refactor predictable: add method to check if model is ready

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

@@ -89,6 +89,8 @@ public void writeTo(StreamOutput out) throws IOException {
         if (headers != null) {
             out.writeBoolean(true);
             out.writeMap(headers, StreamOutput::writeString, StreamOutput::writeString);
+        } else {
+            out.writeBoolean(false);
         }
         out.writeOptionalString(requestBody);
         out.writeOptionalString(preProcessFunction);

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

@@ -5,8 +5,22 @@
 
 package org.opensearch.ml.common.connector;
 
+import java.util.Arrays;
+import java.util.Set;
+
 public class ConnectorProtocols {
 
     public static final String HTTP = "http";
     public static final String AWS_SIGV4 = "aws_sigv4";
+
+    public static final Set<String> VALID_PROTOCOLS = Set.of(HTTP, AWS_SIGV4);
+
+    public static void validateProtocol(String protocol) {
+        if (protocol == null) {
+            throw new IllegalArgumentException("Connector protocol is null. Please use one of [" + Arrays.toString(VALID_PROTOCOLS.toArray(new String[0]))+ "]");
+        }
+        if (!VALID_PROTOCOLS.contains(protocol)) {
+            throw new IllegalArgumentException("Unsupported connector protocol. Please use one of [" + Arrays.toString(VALID_PROTOCOLS.toArray(new String[0]))+ "]");
+        }
+    }
 }

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

@@ -28,6 +28,7 @@
 
 import static org.opensearch.common.xcontent.XContentParserUtils.ensureExpectedToken;
 import static org.opensearch.ml.common.connector.ConnectorProtocols.HTTP;
+import static org.opensearch.ml.common.connector.ConnectorProtocols.validateProtocol;
 import static org.opensearch.ml.common.utils.StringUtils.getParameterMap;
 import static org.opensearch.ml.common.utils.StringUtils.isJson;
 
@@ -47,6 +48,7 @@ public class HttpConnector extends AbstractConnector {
     public HttpConnector(String name, String description, String version, String protocol,
                          Map<String, String> parameters, Map<String, String> credential, List<ConnectorAction> actions,
                          List<String> backendRoles, AccessMode accessMode) {
+        validateProtocol(protocol);
         this.name = name;
         this.description = description;
         this.version = version;

ml-algorithms/src/main/java/org/opensearch/ml/engine/Predictable.java

@@ -45,4 +45,10 @@ public interface Predictable {
      * Close resources like deployed model.
      */
     void close();
+
+    /**
+     * Check if model ready to be used.
+     * @return
+     */
+    boolean isModelReady();
 }

ml-algorithms/src/main/java/org/opensearch/ml/engine/algorithms/DLModel.java

@@ -157,6 +157,14 @@ public void close() {
         }
     }
 
+    @Override
+    public boolean isModelReady() {
+        if (predictors == null || modelHelper == null || modelId == null) {
+            return false;
+        }
+        return true;
+    }
+
     public abstract Translator<Input, Output> getTranslator(String engine, MLModelConfig modelConfig);
 
     public abstract TranslatorFactory getTranslatorFactory(String engine, MLModelConfig modelConfig);

ml-algorithms/src/main/java/org/opensearch/ml/engine/algorithms/ad/AnomalyDetectionLibSVM.java

@@ -84,6 +84,11 @@ public void close() {
         this.libSVMAnomalyModel = null;
     }
 
+    @Override
+    public boolean isModelReady() {
+        return libSVMAnomalyModel != null;
+    }
+
     @Override
     public MLOutput predict(MLInput mlInput) {
         MLInputDataset inputDataset = mlInput.getInputDataset();

ml-algorithms/src/main/java/org/opensearch/ml/engine/algorithms/clustering/KMeans.java

@@ -98,6 +98,11 @@ public void close() {
         this.kMeansModel = null;
     }
 
+    @Override
+    public boolean isModelReady() {
+        return kMeansModel != null;
+    }
+
     @Override
     public MLOutput predict(MLInput mlInput) {
         DataFrame dataFrame = ((DataFrameInputDataset)mlInput.getInputDataset()).getDataFrame();

ml-algorithms/src/main/java/org/opensearch/ml/engine/algorithms/clustering/RCFSummarize.java

