack/test/api_integration/apis/ml/trained_models/index.ts

@@ -0,0 +1,14 @@
+/*
+ * 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 { FtrProviderContext } from '../../../ftr_provider_context';
+
+export default function ({ loadTestFile }: FtrProviderContext) {
+  describe('trained models', function () {
+    loadTestFile(require.resolve('./get_models'));
+  });
+}

x-pack/test/functional/services/ml/api.ts

@@ -8,6 +8,8 @@
 import { estypes } from '@elastic/elasticsearch';
 import expect from '@kbn/expect';
 import { ProvidedType } from '@kbn/test';
+import fs from 'fs';
+import path from 'path';
 import { Calendar } from '../../../../plugins/ml/server/models/calendar/index';
 import { Annotation } from '../../../../plugins/ml/common/types/annotations';
 import { DataFrameAnalyticsConfig } from '../../../../plugins/ml/public/application/data_frame_analytics/common';
@@ -25,6 +27,8 @@ import {
 import { COMMON_REQUEST_HEADERS } from '../../../functional/services/ml/common_api';
 import { PutTrainedModelConfig } from '../../../../plugins/ml/common/types/trained_models';
 
+type ModelType = 'regression' | 'classification';
+
 export function MachineLearningAPIProvider({ getService }: FtrProviderContext) {
   const es = getService('es');
   const log = getService('log');
@@ -943,5 +947,85 @@ export function MachineLearningAPIProvider({ getService }: FtrProviderContext) {
       log.debug('> Trained model crated');
       return model;
     },
+
+    async createdTestTrainedModels(
+      modelType: ModelType,
+      count: number = 10,
+      withIngestPipelines = false
+    ) {
+      const compressedDefinition = this.getCompressedModelDefinition(modelType);
+
+      const modelIds = new Array(count).fill(null).map((v, i) => `dfa_${modelType}_model_n_${i}`);
+
+      const models = modelIds.map((id) => {
+        return {
+          model_id: id,
+          body: {
+            compressed_definition: compressedDefinition,
+            inference_config: {
+              [modelType]: {},
+            },
+            input: {
+              field_names: ['common_field'],
+            },
+          } as PutTrainedModelConfig,
+        };
+      });
+
+      for (const model of models) {
+        await this.createTrainedModel(model.model_id, model.body);
+        if (withIngestPipelines) {
+          await this.createIngestPipeline(model.model_id);
+        }
+      }
+
+      return modelIds;
+    },
+
+    /**
+     * Retrieves compressed model definition from the test resources.
+     * @param modelType
+     */
+    getCompressedModelDefinition(modelType: ModelType) {
+      return fs.readFileSync(
+        path.resolve(
+          __dirname,
+          'resources',
+          'trained_model_definitions',
+          `minimum_valid_config_${modelType}.json.gz.b64`
+        ),
+        'utf-8'
+      );
+    },
+
+    /**
+     * Creates ingest pipelines for trained model
+     * @param modelId
+     */
+    async createIngestPipeline(modelId: string) {
+      log.debug(`Creating ingest pipeline for trained model with id "${modelId}"`);
+      const ingestPipeline = await esSupertest
+        .put(`/_ingest/pipeline/pipeline_${modelId}`)
+        .send({
+          processors: [
+            {
+              inference: {
+                model_id: modelId,
+              },
+            },
+          ],
+        })
+        .expect(200)
+        .then((res) => res.body);
+
+      log.debug('> Ingest pipeline crated');
+      return ingestPipeline;
+    },
+
+    async deleteIngestPipeline(modelId: string) {
+      log.debug(`Deleting ingest pipeline for trained model with id "${modelId}"`);
+      await esSupertest.delete(`/_ingest/pipeline/pipeline_${modelId}`).expect(200);
+      log.debug('> Ingest pipeline deleted');
+    },
   };
 }

x-pack/test/functional/services/ml/trained_models.ts

@@ -5,12 +5,9 @@
  * 2.0.
  */
 
-import fs from 'fs';
-import path from 'path';
 import expect from '@kbn/expect';
 import { FtrProviderContext } from '../../ftr_provider_context';
 import { MlApi } from './api';
-import { PutTrainedModelConfig } from '../../../../plugins/ml/common/types/trained_models';
 import { MlCommonUI } from './common_ui';
 
 type ModelType = 'regression' | 'classification';
@@ -24,38 +21,7 @@ export function TrainedModelsProvider(
 
   return {
     async createdTestTrainedModels(modelType: ModelType, count: number = 10) {
-      const compressedDefinition = this.getCompressedModelDefinition(modelType);
-
-      const models = new Array(count).fill(null).map((v, i) => {
-        return {
-          model_id: `dfa_${modelType}_model_n_${i}`,
-          body: {
-            compressed_definition: compressedDefinition,
-            inference_config: {
-              [modelType]: {},
-            },
-            input: {
-              field_names: ['common_field'],
-            },
-          } as PutTrainedModelConfig,
-        };
-      });
-
-      for (const model of models) {
-        await mlApi.createTrainedModel(model.model_id, model.body);
-      }
-    },
-
-    getCompressedModelDefinition(modelType: ModelType) {
-      return fs.readFileSync(
-        path.resolve(
-          __dirname,
-          'resources',
-          'trained_model_definitions',
-          `minimum_valid_config_${modelType}.json.gz.b64`
-        ),
-        'utf-8'
-      );
+      await mlApi.createdTestTrainedModels(modelType, count);
     },
 
     async assertStats(expectedTotalCount: number) {