workflow_detail tests

Signed-off-by: saimedhi <saimedhi@amazon.com>

Author: saimedhi

public/pages/workflow_detail/workflow_detail.test.tsx

@@ -57,13 +57,7 @@ const workflowId = '12345';
 const workflowName = 'test_workflow';
 
 describe('WorkflowDetail', () => {
-  const workflowTypes = [
-    WORKFLOW_TYPE.CUSTOM,
-    WORKFLOW_TYPE.SEMANTIC_SEARCH,
-    WORKFLOW_TYPE.HYBRID_SEARCH,
-  ];
-
-  workflowTypes.forEach((type) => {
+  Object.values(WORKFLOW_TYPE).forEach((type) => {
     test(`renders the page with ${type} type`, () => {
       const { getAllByText, getByText, getByRole } = renderWithRouter(
         workflowId,

public/pages/workflows/new_workflow/utils.ts

@@ -60,7 +60,7 @@ export function enrichPresetWorkflowWithUiMetadata(
   } as WorkflowTemplate;
 }
 
-function fetchEmptyMetadata(): UIState {
+export function fetchEmptyMetadata(): UIState {
   return {
     type: WORKFLOW_TYPE.CUSTOM,
     config: {
@@ -125,7 +125,7 @@ function fetchEmptyMetadata(): UIState {
   };
 }
 
-function fetchSemanticSearchMetadata(): UIState {
+export function fetchSemanticSearchMetadata(): UIState {
   let baseState = fetchEmptyMetadata();
   baseState.type = WORKFLOW_TYPE.SEMANTIC_SEARCH;
   baseState.config.ingest.enrich.processors = [new MLIngestProcessor().toObj()];
@@ -143,7 +143,7 @@ function fetchSemanticSearchMetadata(): UIState {
   return baseState;
 }
 
-function fetchMultimodalSearchMetadata(): UIState {
+export function fetchMultimodalSearchMetadata(): UIState {
   let baseState = fetchEmptyMetadata();
   baseState.type = WORKFLOW_TYPE.MULTIMODAL_SEARCH;
   baseState.config.ingest.enrich.processors = [new MLIngestProcessor().toObj()];
@@ -163,7 +163,7 @@ function fetchMultimodalSearchMetadata(): UIState {
   return baseState;
 }
 
-function fetchHybridSearchMetadata(): UIState {
+export function fetchHybridSearchMetadata(): UIState {
   let baseState = fetchEmptyMetadata();
   baseState.type = WORKFLOW_TYPE.HYBRID_SEARCH;
   baseState.config.ingest.enrich.processors = [new MLIngestProcessor().toObj()];

test/utils.ts

@@ -3,12 +3,14 @@
  * SPDX-License-Identifier: Apache-2.0
  */
 
-import { PROCESSOR_TYPE, WORKFLOW_TYPE } from '../common/constants';
+import { WORKFLOW_TYPE } from '../common/constants';
+import { UIState, Workflow } from '../common/interfaces';
 import {
-  IProcessorConfig,
-  ProcessorsConfig,
-  Workflow,
-} from '../common/interfaces';
+  fetchEmptyMetadata,
+  fetchHybridSearchMetadata,
+  fetchMultimodalSearchMetadata,
+  fetchSemanticSearchMetadata,
+} from '../public/pages/workflows/new_workflow/utils';
 