@@ -145,6 +145,11 @@ public void close() {
         this.summary = null;
     }
 
+    @Override
+    public boolean isModelReady() {
+        return summary != null;
+    }
+
     @Override
     public MLOutput predict(MLInput mlInput) {
         Iterable<float[]> centroidsLst = Arrays.asList(summary.summaryPoints);

ml-algorithms/src/main/java/org/opensearch/ml/engine/algorithms/rcf/BatchRandomCutForest.java

@@ -82,6 +82,11 @@ public void close() {
         forest = null;
     }
 
+    @Override
+    public boolean isModelReady() {
+        return forest != null;
+    }
+
     @Override
     public MLOutput predict(MLInput mlInput) {
         DataFrame dataFrame = ((DataFrameInputDataset)mlInput.getInputDataset()).getDataFrame();

ml-algorithms/src/main/java/org/opensearch/ml/engine/algorithms/rcf/FixedInTimeRandomCutForest.java

@@ -110,6 +110,11 @@ public void close() {
         this.forest = null;
     }
 
+    @Override
+    public boolean isModelReady() {
+        return forest != null;
+    }
+
     @Override
     public MLOutput predict(MLInput mlInput) {
         DataFrame dataFrame = ((DataFrameInputDataset)mlInput.getInputDataset()).getDataFrame();

ml-algorithms/src/main/java/org/opensearch/ml/engine/algorithms/regression/LinearRegression.java

@@ -209,6 +209,11 @@ public void close() {
         this.regressionModel = null;
     }
 
+    @Override
+    public boolean isModelReady() {
+        return regressionModel != null;
+    }
+
     @Override
     public MLOutput predict(MLInput mlInput) {
         if (regressionModel == null) {

ml-algorithms/src/main/java/org/opensearch/ml/engine/algorithms/regression/LogisticRegression.java

@@ -202,6 +202,11 @@ public void close() {
         this.classificationModel = null;
     }
 
+    @Override
+    public boolean isModelReady() {
+        return classificationModel != null;
+    }
+
     @Override
     public MLOutput predict(MLInput mlInput) {
         DataFrame dataFrame = ((DataFrameInputDataset)mlInput.getInputDataset()).getDataFrame();

ml-algorithms/src/main/java/org/opensearch/ml/engine/algorithms/remote/RemoteModel.java

@@ -5,11 +5,7 @@
 
 package org.opensearch.ml.engine.algorithms.remote;
 
-import ai.djl.modality.Input;
-import ai.djl.modality.Output;
-import ai.djl.translate.TranslateException;
-import ai.djl.translate.Translator;
-import ai.djl.translate.TranslatorFactory;
+import com.google.common.annotations.VisibleForTesting;
 import lombok.extern.log4j.Log4j2;
 import org.opensearch.client.Client;
 import org.opensearch.cluster.service.ClusterService;
@@ -19,11 +15,9 @@
 import org.opensearch.ml.common.connector.Connector;
 import org.opensearch.ml.common.exception.MLException;
 import org.opensearch.ml.common.input.MLInput;
-import org.opensearch.ml.common.model.MLModelConfig;
 import org.opensearch.ml.common.output.MLOutput;
-import org.opensearch.ml.common.output.model.ModelTensorOutput;
 import org.opensearch.ml.engine.MLEngineClassLoader;
-import org.opensearch.ml.engine.algorithms.DLModel;
+import org.opensearch.ml.engine.Predictable;
 import org.opensearch.ml.engine.annotation.Function;
 import org.opensearch.ml.engine.encryptor.Encryptor;
 import org.opensearch.script.ScriptService;
@@ -32,27 +26,51 @@
 
 @Log4j2
 @Function(FunctionName.REMOTE)
-public class RemoteModel extends DLModel {
+public class RemoteModel implements Predictable {
 
     public static final String CLUSTER_SERVICE = "cluster_service";
     public static final String SCRIPT_SERVICE = "script_service";
     public static final String CLIENT = "client";
     public static final String XCONTENT_REGISTRY = "xcontent_registry";
+
     private RemoteConnectorExecutor connectorExecutor;
 
