[Enterprise Search] fix(index inference pipelines): fetch models on e…

…lser deploy (#157318)

## Summary

Updated the inference pipeline flyout logic to refetch ml models when
the user deploys the ELSER text expansion model. This will allow them to
select the model if they deploy it from the flyout.


https://github.com/elastic/kibana/assets/1972968/25916c61-cdad-4213-8034-265aaac1f945

Co-authored-by: Kibana Machine <42973632+kibanamachine@users.noreply.github.com>

x-pack/plugins/enterprise_search/public/applications/enterprise_search_content/components/search_index/pipelines/ml_inference/ml_inference_logic.test.ts

@@ -16,6 +16,7 @@ import { TrainedModelState } from '../../../../../../../common/types/pipelines';
 import { GetDocumentsApiLogic } from '../../../../api/documents/get_document_logic';
 import { MappingsApiLogic } from '../../../../api/mappings/mappings_logic';
 import { MLModelsApiLogic } from '../../../../api/ml_models/ml_models_logic';
+import { StartTextExpansionModelApiLogic } from '../../../../api/ml_models/text_expansion/start_text_expansion_model_api_logic';
 import { AttachMlInferencePipelineApiLogic } from '../../../../api/pipelines/attach_ml_inference_pipeline';
 import { CreateMlInferencePipelineApiLogic } from '../../../../api/pipelines/create_ml_inference_pipeline';
 import { FetchMlInferencePipelineProcessorsApiLogic } from '../../../../api/pipelines/fetch_ml_inference_pipeline_processors';
@@ -85,6 +86,7 @@ describe('MlInferenceLogic', () => {
     FetchMlInferencePipelinesApiLogic
   );
   const { mount: mountGetDocumentsApiLogic } = new LogicMounter(GetDocumentsApiLogic);
+  const { mount: mountStartTextExpansionModel } = new LogicMounter(StartTextExpansionModelApiLogic);
 
   beforeEach(() => {
     jest.clearAllMocks();
@@ -97,6 +99,7 @@ describe('MlInferenceLogic', () => {
     mountCreateMlInferencePipelineApiLogic();
     mountAttachMlInferencePipelineApiLogic();
     mountGetDocumentsApiLogic();
+    mountStartTextExpansionModel();
     mount();
   });
 
@@ -628,5 +631,16 @@ describe('MlInferenceLogic', () => {
         });
       });
     });
+    describe('startTextExpansionModelSuccess', () => {
+      it('fetches ml models', () => {
+        jest.spyOn(MLInferenceLogic.actions, 'makeMLModelsRequest');
+        StartTextExpansionModelApiLogic.actions.apiSuccess({
+          deploymentState: 'started',
+          modelId: 'foo',
+        });
+
+        expect(MLInferenceLogic.actions.makeMLModelsRequest).toHaveBeenCalledWith(undefined);
+      });
+    });
   });
 });

x-pack/plugins/enterprise_search/public/applications/enterprise_search_content/components/search_index/pipelines/ml_inference/ml_inference_logic.ts

@@ -39,6 +39,10 @@ import {
   TrainedModelsApiLogicActions,
   TrainedModelsApiLogic,
 } from '../../../../api/ml_models/ml_trained_models_logic';
+import {
+  StartTextExpansionModelApiLogic,
+  StartTextExpansionModelApiLogicActions,
+} from '../../../../api/ml_models/text_expansion/start_text_expansion_model_api_logic';
 import {
   AttachMlInferencePipelineApiLogic,
   AttachMlInferencePipelineApiLogicArgs,
@@ -156,6 +160,7 @@ interface MLInferenceProcessorsActions {
   setInferencePipelineConfiguration: (configuration: InferencePipelineConfiguration) => {
     configuration: InferencePipelineConfiguration;
   };
+  startTextExpansionModelSuccess: StartTextExpansionModelApiLogicActions['apiSuccess'];
 }
 
 export interface AddInferencePipelineModal {
@@ -230,6 +235,8 @@ export const MLInferenceLogic = kea<
       ],
       PipelinesLogic,
       ['closeAddMlInferencePipelineModal as closeAddMlInferencePipelineModal'],
+      StartTextExpansionModelApiLogic,
+      ['apiSuccess as startTextExpansionModelSuccess'],
     ],
     values: [
       CachedFetchIndexApiLogic,
@@ -316,6 +323,10 @@ export const MLInferenceLogic = kea<
         });
       }
     },
+    startTextExpansionModelSuccess: () => {
+      // Refresh ML models list when the text expansion model is started
+      actions.makeMLModelsRequest(undefined);
+    },
   }),
   path: ['enterprise_search', 'content', 'pipelines_add_ml_inference_pipeline'],
   reducers: {