format code

Signed-off-by: zane-neo <zaniu@amazon.com>

Author: zane-neo

plugin/src/test/java/org/opensearch/ml/rest/RestMLRemoteInferenceIT.java

@@ -8,7 +8,6 @@
 import java.io.IOException;
 import java.util.List;
 import java.util.Map;
-import java.util.concurrent.TimeUnit;
 import java.util.function.Consumer;
 
 import org.apache.commons.lang3.exception.ExceptionUtils;
@@ -216,49 +215,49 @@ public void testDeployRemoteModel() throws IOException, InterruptedException {
         waitForTask(taskId, MLTaskState.COMPLETED);
     }
 
-//    public void testPredictWithAutoDeployAndTTL_RemoteModel() throws IOException, InterruptedException {
-//        // Skip test if key is null
-//        if (OPENAI_KEY == null) {
-//            System.out.println("OPENAI_KEY is null");
-//            return;
-//        }
-//        Response updateCBSettingResponse = TestHelper
-//            .makeRequest(
-//                client(),
-//                "PUT",
-//                "_cluster/settings",
-//                null,
-//                "{\"persistent\":{\"plugins.ml_commons.jvm_heap_memory_threshold\":100}}",
-//                ImmutableList.of(new BasicHeader(HttpHeaders.USER_AGENT, ""))
-//            );
-//        assertEquals(200, updateCBSettingResponse.getStatusLine().getStatusCode());
-//
-//        Response response = createConnector(completionModelConnectorEntity);
-//        Map responseMap = parseResponseToMap(response);
-//        String connectorId = (String) responseMap.get("connector_id");
-//        response = registerRemoteModelWithTTLAndSkipHeapMemCheck("openAI-GPT-3.5 completions", connectorId, 1);
-//        responseMap = parseResponseToMap(response);
-//        String modelId = (String) responseMap.get("model_id");
-//        String predictInput = "{\n" + "  \"parameters\": {\n" + "      \"prompt\": \"Say this is a test\"\n" + "  }\n" + "}";
-//        response = predictRemoteModel(modelId, predictInput);
-//        responseMap = parseResponseToMap(response);
-//        List responseList = (List) responseMap.get("inference_results");
-//        responseMap = (Map) responseList.get(0);
-//        responseList = (List) responseMap.get("output");
-//        responseMap = (Map) responseList.get(0);
-//        responseMap = (Map) responseMap.get("dataAsMap");
-//        responseList = (List) responseMap.get("choices");
-//        if (responseList == null) {
-//            assertTrue(checkThrottlingOpenAI(responseMap));
-//            return;
-//        }
-//        responseMap = (Map) responseList.get(0);
-//        assertFalse(((String) responseMap.get("text")).isEmpty());
-//
-//        getModelProfile(modelId, verifyRemoteModelDeployed());
-//        TimeUnit.SECONDS.sleep(71);
-//        assertTrue(getModelProfile(modelId, verifyRemoteModelDeployed()).isEmpty());
-//    }
+    // public void testPredictWithAutoDeployAndTTL_RemoteModel() throws IOException, InterruptedException {
+    // // Skip test if key is null
+    // if (OPENAI_KEY == null) {
+    // System.out.println("OPENAI_KEY is null");
+    // return;
+    // }
+    // Response updateCBSettingResponse = TestHelper
+    // .makeRequest(
+    // client(),
+    // "PUT",
+    // "_cluster/settings",
+    // null,
+    // "{\"persistent\":{\"plugins.ml_commons.jvm_heap_memory_threshold\":100}}",
+    // ImmutableList.of(new BasicHeader(HttpHeaders.USER_AGENT, ""))
+    // );
+    // assertEquals(200, updateCBSettingResponse.getStatusLine().getStatusCode());
+    //
+    // Response response = createConnector(completionModelConnectorEntity);
+    // Map responseMap = parseResponseToMap(response);
+    // String connectorId = (String) responseMap.get("connector_id");
+    // response = registerRemoteModelWithTTLAndSkipHeapMemCheck("openAI-GPT-3.5 completions", connectorId, 1);
+    // responseMap = parseResponseToMap(response);
+    // String modelId = (String) responseMap.get("model_id");
+    // String predictInput = "{\n" + " \"parameters\": {\n" + " \"prompt\": \"Say this is a test\"\n" + " }\n" + "}";
+    // response = predictRemoteModel(modelId, predictInput);
+    // responseMap = parseResponseToMap(response);
+    // List responseList = (List) responseMap.get("inference_results");
+    // responseMap = (Map) responseList.get(0);
+    // responseList = (List) responseMap.get("output");
+    // responseMap = (Map) responseList.get(0);
+    // responseMap = (Map) responseMap.get("dataAsMap");
+    // responseList = (List) responseMap.get("choices");
+    // if (responseList == null) {
+    // assertTrue(checkThrottlingOpenAI(responseMap));
+    // return;
+    // }
+    // responseMap = (Map) responseList.get(0);
+    // assertFalse(((String) responseMap.get("text")).isEmpty());
+    //
+    // getModelProfile(modelId, verifyRemoteModelDeployed());
+    // TimeUnit.SECONDS.sleep(71);
+    // assertTrue(getModelProfile(modelId, verifyRemoteModelDeployed()).isEmpty());
+    // }
 
     public void testPredictRemoteModelWithInterface(String testCase, Consumer<Map> verifyResponse, Consumer<Exception> verifyException)
         throws IOException,