+    @VisibleForTesting
+    RemoteConnectorExecutor getConnectorExecutor() {
+        return this.connectorExecutor;
+    }
+
+    @Override
+    public MLOutput predict(MLInput mlInput, MLModel model) {
+        throw new IllegalArgumentException(
+                "Model not ready yet. Please run this first: POST /_plugins/_ml/models/" + model.getModelId() + "/_deploy"
+        );
+    }
+
     @Override
     public MLOutput predict(MLInput mlInput) {
+        if (!isModelReady()) {
+            throw new IllegalArgumentException("Model not ready yet. Please run this first: POST /_plugins/_ml/models/<model_id>/_deploy");
+        }
         try {
-            return predict(modelId, mlInput);
-        } catch (Throwable t) {
-            log.error("Failed to call remote model", t);
-            throw new MLException("Failed to call remote model. " + t.getMessage());
+            return connectorExecutor.executePredict(mlInput);
+        } catch (RuntimeException e) {
+            log.error("Failed to call remote model", e);
+            throw e;
+        } catch (Throwable e) {
+            log.error("Failed to call remote model", e);
+            throw new MLException(e);
         }
     }
 
     @Override
-    public ModelTensorOutput predict(String modelId, MLInput mlInput) throws TranslateException {
-        return connectorExecutor.executePredict(mlInput);
+    public void close() {
+        this.connectorExecutor = null;
+    }
+
+    @Override
+    public boolean isModelReady() {
+        return connectorExecutor != null;
     }
 
     @Override
@@ -65,21 +83,13 @@ public void initModel(MLModel model, Map<String, Object> params, Encryptor encry
             this.connectorExecutor.setClusterService((ClusterService) params.get(CLUSTER_SERVICE));
             this.connectorExecutor.setClient((Client) params.get(CLIENT));
             this.connectorExecutor.setXContentRegistry((NamedXContentRegistry) params.get(XCONTENT_REGISTRY));
-        } catch (Exception e) {
+        } catch (RuntimeException e) {
+            log.error("Failed to init remote model", e);
+            throw e;
+        } catch (Throwable e) {
             log.error("Failed to init remote model", e);
             throw new MLException(e);
         }
     }
 
-    @Override
-    public Translator<Input, Output> getTranslator(String engine, MLModelConfig modelConfig) {
-        return null;
-    }
-
-    @Override
-    public TranslatorFactory getTranslatorFactory(String engine, MLModelConfig modelConfig) {
-        return null;
-    }
-
-
 }

ml-algorithms/src/main/java/org/opensearch/ml/engine/algorithms/sample/SampleAlgo.java

@@ -48,6 +48,11 @@ public void close() {
         sampleParam = DEFAULT_SAMPLE_PARAM;
     }
 
+    @Override
+    public boolean isModelReady() {
+        return true;
+    }
+
     @Override
     public MLOutput predict(MLInput mlInput) {
         AtomicReference<Double> sum = new AtomicReference<>((double) 0);

ml-algorithms/src/test/java/org/opensearch/ml/engine/algorithms/remote/AwsConnectorExecutorTest.java

@@ -80,7 +80,7 @@ public void executePredict_RemoteInferenceInput_MissingCredential() {
                 .url("http://test.com/mock")
                 .requestBody("{\"input\": \"${parameters.input}\"}")
                 .build();
-        AwsConnector.awsConnectorBuilder().name("test connector").version("1").actions(Arrays.asList(predictAction)).build();
+        AwsConnector.awsConnectorBuilder().name("test connector").protocol("http").version("1").actions(Arrays.asList(predictAction)).build();
     }
 
