[Backport 2.x] Add support for radial search on Neural query (#1245)

* Add support for radial search on Neural query (#1235) * Add support for radial search on k-NN and Neural query types Signed-off-by: Thomas Farr <[email protected]> * spotless Signed-off-by: Thomas Farr <[email protected]> * Fix compile errors Signed-off-by: Thomas Farr <[email protected]> * Fix test Signed-off-by: Thomas Farr <[email protected]> --------- Signed-off-by: Thomas Farr <[email protected]> (cherry picked from commit a3a3e54) Signed-off-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> * Fix compile error Signed-off-by: Thomas Farr <[email protected]> --------- Signed-off-by: Thomas Farr <[email protected]> Signed-off-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Thomas Farr <[email protected]>
opensearch-project · Oct 22, 2024 · 869aa24 · 869aa24
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commit 869aa24
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diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -4,6 +4,7 @@ Inspired from [Keep a Changelog](https://keepachangelog.com/en/1.0.0/)
 ## [Unreleased 2.x]
 ### Added
 - Added `minScore` and `maxDistance` to `KnnQuery` ([#1166](https://github.com/opensearch-project/opensearch-java/pull/1166))
+- Added `minScore` and `maxDistance` to `NeuralQuery` ([#1235](https://github.com/opensearch-project/opensearch-java/pull/1235))
 
 ### Dependencies
 - Bumps `org.ajoberstar.grgit:grgit-gradle` from 5.2.2 to 5.3.0

diff --git a/java-client/src/main/java/org/opensearch/client/opensearch/_types/query_dsl/KnnQuery.java b/java-client/src/main/java/org/opensearch/client/opensearch/_types/query_dsl/KnnQuery.java
@@ -76,6 +76,7 @@ public final float[] vector() {
      * Optional - The number of neighbors the search of each graph will return.
      * @return The number of neighbors to return.
      */
+    @Nullable
     public final Integer k() {
         return this.k;
     }
@@ -84,6 +85,7 @@ public final Integer k() {
      * Optional - The minimum score allowed for the returned search results.
      * @return The minimum score allowed for the returned search results.
      */
+    @Nullable
     private final Float minScore() {
         return this.minScore;
     }
@@ -92,6 +94,7 @@ private final Float minScore() {
      * Optional - The maximum distance allowed between the vector and each of the returned search results.
      * @return The maximum distance allowed between the vector and each ofthe returned search results.
      */
+    @Nullable
     private final Float maxDistance() {
         return this.maxDistance;
     }
@@ -111,8 +114,6 @@ protected void serializeInternal(JsonGenerator generator, JsonpMapper mapper) {
 
         super.serializeInternal(generator, mapper);
 
-        // TODO: Implement the rest of the serialization.
-
         generator.writeKey("vector");
         generator.writeStartArray();
         for (float value : this.vector) {
@@ -183,7 +184,7 @@ public Builder vector(@Nullable float[] vector) {
         }
 
         /**
-         * Required - The number of neighbors the search of each graph will return.
+         * Optional - The number of neighbors to return.
          *
          * @param k The number of neighbors to return.
          * @return This builder.

diff --git a/java-client/src/main/java/org/opensearch/client/opensearch/_types/query_dsl/NeuralQuery.java b/java-client/src/main/java/org/opensearch/client/opensearch/_types/query_dsl/NeuralQuery.java
@@ -26,7 +26,12 @@ public class NeuralQuery extends QueryBase implements QueryVariant {
     private final String field;
     private final String queryText;
     private final String queryImage;
-    private final int k;
+    @Nullable
+    private final Integer k;
+    @Nullable
+    private final Float minScore;
+    @Nullable
+    private final Float maxDistance;
     @Nullable
     private final String modelId;
     @Nullable
@@ -41,7 +46,9 @@ private NeuralQuery(NeuralQuery.Builder builder) {
         }
         this.queryText = builder.queryText;
         this.queryImage = builder.queryImage;
-        this.k = ApiTypeHelper.requireNonNull(builder.k, this, "k");
+        this.k = builder.k;
+        this.minScore = builder.minScore;
+        this.maxDistance = builder.maxDistance;
         this.modelId = builder.modelId;
         this.filter = builder.filter;
     }
@@ -90,17 +97,34 @@ public final String queryImage() {
     }
 
     /**
-     * Required - The number of neighbors to return.
+     * Optional - The number of neighbors to return.
      *
      * @return The number of neighbors to return.
      */
-    public final int k() {
+    @Nullable
+    public final Integer k() {
         return this.k;
     }
 
