(improvement)(chat) Fix the error in Milvus query and add the option to create EmbeddingStore based on caching mode (#1310)

common/src/main/java/com/tencent/supersonic/common/service/impl/EmbeddingServiceImpl.java

@@ -4,7 +4,6 @@ import com.tencent.supersonic.common.service.EmbeddingService;
 import dev.langchain4j.data.embedding.Embedding;
 import dev.langchain4j.data.segment.TextSegment;
 import dev.langchain4j.model.embedding.EmbeddingModel;
-import dev.langchain4j.model.output.Response;
 import dev.langchain4j.store.embedding.EmbeddingMatch;
 import dev.langchain4j.store.embedding.EmbeddingSearchRequest;
 import dev.langchain4j.store.embedding.EmbeddingSearchResult;
@@ -16,9 +15,9 @@ import dev.langchain4j.store.embedding.RetrieveQueryResult;
 import dev.langchain4j.store.embedding.TextSegmentConvert;
 import dev.langchain4j.store.embedding.filter.Filter;
 import dev.langchain4j.store.embedding.filter.comparison.IsEqualTo;
-import lombok.RequiredArgsConstructor;
 import lombok.extern.slf4j.Slf4j;
 import org.apache.commons.collections.MapUtils;
+import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.stereotype.Service;
 
 import java.util.ArrayList;
@@ -26,27 +25,31 @@ import java.util.Comparator;
 import java.util.HashMap;
 import java.util.List;
 import java.util.Map;
-import java.util.concurrent.ConcurrentHashMap;
+import java.util.Objects;
 import java.util.stream.Collectors;
 
 @Service
 @Slf4j
-@RequiredArgsConstructor
 public class EmbeddingServiceImpl implements EmbeddingService {
-    private static final Map<String, EmbeddingStore<TextSegment>> embeddingStoreMap = new ConcurrentHashMap<>();
+
-    private final EmbeddingStoreFactory embeddingStoreFactory;
+    @Autowired
-    private final EmbeddingModel embeddingModel;
+    private EmbeddingStoreFactory embeddingStoreFactory;
+
+    @Autowired
+    private EmbeddingModel embeddingModel;
 
     @Override
     public void addQuery(String collectionName, List<TextSegment> queries) {
-        EmbeddingStore<TextSegment> embeddingStore = embeddingStoreMap
+        EmbeddingStore embeddingStore = embeddingStoreFactory.create(collectionName);
-                .computeIfAbsent(collectionName, embeddingStoreFactory::create);
+        for (TextSegment query : queries) {
-        try {
+            String question = query.text();
-            Response<List<Embedding>> embedAll = embeddingModel.embedAll(queries);
+            try {
-            embeddingStore.addAll(embedAll.content(), queries);
+                Embedding embedding = embeddingModel.embed(question).content();
-        } catch (Exception e) {
+                embeddingStore.add(embedding, query);
-            log.error("embeddingModel embed error queries: {}, embeddingStore: {}", queries,
+            } catch (Exception e) {
-                    embeddingStore.getClass().getSimpleName(), e);
+                log.error("embeddingModel embed error question: {}, embeddingStore: {}", question,
+                        embeddingStore.getClass().getSimpleName(), e);
+            }
         }
     }
 
@@ -58,8 +61,7 @@ public class EmbeddingServiceImpl implements EmbeddingService {
     public List<RetrieveQueryResult> retrieveQuery(String collectionName, RetrieveQuery retrieveQuery, int num) {
         List<RetrieveQueryResult> results = new ArrayList<>();
 
-        EmbeddingStore<TextSegment> embeddingStore = embeddingStoreMap
+        EmbeddingStore embeddingStore = embeddingStoreFactory.create(collectionName);
-                .computeIfAbsent(collectionName, embeddingStoreFactory::create);
         List<String> queryTextsList = retrieveQuery.getQueryTextsList();
         Map<String, String> filterCondition = retrieveQuery.getFilterCondition();
         for (String queryText : queryTextsList) {
@@ -68,7 +70,7 @@ public class EmbeddingServiceImpl implements EmbeddingService {
             EmbeddingSearchRequest request = EmbeddingSearchRequest.builder()
                     .queryEmbedding(embeddedText).filter(filter).maxResults(num).build();
 
-            EmbeddingSearchResult<TextSegment> result = embeddingStore.search(request);
+            EmbeddingSearchResult result = embeddingStore.search(request);
             List<EmbeddingMatch<TextSegment>> relevant = result.matches();
 
