minor changes based on comments

Signed-off-by: zhichao-aws <[email protected]>

CHANGELOG.md

@@ -5,7 +5,6 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 
 ## [Unreleased 3.0](https://github.com/opensearch-project/neural-search/compare/2.x...HEAD)
 ### Features
-Support sparse semantic retrieval by introducing `sparse_encoding` ingest processor and query builder ([#333](https://github.com/opensearch-project/neural-search/pull/333))
 ### Enhancements
 ### Bug Fixes
 ### Infrastructure

src/main/java/org/opensearch/neuralsearch/processor/SparseEncodingProcessor.java

@@ -22,7 +22,7 @@
  * and field_map can be used to indicate which fields needs text embedding and the corresponding keys for the sparse encoding results.
  */
 @Log4j2
-public class SparseEncodingProcessor extends NLPProcessor {
+public final class SparseEncodingProcessor extends NLPProcessor {
 
     public static final String TYPE = "sparse_encoding";
     public static final String LIST_TYPE_NESTED_MAP_KEY = "sparse_encoding";

src/main/java/org/opensearch/neuralsearch/processor/TextEmbeddingProcessor.java

@@ -21,7 +21,7 @@
  * and field_map can be used to indicate which fields needs text embedding and the corresponding keys for the text embedding results.
  */
 @Log4j2
-public class TextEmbeddingProcessor extends NLPProcessor {
+public final class TextEmbeddingProcessor extends NLPProcessor {
 
     public static final String TYPE = "text_embedding";
     public static final String LIST_TYPE_NESTED_MAP_KEY = "knn";

src/main/java/org/opensearch/neuralsearch/processor/factory/SparseEncodingProcessorFactory.java

@@ -18,6 +18,9 @@
 import org.opensearch.neuralsearch.ml.MLCommonsClientAccessor;
 import org.opensearch.neuralsearch.processor.SparseEncodingProcessor;
 
+/**
+ * Factory for sparse encoding ingest processor for ingestion pipeline. Instantiates processor based on user provided input.
+ */
 @Log4j2
 public class SparseEncodingProcessorFactory implements Processor.Factory {
     private final MLCommonsClientAccessor clientAccessor;

src/main/java/org/opensearch/neuralsearch/processor/factory/TextEmbeddingProcessorFactory.java

@@ -16,6 +16,9 @@
 import org.opensearch.neuralsearch.ml.MLCommonsClientAccessor;
 import org.opensearch.neuralsearch.processor.TextEmbeddingProcessor;
 
+/**
+ * Factory for text embedding ingest processor for ingestion pipeline. Instantiates processor based on user provided input.
+ */
 public class TextEmbeddingProcessorFactory implements Processor.Factory {
 
     private final MLCommonsClientAccessor clientAccessor;

src/main/java/org/opensearch/neuralsearch/query/SparseEncodingQueryBuilder.java

@@ -126,22 +126,24 @@ public static SparseEncodingQueryBuilder fromXContent(XContentParser parser) thr
         if (parser.nextToken() != XContentParser.Token.END_OBJECT) {
             throw new ParsingException(
                 parser.getTokenLocation(),
-                "["
-                    + NAME
-                    + "] query doesn't support multiple fields, found ["
-                    + sparseEncodingQueryBuilder.fieldName()
-                    + "] and ["
-                    + parser.currentName()
-                    + "]"
+                String.format(
+                    "[%s] query doesn't support multiple fields, found [%s] and [%s]",
+                    NAME,
+                    sparseEncodingQueryBuilder.fieldName(),
+                    parser.currentName()
+                )
             );
         }
 
         requireValue(sparseEncodingQueryBuilder.fieldName(), "Field name must be provided for " + NAME + " query");
         requireValue(
             sparseEncodingQueryBuilder.queryText(),
-            QUERY_TEXT_FIELD.getPreferredName() + " must be provided for " + NAME + " query"
+            String.format("%s field must be provided for [%s] query", QUERY_TEXT_FIELD.getPreferredName(), NAME)
+        );
+        requireValue(
+            sparseEncodingQueryBuilder.modelId(),
+            String.format("%s field must be provided for [%s] query", MODEL_ID_FIELD.getPreferredName(), NAME)
         );
-        requireValue(sparseEncodingQueryBuilder.modelId(), MODEL_ID_FIELD.getPreferredName() + " must be provided for " + NAME + " query");
 
         return sparseEncodingQueryBuilder;
     }
@@ -164,13 +166,13 @@ private static void parseQueryParams(XContentParser parser, SparseEncodingQueryB
                 } else {
                     throw new ParsingException(
                         parser.getTokenLocation(),
-                        "[" + NAME + "] query does not support [" + currentFieldName + "]"
+                        String.format("[%s] query does not support [%s] field", NAME, currentFieldName)
                     );
                 }
             } else {
                 throw new ParsingException(
                     parser.getTokenLocation(),
-                    "[" + NAME + "] unknown token [" + token + "] after [" + currentFieldName + "]"
+                    String.format("[%s] unknown token [%s] after [%s]", NAME, token, currentFieldName)
                 );
             }
         }
@@ -220,7 +222,7 @@ protected Query doToQuery(QueryShardContext context) throws IOException {
     private static void validateForRewrite(String queryText, String modelId) {
         if (StringUtils.isBlank(queryText) || StringUtils.isBlank(modelId)) {
             throw new IllegalArgumentException(
-                QUERY_TEXT_FIELD.getPreferredName() + " and " + MODEL_ID_FIELD.getPreferredName() + " cannot be null."
+                String.format("%s and %s cannot be null", QUERY_TEXT_FIELD.getPreferredName(), MODEL_ID_FIELD.getPreferredName())
             );
         }
     }
@@ -238,7 +240,7 @@ private static void validateQueryTokens(Map<String, Float> queryTokens) {
         for (Map.Entry<String, Float> entry : queryTokens.entrySet()) {
             if (entry.getValue() <= 0) {
                 throw new IllegalArgumentException(
-                    "Feature weight must be larger than 0, got: " + entry.getValue() + "for key " + entry.getKey()
+                    "Feature weight must be larger than 0, feature [" + entry.getValue() + "] has negative weight."
                 );
             }
         }

src/main/java/org/opensearch/neuralsearch/util/TokenWeightUtil.java

@@ -46,6 +46,9 @@ public class TokenWeightUtil {
      * @param mapResultList {@link Map} which is the response from {@link org.opensearch.neuralsearch.ml.MLCommonsClientAccessor}
      */
     public static List<Map<String, Float>> fetchListOfTokenWeightMap(List<Map<String, ?>> mapResultList) {
+        if (null == mapResultList || mapResultList.isEmpty()) {
+            throw new IllegalArgumentException("The inference result can not be null or empty.");
+        }
         List<Object> results = new ArrayList<>();
         for (Map<String, ?> map : mapResultList) {
             if (!map.containsKey(RESPONSE_KEY)) {
@@ -66,7 +69,7 @@ private static Map<String, Float> buildTokenWeightMap(Object uncastedMap) {
         Map<String, Float> result = new HashMap<>();
         for (Map.Entry<?, ?> entry : ((Map<?, ?>) uncastedMap).entrySet()) {
             if (!String.class.isAssignableFrom(entry.getKey().getClass()) || !Number.class.isAssignableFrom(entry.getValue().getClass())) {
-                throw new IllegalArgumentException("The expected inference result is a Map with String keys and  " + " Float values.");
+                throw new IllegalArgumentException("The expected inference result is a Map with String keys and Float values.");
             }
             result.put((String) entry.getKey(), ((Number) entry.getValue()).floatValue());
         }