     /**
-     * Builder for {@link NeuralQuery}.
+     * Optional - The minimum score threshold for the search results
+     *
+     * @return The minimum score threshold for the search results
+     */
+    @Nullable
+    public final Float minScore() {
+        return this.minScore;
+    }
+
+    /**
+     * Optional - The maximum distance threshold for the search results
+     *
+     * @return The maximum distance threshold for the search results
      */
+    @Nullable
+    public final Float maxDistance() {
+        return this.maxDistance;
+    }
 
     /**
      * Optional - The model_id field if the default model for the index or field is set.
@@ -141,7 +165,17 @@ protected void serializeInternal(JsonGenerator generator, JsonpMapper mapper) {
             generator.write("model_id", this.modelId);
         }
 
-        generator.write("k", this.k);
+        if (this.k != null) {
+            generator.write("k", this.k);
+        }
+
+        if (this.minScore != null) {
+            generator.write("min_score", this.minScore);
+        }
+
+        if (this.maxDistance != null) {
+            generator.write("max_distance", this.maxDistance);
+        }
 
         if (this.filter != null) {
             generator.writeKey("filter");
@@ -152,7 +186,14 @@ protected void serializeInternal(JsonGenerator generator, JsonpMapper mapper) {
     }
 
     public Builder toBuilder() {
-        return toBuilder(new Builder()).field(field).queryText(queryText).queryImage(queryImage).k(k).modelId(modelId).filter(filter);
+        return toBuilder(new Builder()).field(field)
+            .queryText(queryText)
+            .queryImage(queryImage)
+            .k(k)
+            .minScore(minScore)
+            .maxDistance(maxDistance)
+            .modelId(modelId)
+            .filter(filter);
     }
 
     /**
@@ -162,8 +203,13 @@ public static class Builder extends QueryBase.AbstractBuilder<NeuralQuery.Builde
         private String field;
         private String queryText;
         private String queryImage;
+        @Nullable
         private Integer k;
         @Nullable
+        private Float minScore;
+        @Nullable
+        private Float maxDistance;
+        @Nullable
         private String modelId;
         @Nullable
         private Query filter;
@@ -216,7 +262,7 @@ public NeuralQuery.Builder modelId(@Nullable String modelId) {
         }
 
         /**
-         * Required - The number of neighbors to return.
+         * Optional - The number of neighbors to return.
          *
          * @param k The number of neighbors to return.
          * @return This builder.
@@ -226,6 +272,28 @@ public NeuralQuery.Builder k(@Nullable Integer k) {
             return this;
         }
 
+        /**
+         * Optional - The minimum score threshold for the search results
+         *
+         * @param minScore The minimum score threshold for the search results
+         * @return This builder.
+         */
+        public NeuralQuery.Builder minScore(@Nullable Float minScore) {
+            this.minScore = minScore;
+            return this;
+        }
+
+        /**
+         * Optional - The maximum distance threshold for the search results
+         *
+         * @param maxDistance The maximum distance threshold for the search results
+         * @return This builder.
+         */
+        public NeuralQuery.Builder maxDistance(@Nullable Float maxDistance) {
+            this.maxDistance = maxDistance;
+            return this;
+        }
+
         /**
          * Optional - A query to filter the results of the knn query.
          *
@@ -267,6 +335,8 @@ protected static void setupNeuralQueryDeserializer(ObjectDeserializer<NeuralQuer
         op.add(NeuralQuery.Builder::queryImage, JsonpDeserializer.stringDeserializer(), "query_image");
         op.add(NeuralQuery.Builder::modelId, JsonpDeserializer.stringDeserializer(), "model_id");
         op.add(NeuralQuery.Builder::k, JsonpDeserializer.integerDeserializer(), "k");
+        op.add(NeuralQuery.Builder::minScore, JsonpDeserializer.floatDeserializer(), "min_score");
+        op.add(NeuralQuery.Builder::maxDistance, JsonpDeserializer.floatDeserializer(), "max_distance");
         op.add(NeuralQuery.Builder::filter, Query._DESERIALIZER, "filter");
 
         op.setKey(NeuralQuery.Builder::field, JsonpDeserializer.stringDeserializer());

diff --git a/java-client/src/test/java/org/opensearch/client/opensearch/model/VariantsTest.java b/java-client/src/test/java/org/opensearch/client/opensearch/model/VariantsTest.java
@@ -221,7 +221,7 @@ public void testNeuralQuery() {
         assertEquals("passage_embedding", searchRequest.query().neural().field());
         assertEquals("Hi world", searchRequest.query().neural().queryText());
         assertEquals("bQ1J8ooBpBj3wT4HVUsb", searchRequest.query().neural().modelId());
-        assertEquals(100, searchRequest.query().neural().k());
+        assertEquals((Integer) 100, searchRequest.query().neural().k());
     }
 