     @Test
@@ -99,7 +99,7 @@ public void executePredict_RemoteInferenceInput_NullResponse() throws IOExceptio
                 .build();
         Map<String, String> credential = ImmutableMap.of(ACCESS_KEY_FIELD, encryptor.encrypt("test_key"), SECRET_KEY_FIELD, encryptor.encrypt("test_secret_key"));
         Map<String, String> parameters = ImmutableMap.of(REGION_FIELD, "us-west-2", SERVICE_NAME_FIELD, "sagemaker");
-        Connector connector = AwsConnector.awsConnectorBuilder().name("test connector").version("1").parameters(parameters).credential(credential).actions(Arrays.asList(predictAction)).build();
+        Connector connector = AwsConnector.awsConnectorBuilder().name("test connector").version("1").protocol("http").parameters(parameters).credential(credential).actions(Arrays.asList(predictAction)).build();
         connector.decrypt((c) -> encryptor.decrypt(c));
         AwsConnectorExecutor executor = spy(new AwsConnectorExecutor(connector, httpClient));
 
@@ -124,7 +124,7 @@ public void executePredict_RemoteInferenceInput() throws IOException {
                 .build();
         Map<String, String> credential = ImmutableMap.of(ACCESS_KEY_FIELD, encryptor.encrypt("test_key"), SECRET_KEY_FIELD, encryptor.encrypt("test_secret_key"));
         Map<String, String> parameters = ImmutableMap.of(REGION_FIELD, "us-west-2", SERVICE_NAME_FIELD, "sagemaker");
-        Connector connector = AwsConnector.awsConnectorBuilder().name("test connector").version("1").parameters(parameters).credential(credential).actions(Arrays.asList(predictAction)).build();
+        Connector connector = AwsConnector.awsConnectorBuilder().name("test connector").version("1").protocol("http").parameters(parameters).credential(credential).actions(Arrays.asList(predictAction)).build();
         connector.decrypt((c) -> encryptor.decrypt(c));
         AwsConnectorExecutor executor = spy(new AwsConnectorExecutor(connector, httpClient));
 

ml-algorithms/src/test/java/org/opensearch/ml/engine/algorithms/remote/ConnectorUtilsTest.java

@@ -67,7 +67,7 @@ public void processInput_TextDocsInputDataSet_NoPreprocessFunction() {
                 .url("http://test.com/mock")
                 .requestBody("{\"input\": \"${parameters.input}\"}")
                 .build();
-        Connector connector = HttpConnector.builder().name("test connector").version("1").actions(Arrays.asList(predictAction)).build();
+        Connector connector = HttpConnector.builder().name("test connector").version("1").protocol("http").actions(Arrays.asList(predictAction)).build();
         ConnectorUtils.processInput(mlInput, connector, new HashMap<>(), scriptService);
     }
 
@@ -104,7 +104,7 @@ public void processOutput_NoPostprocessFunction() throws IOException {
                 .build();
         Map<String, String> parameters = new HashMap<>();
         parameters.put("key1", "value1");
-        Connector connector = HttpConnector.builder().name("test connector").version("1").parameters(parameters).actions(Arrays.asList(predictAction)).build();
+        Connector connector = HttpConnector.builder().name("test connector").version("1").protocol("http").parameters(parameters).actions(Arrays.asList(predictAction)).build();
         ModelTensors tensors = ConnectorUtils.processOutput("{\"response\": \"test response\"}", connector, scriptService, ImmutableMap.of());
         Assert.assertEquals(1, tensors.getMlModelTensors().size());
         Assert.assertEquals("response", tensors.getMlModelTensors().get(0).getName());
@@ -126,7 +126,7 @@ public void processOutput_PostprocessFunction() throws IOException {
                 .build();
         Map<String, String> parameters = new HashMap<>();
         parameters.put("key1", "value1");
-        Connector connector = HttpConnector.builder().name("test connector").version("1").parameters(parameters).actions(Arrays.asList(predictAction)).build();
+        Connector connector = HttpConnector.builder().name("test connector").version("1").protocol("http").parameters(parameters).actions(Arrays.asList(predictAction)).build();
         String modelResponse = "{\"object\":\"list\",\"data\":[{\"object\":\"embedding\",\"index\":0,\"embedding\":[-0.014555434,-0.0002135904,0.0035105038]}],\"model\":\"text-embedding-ada-002-v2\",\"usage\":{\"prompt_tokens\":5,\"total_tokens\":5}}";
         ModelTensors tensors = ConnectorUtils.processOutput(modelResponse, connector, scriptService, ImmutableMap.of());
         Assert.assertEquals(1, tensors.getMlModelTensors().size());
@@ -153,7 +153,7 @@ private void processInput_TextDocsInputDataSet_PreprocessFunction(String request
                 .build();
         Map<String, String> parameters = new HashMap<>();
         parameters.put("key1", "value1");
-        Connector connector = HttpConnector.builder().name("test connector").version("1").parameters(parameters).actions(Arrays.asList(predictAction)).build();
+        Connector connector = HttpConnector.builder().name("test connector").version("1").protocol("http").parameters(parameters).actions(Arrays.asList(predictAction)).build();
         RemoteInferenceInputDataSet remoteInferenceInputDataSet = ConnectorUtils.processInput(mlInput, connector, new HashMap<>(), scriptService);
         Assert.assertNotNull(remoteInferenceInputDataSet.getParameters());
         Assert.assertEquals(1, remoteInferenceInputDataSet.getParameters().size());

