add model input validation for local models in ml processor (opensearch-project#2610) (opensearch-project#2615)

* add model input validation for local models in ml processor

Signed-off-by: Bhavana Ramaram <rbhavna@amazon.com>

---------

Signed-off-by: Bhavana Ramaram <rbhavna@amazon.com>
(cherry picked from commit 2b953cd)

Co-authored-by: Bhavana Ramaram <rbhavna@amazon.com>

Author: opensearch-trigger-bot[bot]

plugin/src/main/java/org/opensearch/ml/processor/MLInferenceIngestProcessor.java

@@ -72,6 +72,7 @@ public class MLInferenceIngestProcessor extends AbstractProcessor implements Mod
     // At default, ml inference processor allows maximum 10 prediction tasks running in parallel
     // it can be overwritten using max_prediction_tasks when creating processor
     public static final int DEFAULT_MAX_PREDICTION_TASKS = 10;
+    public static final String DEFAULT_MODEl_INPUT = "{ \"parameters\": ${ml_inference.parameters} }";
     private final NamedXContentRegistry xContentRegistry;
 
     private Configuration suppressExceptionConfiguration = Configuration
@@ -489,10 +490,19 @@ public MLInferenceIngestProcessor create(
             boolean override = ConfigurationUtils.readBooleanProperty(TYPE, processorTag, config, OVERRIDE, false);
             String functionName = ConfigurationUtils
                 .readStringProperty(TYPE, processorTag, config, FUNCTION_NAME, FunctionName.REMOTE.name());
-            String modelInput = ConfigurationUtils
-                .readStringProperty(TYPE, processorTag, config, MODEL_INPUT, "{ \"parameters\": ${ml_inference.parameters} }");
-            boolean defaultValue = !functionName.equalsIgnoreCase("remote");
-            boolean fullResponsePath = ConfigurationUtils.readBooleanProperty(TYPE, processorTag, config, FULL_RESPONSE_PATH, defaultValue);
+
+            String modelInput = ConfigurationUtils.readOptionalStringProperty(TYPE, processorTag, config, MODEL_INPUT);
+
+            // if model input is not provided for remote models, use default value
+            if (functionName.equalsIgnoreCase("remote")) {
+                modelInput = (modelInput != null) ? modelInput : DEFAULT_MODEl_INPUT;
+            } else if (modelInput == null) {
+                // if model input is not provided for local models, throw exception since it is mandatory here
+                throw new IllegalArgumentException("Please provide model input when using a local model in ML Inference Processor");
+            }
+            boolean defaultFullResponsePath = !functionName.equalsIgnoreCase(FunctionName.REMOTE.name());
+            boolean fullResponsePath = ConfigurationUtils
+                .readBooleanProperty(TYPE, processorTag, config, FULL_RESPONSE_PATH, defaultFullResponsePath);
 
             boolean ignoreFailure = ConfigurationUtils
                 .readBooleanProperty(TYPE, processorTag, config, ConfigurationUtils.IGNORE_FAILURE_KEY, false);

plugin/src/test/java/org/opensearch/ml/processor/MLInferenceIngestProcessorFactoryTests.java

@@ -174,4 +174,60 @@ public void testCreateOptionalFields() throws Exception {
         assertEquals(mLInferenceIngestProcessor.getTag(), processorTag);
         assertEquals(mLInferenceIngestProcessor.getType(), MLInferenceIngestProcessor.TYPE);
     }
+
+    public void testLocalModel() throws Exception {
+        Map<String, Processor.Factory> registry = new HashMap<>();
+        Map<String, Object> config = new HashMap<>();
+        config.put(MODEL_ID, "model2");
+        config.put(FUNCTION_NAME, "text_embedding");
+        Map<String, Object> model_config = new HashMap<>();
+        model_config.put("return_number", true);
+        config.put(MODEL_CONFIG, model_config);
+        config.put(MODEL_INPUT, "{ \"text_docs\": ${ml_inference.text_docs} }");
+        List<Map<String, String>> inputMap = new ArrayList<>();
+        Map<String, String> input = new HashMap<>();
+        input.put("text_docs", "chunks.*.chunk.text.*.context");
+        inputMap.add(input);
+        List<Map<String, String>> outputMap = new ArrayList<>();
+        Map<String, String> output = new HashMap<>();
+        output.put("chunks.*.chunk.text.*.embedding", "$.inference_results.*.output[2].data");
+        outputMap.add(output);
+        config.put(INPUT_MAP, inputMap);
+        config.put(OUTPUT_MAP, outputMap);
+        config.put(MAX_PREDICTION_TASKS, 5);
+        String processorTag = randomAlphaOfLength(10);
+
+        MLInferenceIngestProcessor mLInferenceIngestProcessor = factory.create(registry, processorTag, null, config);
+        assertNotNull(mLInferenceIngestProcessor);
+        assertEquals(mLInferenceIngestProcessor.getTag(), processorTag);
+        assertEquals(mLInferenceIngestProcessor.getType(), MLInferenceIngestProcessor.TYPE);
+    }
+
+    public void testModelInputIsNullForLocalModels() throws Exception {
+        Map<String, Processor.Factory> registry = new HashMap<>();
+        Map<String, Object> config = new HashMap<>();
+        config.put(MODEL_ID, "model2");
+        config.put(FUNCTION_NAME, "text_embedding");
+        Map<String, Object> model_config = new HashMap<>();
+        model_config.put("return_number", true);
+        config.put(MODEL_CONFIG, model_config);
+        List<Map<String, String>> inputMap = new ArrayList<>();
+        Map<String, String> input = new HashMap<>();
+        input.put("text_docs", "chunks.*.chunk.text.*.context");
+        inputMap.add(input);
+        List<Map<String, String>> outputMap = new ArrayList<>();
+        Map<String, String> output = new HashMap<>();
+        output.put("chunks.*.chunk.text.*.embedding", "$.inference_results.*.output[2].data");
+        outputMap.add(output);
+        config.put(INPUT_MAP, inputMap);
+        config.put(OUTPUT_MAP, outputMap);
+        config.put(MAX_PREDICTION_TASKS, 5);
+        String processorTag = randomAlphaOfLength(10);
+
+        try {
+            factory.create(registry, processorTag, null, config);
+        } catch (IllegalArgumentException e) {
+            assertEquals(e.getMessage(), ("Please provide model input when using a local model in ML Inference Processor"));
+        }
+    }
 }