Upgrade Milvus java sdk to 2.5.4

  - Upgrade Milvus java sdk to 2.5.4
  - Remove use of fastjson
    - Use com.google.gson.JsonObject as Milvus SDK replaces fastjson with gson
  - Change SearchResult RowRecord similarity metric name to score
     - Milvus SDK 2.5.4 uses "score" instead of "distance"

Signed-off-by: Ilayaperumal Gopinathan <[email protected]>

pom.xml

@@ -215,10 +215,10 @@
 		<pgvector.version>0.1.6</pgvector.version>
 		<sap.hanadb.version>2.20.11</sap.hanadb.version>
 		<coherence.version>24.09</coherence.version>
-		<milvus.version>2.3.5</milvus.version>
+		<milvus.version>2.5.4</milvus.version>
 		<gemfire.testcontainers.version>2.3.0</gemfire.testcontainers.version>
 		<pinecone.version>0.8.0</pinecone.version>
-		<fastjson.version>2.0.46</fastjson.version>
+		<fastjson2.version>2.0.46</fastjson2.version>
 		<azure-core.version>1.53.0</azure-core.version>
 		<azure-json.version>1.3.0</azure-json.version>
 		<azure-identity.version>1.14.0</azure-identity.version>

spring-ai-test/src/main/java/org/springframework/ai/test/vectorstore/BaseVectorStoreTests.java

@@ -110,7 +110,8 @@ protected void deleteById() {
 			assertThat(results.get(0).getId()).isEqualTo(documents.get(2).getId());
 			Map<String, Object> metadata = results.get(0).getMetadata();
 			assertThat(normalizeValue(metadata.get("country"))).isEqualTo("BG");
-			assertThat(normalizeValue(metadata.get("year"))).isEqualTo("2023");
+			// the values are converted into Double
+			assertThat(normalizeValue(metadata.get("year"))).isEqualTo("2023.0");
 
 			vectorStore.delete(List.of(documents.get(2).getId()));
 		});

vector-stores/spring-ai-azure-store/pom.xml

@@ -80,7 +80,7 @@
 		<dependency>
 			<groupId>com.alibaba.fastjson2</groupId>
 			<artifactId>fastjson2</artifactId>
-			<version>${fastjson.version}</version>
+			<version>${fastjson2.version}</version>
 		</dependency>
 
 		<!-- TESTING -->

vector-stores/spring-ai-milvus-store/src/main/java/org/springframework/ai/vectorstore/milvus/MilvusVectorStore.java

@@ -16,13 +16,16 @@
 
 package org.springframework.ai.vectorstore.milvus;
 
+import java.lang.reflect.Type;
 import java.util.ArrayList;
 import java.util.List;
 import java.util.Map;
 import java.util.Optional;
 import java.util.stream.Collectors;
 
-import com.alibaba.fastjson.JSONObject;
+import com.google.gson.Gson;
+import com.google.gson.JsonObject;
+import com.google.gson.reflect.TypeToken;
 import io.milvus.client.MilvusServiceClient;
 import io.milvus.common.clientenum.ConsistencyLevelEnum;
 import io.milvus.exception.ParamException;
@@ -159,7 +162,7 @@ public class MilvusVectorStore extends AbstractObservationVectorStore implements
 	public static final String EMBEDDING_FIELD_NAME = "embedding";
 
 	// Metadata, automatically assigned by Milvus.
-	private static final String DISTANCE_FIELD_NAME = "distance";
+	public static final String SIMILARITY_FIELD_NAME = "score";
 
 	private static final Logger logger = LoggerFactory.getLogger(MilvusVectorStore.class);
 
@@ -234,7 +237,7 @@ public void doAdd(List<Document> documents) {
 
 		List<String> docIdArray = new ArrayList<>();
 		List<String> contentArray = new ArrayList<>();
-		List<JSONObject> metadataArray = new ArrayList<>();
+		List<JsonObject> metadataArray = new ArrayList<>();
 		List<List<Float>> embeddingArray = new ArrayList<>();
 
 		// TODO: Need to customize how we pass the embedding options
@@ -246,7 +249,9 @@ public void doAdd(List<Document> documents) {
 			// Use a (future) DocumentTextLayoutFormatter instance to extract
 			// the content used to compute the embeddings
 			contentArray.add(document.getText());
-			metadataArray.add(new JSONObject(document.getMetadata()));
+			Gson gson = new Gson();
+			String jsonString = gson.toJson(document.getMetadata());
+			metadataArray.add(gson.fromJson(jsonString, JsonObject.class));
 			embeddingArray.add(EmbeddingUtils.toList(embeddings.get(documents.indexOf(document))));
 		}
 
@@ -357,29 +362,32 @@ public List<Document> doSimilaritySearch(SearchRequest request) {
 			.map(rowRecord -> {
 				String docId = String.valueOf(rowRecord.get(this.idFieldName));
 				String content = (String) rowRecord.get(this.contentFieldName);
-				JSONObject metadata = null;
+				JsonObject metadata = new JsonObject();
 				try {
-					metadata = (JSONObject) rowRecord.get(this.metadataFieldName);
+					metadata = (JsonObject) rowRecord.get(this.metadataFieldName);
 					// inject the distance into the metadata.
-					metadata.put(DocumentMetadata.DISTANCE.value(), 1 - getResultSimilarity(rowRecord));
+					metadata.addProperty(DocumentMetadata.DISTANCE.value(), 1 - getResultSimilarity(rowRecord));
 				}
 				catch (ParamException e) {
 					// skip the ParamException if metadata doesn't exist for the custom
 					// collection
 				}
+				Gson gson = new Gson();
+				Type type = new TypeToken<Map<String, Object>>() {
+				}.getType();
 				return Document.builder()
 					.id(docId)
 					.text(content)
-					.metadata((metadata != null) ? metadata.getInnerMap() : Map.of())
+					.metadata((metadata != null) ? gson.fromJson(metadata, type) : Map.of())
 					.score((double) getResultSimilarity(rowRecord))
 					.build();
 			})
 			.toList();
 	}
 