     @Test
@@ -251,7 +251,7 @@ public void testNeuralQueryFromJson() {
             searchRequest.query().neural().queryImage()
         );
         assertEquals("bQ1J8ooBpBj3wT4HVUsb", searchRequest.query().neural().modelId());
-        assertEquals(100, searchRequest.query().neural().k());
+        assertEquals((Integer) 100, searchRequest.query().neural().k());
     }
 
     @Test
@@ -279,10 +279,10 @@ public void testHybridQuery() {
         assertEquals("passage_embedding", searchRequest.query().hybrid().queries().get(1).neural().field());
         assertEquals("Hi world", searchRequest.query().hybrid().queries().get(1).neural().queryText());
         assertEquals("bQ1J8ooBpBj3wT4HVUsb", searchRequest.query().hybrid().queries().get(1).neural().modelId());
-        assertEquals(100, searchRequest.query().hybrid().queries().get(1).neural().k());
+        assertEquals((Integer) 100, searchRequest.query().hybrid().queries().get(1).neural().k());
         assertEquals("passage_embedding", searchRequest.query().hybrid().queries().get(2).knn().field());
         assertEquals(2, searchRequest.query().hybrid().queries().get(2).knn().vector().length);
-        assertEquals(Integer.valueOf(2), searchRequest.query().hybrid().queries().get(2).knn().k());
+        assertEquals((Integer) 2, searchRequest.query().hybrid().queries().get(2).knn().k());
     }
 
     @Test
@@ -301,9 +301,9 @@ public void testHybridQueryFromJson() {
         assertEquals("passage_embedding", searchRequest.query().hybrid().queries().get(1).neural().field());
         assertEquals("Hi world", searchRequest.query().hybrid().queries().get(1).neural().queryText());
         assertEquals("bQ1J8ooBpBj3wT4HVUsb", searchRequest.query().hybrid().queries().get(1).neural().modelId());
-        assertEquals(100, searchRequest.query().hybrid().queries().get(1).neural().k());
+        assertEquals((Integer) 100, searchRequest.query().hybrid().queries().get(1).neural().k());
         assertEquals("passage_embedding", searchRequest.query().hybrid().queries().get(2).knn().field());
         assertEquals(2, searchRequest.query().hybrid().queries().get(2).knn().vector().length);
-        assertEquals(Integer.valueOf(2), searchRequest.query().hybrid().queries().get(2).knn().k());
+        assertEquals((Integer) 2, searchRequest.query().hybrid().queries().get(2).knn().k());
     }
 }
diff --git a/...st/java11/org/opensearch/client/opensearch/integTest/AbstractSearchTemplateRequestIT.java b/...st/java11/org/opensearch/client/opensearch/integTest/AbstractSearchTemplateRequestIT.java
@@ -12,6 +12,7 @@
 import java.util.List;
 import java.util.Map;
 import org.junit.Test;
+import org.opensearch.Version;
 import org.opensearch.client.json.JsonData;
 import org.opensearch.client.opensearch._types.Refresh;
 import org.opensearch.client.opensearch._types.mapping.Property;
@@ -89,6 +90,14 @@ public void testTemplateSearchAggregations() throws Exception {
 
     @Test
     public void testMultiSearchTemplate() throws Exception {
+        Integer expectedSuccessStatus = null;
+        Integer expectedFailureStatus = null;
+
+        if (getServerVersion().onOrAfter(Version.fromString("2.18.0"))) {
+            expectedSuccessStatus = 200;
+            expectedFailureStatus = 404;
+        }
+
         var index = "test-msearch-template";
         createDocuments(index);
 
@@ -120,11 +129,11 @@ public void testMultiSearchTemplate() throws Exception {
         assertEquals(2, searchResponse.responses().size());
         var response = searchResponse.responses().get(0);
         assertTrue(response.isResult());
-        assertNull(response.result().status());
+        assertEquals(expectedSuccessStatus, response.result().status());
         assertEquals(4, response.result().hits().hits().size());
         var failureResponse = searchResponse.responses().get(1);
         assertTrue(failureResponse.isFailure());
-        assertNull(failureResponse.failure().status());
+        assertEquals(expectedFailureStatus, failureResponse.failure().status());
     }
 
     private SearchTemplateResponse<SimpleDoc> sendTemplateRequest(String index, String title, boolean suggs, boolean aggs)