 export function mockStore(
   workflowId: string,
@@ -49,222 +51,30 @@ function generateWorkflow(
     id: workflowId,
     name: workflowName,
     version: { template: '1.0.0', compatibility: ['2.17.0', '3.0.0'] },
-    ui_metadata: {
-      type: workflowType,
-      config: {
-        search: {
-          pipelineName: {
-            id: 'pipelineName',
-            type: 'string',
-            value: 'search_pipeline',
-          },
-          request: {
-            id: 'request',
-            type: 'json',
-            value: '{\n "query": {\n "match_all": {}\n },\n "size": 1000\n}',
-          },
-          index: { name: { id: 'indexName', type: 'string' } },
-          enrichRequest: getRequestProcessor(workflowType),
-          enrichResponse: getResponseProcessor(workflowType),
-        },
-        ingest: {
-          pipelineName: {
-            id: 'pipelineName',
-            type: 'string',
-            value: 'ingest_pipeline',
-          },
-          enrich: getRequestProcessor(workflowType),
-          index: {
-            settings: { id: 'indexSettings', type: 'json' },
-            mappings: {
-              id: 'indexMappings',
-              type: 'json',
-              value: '{\n "properties": {}\n}',
-            },
-            name: {
-              id: 'indexName',
-              type: 'string',
-              value: 'my-new-index',
-            },
-          },
-          enabled: { id: 'enabled', type: 'boolean', value: true },
-        },
-      },
-    },
+    ui_metadata: getConfig(workflowType),
   };
 }
-
-function getRequestProcessor(workflowType: WORKFLOW_TYPE): ProcessorsConfig {
-  if (
-    workflowType === WORKFLOW_TYPE.HYBRID_SEARCH ||
-    workflowType === WORKFLOW_TYPE.SEMANTIC_SEARCH
-  ) {
-    // TODO: In the code below, only the ml_inference processor has been added. Other processors still need to be included.
-    const mlInferenceProcessor: IProcessorConfig = {
-      name: 'ML Inference Processor',
-      id: 'ml_processor_ingest',
-      fields: [
-        {
-          id: 'model',
-          type: 'model',
-          value: {
-            id: 'dfMPE5EB8_-RPNi-S0gD',
-          },
-        },
-        {
-          id: 'input_map',
-          type: 'mapArray',
-          value: [
-            [
-              {
-                value: 'my_text',
-                key: '',
-              },
-            ],
-          ],
-        },
-        {
-          id: 'output_map',
-          type: 'mapArray',
-          value: [
-            [
-              {
-                value: '',
-                key: 'my_embedding',
-              },
-            ],
-          ],
-        },
-      ],
-      type: PROCESSOR_TYPE.ML,
-      optionalFields: [
-        {
-          id: 'query_template',
-          type: 'jsonString',
-          value: getQueryTemplate(workflowType),
-        },
-        {
-          id: 'description',
-          type: 'string',
-        },
-        {
-          id: 'model_config',
-          type: 'json',
-        },
-        {
-          id: 'full_response_path',
-          type: 'boolean',
-          value: false,
-        },
-        {
-          id: 'ignore_missing',
-          type: 'boolean',
-          value: false,
-        },
-        {
-          id: 'ignore_failure',
-          type: 'boolean',
-          value: false,
-        },
-        {
-          id: 'max_prediction_tasks',
-          type: 'number',
-          value: 10,
-        },
-        {
-          id: 'tag',
-          type: 'string',
-        },
-      ],
-    };
-    return {
-      processors: [mlInferenceProcessor],
-    };
-  }
-
-  return { processors: [] };
-}
-
-// Function to get the query template based on workflow type
-function getQueryTemplate(workflowType: WORKFLOW_TYPE) {
-  if (workflowType === WORKFLOW_TYPE.HYBRID_SEARCH) {
-    return `{
-      "_source": {
-        "excludes": ["my_embedding"]
-      },
-      "query": {
-        "hybrid": {
-          "queries": [
-            {
-              "match": {
-                "my_text": {
-                  "query": "{{query_text}}"
-                }
-              }
-            },
-            {
-              "knn": {
-                "my_embedding": {
-                  "vector": jest.fn(),
-                  "k": 10
-                }
-              }
-            }
-          ]
-        }
-      }
-    }`;
-  }
-
-  if (workflowType === WORKFLOW_TYPE.SEMANTIC_SEARCH) {
-    return `{
-      "_source": {
-        "excludes": ["my_embedding"]
-      },
-      "query": {
-        "knn": {
-          "my_embedding": {
-            "vector": jest.fn(),
-            "k": 10
-          }
-        }
-      }
-    }`;
+function getConfig(workflowType: WORKFLOW_TYPE) {
+  let uiMetadata = {} as UIState;
+  switch (workflowType) {
+    case WORKFLOW_TYPE.SEMANTIC_SEARCH: {
+      uiMetadata = fetchSemanticSearchMetadata();
+      break;
+    }
+    case WORKFLOW_TYPE.MULTIMODAL_SEARCH: {
+      uiMetadata = fetchMultimodalSearchMetadata();
+      break;
+    }
+    case WORKFLOW_TYPE.HYBRID_SEARCH: {
+      uiMetadata = fetchHybridSearchMetadata();
+      break;
+    }
+    default: {
+      uiMetadata = fetchEmptyMetadata();
+      break;
+    }
   }
-}
-
-function getResponseProcessor(workflowType: WORKFLOW_TYPE): ProcessorsConfig {
-  return workflowType === WORKFLOW_TYPE.HYBRID_SEARCH
-    ? {
-        processors: [
-          {
-            id: 'normalization_processor',
-            name: 'Normalization Processor',
-            type: PROCESSOR_TYPE.NORMALIZATION,
-            fields: [],
-            optionalFields: [
-              { id: 'weights', type: 'string', value: '0.5, 0.5' },
-              {
-                id: 'normalization_technique',
-                type: 'select',
-                selectOptions: ['min_max', 'l2'],
-              },
-              {
-                id: 'combination_technique',
-                type: 'select',
-                selectOptions: [
-                  'arithmetic_mean',
-                  'geometric_mean',
-                  'harmonic_mean',
-                ],
-              },
-              { id: 'description', type: 'string' },
-              { id: 'tag', type: 'string' },
-            ],
-          },
-        ],
-      }
-    : { processors: [] };
+  return uiMetadata;
 }
 
 export const resizeObserverMock = jest.fn().mockImplementation(() => ({