             RetrieveQueryResult retrieveQueryResult = new RetrieveQueryResult();
@@ -81,7 +83,8 @@ public class EmbeddingServiceImpl implements EmbeddingService {
                 retrieval.setId(TextSegmentConvert.getQueryId(embedded));
                 retrieval.setQuery(embedded.text());
                 Map<String, Object> metadata = new HashMap<>();
-                if (MapUtils.isNotEmpty(embedded.metadata().toMap())) {
+                if (Objects.nonNull(embedded)
+                        && MapUtils.isNotEmpty(embedded.metadata().toMap())) {
                     metadata.putAll(embedded.metadata().toMap());
                 }
                 retrieval.setMetadata(metadata);

common/src/main/java/dev/langchain4j/chroma/spring/ChromaEmbeddingStoreFactory.java

@@ -1,15 +1,12 @@
 package dev.langchain4j.chroma.spring;
 
-import dev.langchain4j.inmemory.spring.InMemoryEmbeddingStoreFactory;
+import dev.langchain4j.store.embedding.BaseEmbeddingStoreFactory;
 import dev.langchain4j.store.embedding.EmbeddingStore;
-import dev.langchain4j.store.embedding.EmbeddingStoreFactory;
 import dev.langchain4j.store.embedding.chroma.ChromaEmbeddingStore;
 import lombok.extern.slf4j.Slf4j;
 
-import java.util.Objects;
-
 @Slf4j
-public class ChromaEmbeddingStoreFactory implements EmbeddingStoreFactory {
+public class ChromaEmbeddingStoreFactory extends BaseEmbeddingStoreFactory {
 
     private Properties properties;
 
@@ -18,31 +15,12 @@ public class ChromaEmbeddingStoreFactory implements EmbeddingStoreFactory {
     }
 
     @Override
-    public EmbeddingStore create(String collectionName) {
+    public EmbeddingStore createEmbeddingStore(String collectionName) {
         EmbeddingStoreProperties storeProperties = properties.getEmbeddingStore();
-        EmbeddingStore embeddingStore = null;
+        return ChromaEmbeddingStore.builder()
-        try {
+                .baseUrl(storeProperties.getBaseUrl())
-            embeddingStore = ChromaEmbeddingStore.builder()
+                .collectionName(collectionName)
-                    .baseUrl(storeProperties.getBaseUrl())
+                .timeout(storeProperties.getTimeout())
-                    .collectionName(collectionName)
+                .build();
-                    .timeout(storeProperties.getTimeout())
-                    .build();
-        } catch (Exception e) {
-            log.debug("Failed to create ChromaEmbeddingStore,collectionName:{}"
-                            + ", fallback to the default InMemoryEmbeddingStore method。",
-                    collectionName, e.getMessage());
-        }
-        if (Objects.isNull(embeddingStore)) {
-            embeddingStore = createInMemoryEmbeddingStore(collectionName);
-        }
-        return embeddingStore;
-    }
-
-    private EmbeddingStore createInMemoryEmbeddingStore(String collectionName) {
-        dev.langchain4j.inmemory.spring.Properties properties = new dev.langchain4j.inmemory.spring.Properties();
-        dev.langchain4j.inmemory.spring.EmbeddingStoreProperties embeddingStoreProperties =
-                new dev.langchain4j.inmemory.spring.EmbeddingStoreProperties();
-        properties.setEmbeddingStore(embeddingStoreProperties);
-        return new InMemoryEmbeddingStoreFactory(properties).create(collectionName);
     }
 }

common/src/main/java/dev/langchain4j/inmemory/spring/InMemoryEmbeddingStoreFactory.java

@@ -3,8 +3,8 @@ package dev.langchain4j.inmemory.spring;
 import com.tencent.supersonic.common.config.EmbeddingConfig;
 import com.tencent.supersonic.common.util.ContextUtils;
 import dev.langchain4j.data.segment.TextSegment;
+import dev.langchain4j.store.embedding.BaseEmbeddingStoreFactory;
 import dev.langchain4j.store.embedding.EmbeddingStore;
-import dev.langchain4j.store.embedding.EmbeddingStoreFactory;
 import dev.langchain4j.store.embedding.inmemory.InMemoryEmbeddingStore;
 import lombok.extern.slf4j.Slf4j;
 import org.apache.commons.collections4.MapUtils;
@@ -15,15 +15,12 @@ import java.nio.file.Path;
 import java.nio.file.Paths;
 import java.util.Map;
 import java.util.Objects;
-import java.util.concurrent.ConcurrentHashMap;
 import java.util.concurrent.CopyOnWriteArraySet;
 
 @Slf4j
-public class InMemoryEmbeddingStoreFactory implements EmbeddingStoreFactory {
+public class InMemoryEmbeddingStoreFactory extends BaseEmbeddingStoreFactory {
 
     public static final String PERSISTENT_FILE_PRE = "InMemory.";
-    private static Map<String, InMemoryEmbeddingStore<TextSegment>> collectionNameToStore =
-            new ConcurrentHashMap<>();
     private Properties properties;
 
 
@@ -32,18 +29,12 @@ public class InMemoryEmbeddingStoreFactory implements EmbeddingStoreFactory {
     }
 
