Prevents Locale Code build failures opensearch-project#2967 (opensearch-project#2980) (opensearch-project#2991)

* Prevents future UT build issues addresses opensearch-project#2967

Depending on the GitHub CI workflow executes it will invoke ./gradlew build which will run tests on random parameters everytime, there are local-code's that will break a build one of them being az-Cyrl. The solution here was preventing (explicitly writing the local to be set to en-US) Github actions building on these random parameters that will interupt a build and lose time. Manual testing was done to prove that using this flag breaks a build, you can check the issue opensearch-project#2967 or you can run ./gradlew build -Dtests.local=az-Cyrl to see it breaks

Signed-off-by: Brian Flores <[email protected]>

* Updates current codebase with Local.Root to string operations

The previous commit made a hard change on the build while ignoring the root problem, which was making sure that our codebase currently supports string operations regardless of the locale code. In this new commit String operations like toUpperCase have a extra argument of Locale.Root making the codebase agnostic to the rules of other langugages such as Spanish or Turkish. Manual testing was done like raised in the GitHub issue opensearch-project#2967 also ./gradlew build -Dtests.Local=az-Cyrl passes

Signed-off-by: Brian Flores <[email protected]>

---------

Signed-off-by: Brian Flores <[email protected]>
(cherry picked from commit cd83590)

Co-authored-by: Brian Flores <[email protected]>

Author: opensearch-trigger-bot[bot]

common/src/main/java/org/opensearch/ml/common/connector/ConnectorAction.java

@@ -208,7 +208,7 @@ public static boolean isValidActionInModelPrediction(ActionType actionType) {
 
         public static boolean isValidAction(String action) {
             try {
-                ActionType.valueOf(action.toUpperCase());
+                ActionType.valueOf(action.toUpperCase(Locale.ROOT));
                 return true;
             } catch (IllegalArgumentException e) {
                 return false;

common/src/main/java/org/opensearch/ml/common/input/parameter/clustering/RCFSummarizeParams.java

@@ -8,6 +8,7 @@
 import static org.opensearch.core.xcontent.XContentParserUtils.ensureExpectedToken;
 
 import java.io.IOException;
+import java.util.Locale;
 
 import org.opensearch.core.ParseField;
 import org.opensearch.core.common.io.stream.StreamInput;
@@ -97,7 +98,7 @@ public static MLAlgoParams parse(XContentParser parser) throws IOException {
                     parallel = parser.booleanValue();
                     break;
                 case DISTANCE_TYPE_FIELD:
-                    distanceType = DistanceType.from(parser.text().toUpperCase());
+                    distanceType = DistanceType.from(parser.text().toUpperCase(Locale.ROOT));
                     break;
                 default:
                     parser.skipChildren();

ml-algorithms/src/main/java/org/opensearch/ml/engine/algorithms/agent/MLAgentExecutor.java

@@ -13,6 +13,7 @@
 import java.security.PrivilegedExceptionAction;
 import java.util.ArrayList;
 import java.util.List;
+import java.util.Locale;
 import java.util.Map;
 
 import org.opensearch.ResourceNotFoundException;
@@ -281,7 +282,7 @@ private ActionListener<Object> createAgentActionListener(
 
     @VisibleForTesting
     protected MLAgentRunner getAgentRunner(MLAgent mlAgent) {
-        final MLAgentType agentType = MLAgentType.from(mlAgent.getType().toUpperCase());
+        final MLAgentType agentType = MLAgentType.from(mlAgent.getType().toUpperCase(Locale.ROOT));
         switch (agentType) {
             case FLOW:
                 return new MLFlowAgentRunner(client, settings, clusterService, xContentRegistry, toolFactories, memoryFactoryMap);

plugin/src/main/java/org/opensearch/ml/action/batch/TransportBatchIngestionAction.java

@@ -15,6 +15,7 @@
 
 import java.time.Instant;
 import java.util.List;
+import java.util.Locale;
 import java.util.Map;
 import java.util.regex.Pattern;
 import java.util.stream.Collectors;
@@ -101,7 +102,7 @@ protected void doExecute(Task task, ActionRequest request, ActionListener<MLBatc
                     mlTaskManager.add(mlTask);
                     listener.onResponse(new MLBatchIngestionResponse(taskId, MLTaskType.BATCH_INGEST, MLTaskState.CREATED.name()));
                     String ingestType = (String) mlBatchIngestionInput.getDataSources().get(TYPE);
-                    Ingestable ingestable = MLEngineClassLoader.initInstance(ingestType.toLowerCase(), client, Client.class);
+                    Ingestable ingestable = MLEngineClassLoader.initInstance(ingestType.toLowerCase(Locale.ROOT), client, Client.class);
                     threadPool.executor(INGEST_THREAD_POOL).execute(() -> {
                         executeWithErrorHandling(() -> {
                             double successRate = ingestable.ingest(mlBatchIngestionInput);
@@ -193,7 +194,7 @@ private void validateBatchIngestInput(MLBatchIngestionInput mlBatchIngestionInpu
         if (dataSources.get(TYPE) == null || dataSources.get(SOURCE) == null) {
             throw new IllegalArgumentException("The batch ingest input data source is missing data type or source");
         }
-        if (((String) dataSources.get(TYPE)).toLowerCase() == "s3") {
+        if (((String) dataSources.get(TYPE)).equalsIgnoreCase("s3")) {
             List<String> s3Uris = (List<String>) dataSources.get(SOURCE);
             if (s3Uris == null || s3Uris.isEmpty()) {
                 throw new IllegalArgumentException("The batch ingest input s3Uris is empty");

plugin/src/main/java/org/opensearch/ml/rest/RestMLPredictionAction.java

@@ -130,7 +130,8 @@ MLPredictionTaskRequest getRequest(String modelId, String algorithm, RestRequest
         ActionType actionType = ActionType.from(getActionTypeFromRestRequest(request));
         if (FunctionName.REMOTE.name().equals(algorithm) && !mlFeatureEnabledSetting.isRemoteInferenceEnabled()) {
             throw new IllegalStateException(REMOTE_INFERENCE_DISABLED_ERR_MSG);
-        } else if (FunctionName.isDLModel(FunctionName.from(algorithm.toUpperCase())) && !mlFeatureEnabledSetting.isLocalModelEnabled()) {
+        } else if (FunctionName.isDLModel(FunctionName.from(algorithm.toUpperCase(Locale.ROOT)))
+            && !mlFeatureEnabledSetting.isLocalModelEnabled()) {
             throw new IllegalStateException(LOCAL_MODEL_DISABLED_ERR_MSG);
         } else if (ActionType.BATCH_PREDICT == actionType && !mlFeatureEnabledSetting.isOfflineBatchInferenceEnabled()) {
             throw new IllegalStateException(BATCH_INFERENCE_DISABLED_ERR_MSG);