ml-algorithms/src/test/java/org/opensearch/ml/engine/algorithms/remote/HttpJsonConnectorExecutorTest.java

@@ -66,7 +66,7 @@ public void invokeRemoteModel_WrongHttpMethod() {
                 .url("http://test.com/mock")
                 .requestBody("{\"input\": \"${parameters.input}\"}")
                 .build();
-        Connector connector = HttpConnector.builder().name("test connector").version("1").actions(Arrays.asList(predictAction)).build();
+        Connector connector = HttpConnector.builder().name("test connector").version("1").protocol("http").actions(Arrays.asList(predictAction)).build();
         HttpJsonConnectorExecutor executor = new HttpJsonConnectorExecutor(connector);
         executor.invokeRemoteModel(null, null, null, null);
     }
@@ -79,7 +79,7 @@ public void executePredict_RemoteInferenceInput() throws IOException {
                 .url("http://test.com/mock")
                 .requestBody("{\"input\": \"${parameters.input}\"}")
                 .build();
-        Connector connector = HttpConnector.builder().name("test connector").version("1").actions(Arrays.asList(predictAction)).build();
+        Connector connector = HttpConnector.builder().name("test connector").version("1").protocol("http").actions(Arrays.asList(predictAction)).build();
         HttpJsonConnectorExecutor executor = spy(new HttpJsonConnectorExecutor(connector));
         when(httpClient.execute(any())).thenReturn(response);
         HttpEntity entity = new StringEntity("{\"response\": \"test result\"}");
@@ -103,7 +103,7 @@ public void executePredict_TextDocsInput_NoPreprocessFunction() {
                 .url("http://test.com/mock")
                 .requestBody("{\"input\": \"${parameters.input}\"}")
                 .build();
-        Connector connector = HttpConnector.builder().name("test connector").version("1").actions(Arrays.asList(predictAction)).build();
+        Connector connector = HttpConnector.builder().name("test connector").version("1").protocol("http").actions(Arrays.asList(predictAction)).build();
         HttpJsonConnectorExecutor executor = new HttpJsonConnectorExecutor(connector);
         MLInputDataset inputDataSet = TextDocsInputDataSet.builder().docs(Arrays.asList("test doc1", "test doc2")).build();
         executor.executePredict(MLInput.builder().algorithm(FunctionName.REMOTE).inputDataset(inputDataSet).build());
@@ -129,7 +129,7 @@ public void executePredict_TextDocsInput() throws IOException {
                 .postProcessFunction(MLPostProcessFunction.OPENAI_EMBEDDING)
                 .requestBody("{\"input\": \"${parameters.input}\"}")
                 .build();
-        Connector connector = HttpConnector.builder().name("test connector").version("1").actions(Arrays.asList(predictAction)).build();
+        Connector connector = HttpConnector.builder().name("test connector").version("1").protocol("http").actions(Arrays.asList(predictAction)).build();
         HttpJsonConnectorExecutor executor = spy(new HttpJsonConnectorExecutor(connector));
         executor.setScriptService(scriptService);
         when(httpClient.execute(any())).thenReturn(response);