 	private float getResultSimilarity(RowRecord rowRecord) {
-		Float distance = (Float) rowRecord.get(DISTANCE_FIELD_NAME);
-		return (this.metricType == MetricType.IP || this.metricType == MetricType.COSINE) ? distance : (1 - distance);
+		Float score = (Float) rowRecord.get(SIMILARITY_FIELD_NAME);
+		return (this.metricType == MetricType.IP || this.metricType == MetricType.COSINE) ? score : (1 - score);
 	}
 
 	// ---------------------------------------------------------------------------------

vector-stores/spring-ai-milvus-store/src/test/java/org/springframework/ai/vectorstore/milvus/MilvusImage.java

@@ -23,7 +23,7 @@
  */
 public final class MilvusImage {
 
-	public static final DockerImageName DEFAULT_IMAGE = DockerImageName.parse("milvusdb/milvus:v2.4.9");
+	public static final DockerImageName DEFAULT_IMAGE = DockerImageName.parse("milvusdb/milvus:v2.5.4");
 
 	private MilvusImage() {
 

vector-stores/spring-ai-milvus-store/src/test/java/org/springframework/ai/vectorstore/milvus/MilvusVectorStoreCustomFieldNamesIT.java

@@ -103,16 +103,14 @@ void searchWithCustomFieldNames(String metricType) {
 				List<Document> fullResult = vectorStore
 					.similaritySearch(SearchRequest.builder().query("Spring").build());
 
-				List<Float> distances = fullResult.stream()
-					.map(doc -> (Float) doc.getMetadata().get("distance"))
-					.toList();
+				List<Double> scores = fullResult.stream().map(doc -> doc.getScore()).toList();
 
-				assertThat(distances).hasSize(3);
+				assertThat(scores).hasSize(3);
 
-				float threshold = (distances.get(0) + distances.get(1)) / 2;
+				double threshold = (scores.get(0) + scores.get(1)) / 2;
 
 				List<Document> results = vectorStore.similaritySearch(
-						SearchRequest.builder().query("Spring").topK(5).similarityThreshold(1 - threshold).build());
+						SearchRequest.builder().query("Spring").topK(5).similarityThreshold(threshold).build());
 
 				assertThat(results).hasSize(1);
 				Document resultDoc = results.get(0);
@@ -144,16 +142,14 @@ void searchWithoutMetadataFieldOverride(String metricType) {
 				List<Document> fullResult = vectorStore
 					.similaritySearch(SearchRequest.builder().query("Spring").build());
 
-				List<Float> distances = fullResult.stream()
-					.map(doc -> (Float) doc.getMetadata().get("distance"))
-					.toList();
+				List<Double> scores = fullResult.stream().map(doc -> doc.getScore()).toList();
 
-				assertThat(distances).hasSize(3);
+				assertThat(scores).hasSize(3);
 
-				float threshold = (distances.get(0) + distances.get(1)) / 2;
+				double threshold = (scores.get(0) + scores.get(1)) / 2;
 
 				List<Document> results = vectorStore.similaritySearch(
-						SearchRequest.builder().query("Spring").topK(5).similarityThreshold(1 - threshold).build());
+						SearchRequest.builder().query("Spring").topK(5).similarityThreshold(threshold).build());
 
 				assertThat(results).hasSize(1);
 				Document resultDoc = results.get(0);
@@ -187,16 +183,14 @@ void searchWithAutoIdEnabled(String metricType) {
 				List<Document> fullResult = vectorStore
 					.similaritySearch(SearchRequest.builder().query("Spring").build());
 
-				List<Float> distances = fullResult.stream()
-					.map(doc -> (Float) doc.getMetadata().get("distance"))
-					.toList();
+				List<Double> scores = fullResult.stream().map(doc -> doc.getScore()).toList();
 
-				assertThat(distances).hasSize(3);
+				assertThat(scores).hasSize(3);
 
-				float threshold = (distances.get(0) + distances.get(1)) / 2;
+				double threshold = (scores.get(0) + scores.get(1)) / 2;
 
 				List<Document> results = vectorStore.similaritySearch(
-						SearchRequest.builder().query("Spring").topK(5).similarityThreshold(1 - threshold).build());
+						SearchRequest.builder().query("Spring").topK(5).similarityThreshold(threshold).build());
 
 				assertThat(results).hasSize(1);
 				Document resultDoc = results.get(0);

vector-stores/spring-ai-milvus-store/src/test/java/org/springframework/ai/vectorstore/milvus/MilvusVectorStoreIT.java

@@ -319,7 +319,7 @@ public void deleteWithComplexFilterExpression() {
 			assertThat(results.stream().map(doc -> doc.getMetadata().get("type")).collect(Collectors.toList()))
 				.containsExactlyInAnyOrder("A", "B");
 			assertThat(results.stream().map(doc -> doc.getMetadata().get("priority")).collect(Collectors.toList()))
-				.containsExactlyInAnyOrder(1, 1);
+				.containsExactlyInAnyOrder(1.0, 1.0);
 		});
 	}