     @Override
-    public synchronized EmbeddingStore create(String collectionName) {
+    public synchronized EmbeddingStore createEmbeddingStore(String collectionName) {
-        InMemoryEmbeddingStore<TextSegment> embeddingStore = collectionNameToStore.get(collectionName);
+        InMemoryEmbeddingStore<TextSegment> embeddingStore = reloadFromPersistFile(collectionName);
-        if (Objects.nonNull(embeddingStore)) {
-            return embeddingStore;
-        }
-        embeddingStore = reloadFromPersistFile(collectionName);
         if (Objects.isNull(embeddingStore)) {
             embeddingStore = new InMemoryEmbeddingStore();
         }
-        collectionNameToStore.putIfAbsent(collectionName, embeddingStore);
         return embeddingStore;
-
     }
 
     private InMemoryEmbeddingStore<TextSegment> reloadFromPersistFile(String collectionName) {
@@ -67,10 +58,10 @@ public class InMemoryEmbeddingStoreFactory implements EmbeddingStoreFactory {
     }
 
     public synchronized void persistFile() {
-        if (MapUtils.isEmpty(collectionNameToStore)) {
+        if (MapUtils.isEmpty(super.collectionNameToStore)) {
             return;
         }
-        for (Map.Entry<String, InMemoryEmbeddingStore<TextSegment>> entry : collectionNameToStore.entrySet()) {
+        for (Map.Entry<String, EmbeddingStore<TextSegment>> entry : collectionNameToStore.entrySet()) {
             Path filePath = getPersistPath(entry.getKey());
             if (Objects.isNull(filePath)) {
                 continue;
@@ -80,7 +71,11 @@ public class InMemoryEmbeddingStoreFactory implements EmbeddingStoreFactory {
                 if (!Files.exists(directoryPath)) {
                     Files.createDirectories(directoryPath);
                 }
-                entry.getValue().serializeToFile(filePath);
+                if (entry.getValue() instanceof InMemoryEmbeddingStore) {
+                    InMemoryEmbeddingStore<TextSegment> inMemoryEmbeddingStore =
+                            (InMemoryEmbeddingStore) entry.getValue();
+                    inMemoryEmbeddingStore.serializeToFile(filePath);
+                }
             } catch (Exception e) {
                 log.error("persistFile error, persistFile:" + filePath, e);
             }

common/src/main/java/dev/langchain4j/milvus/spring/EmbeddingStoreProperties.java

@@ -23,4 +23,5 @@ class EmbeddingStoreProperties {
     private ConsistencyLevelEnum consistencyLevel;
     private Boolean retrieveEmbeddingsOnSearch;
     private String databaseName;
+    private Boolean autoFlushOnInsert;
 }

common/src/main/java/dev/langchain4j/milvus/spring/MilvusEmbeddingStoreFactory.java

@@ -1,11 +1,11 @@
 package dev.langchain4j.milvus.spring;
 
 import dev.langchain4j.data.segment.TextSegment;
+import dev.langchain4j.store.embedding.BaseEmbeddingStoreFactory;
 import dev.langchain4j.store.embedding.EmbeddingStore;
-import dev.langchain4j.store.embedding.EmbeddingStoreFactory;
 import dev.langchain4j.store.embedding.milvus.MilvusEmbeddingStore;
 
-public class MilvusEmbeddingStoreFactory implements EmbeddingStoreFactory {
+public class MilvusEmbeddingStoreFactory extends BaseEmbeddingStoreFactory {
     private final Properties properties;
 
     public MilvusEmbeddingStoreFactory(Properties properties) {
@@ -13,22 +13,23 @@ public class MilvusEmbeddingStoreFactory implements EmbeddingStoreFactory {
     }
 
     @Override
-    public EmbeddingStore<TextSegment> create(String collectionName) {
+    public EmbeddingStore<TextSegment> createEmbeddingStore(String collectionName) {
-        EmbeddingStoreProperties embeddingStore = properties.getEmbeddingStore();
+        EmbeddingStoreProperties storeProperties = properties.getEmbeddingStore();
         return MilvusEmbeddingStore.builder()
-                .host(embeddingStore.getHost())
+                .host(storeProperties.getHost())
-                .port(embeddingStore.getPort())
+                .port(storeProperties.getPort())
                 .collectionName(collectionName)
-                .dimension(embeddingStore.getDimension())
+                .dimension(storeProperties.getDimension())
-                .indexType(embeddingStore.getIndexType())
+                .indexType(storeProperties.getIndexType())
-                .metricType(embeddingStore.getMetricType())
+                .metricType(storeProperties.getMetricType())
-                .uri(embeddingStore.getUri())
+                .uri(storeProperties.getUri())
-                .token(embeddingStore.getToken())
+                .token(storeProperties.getToken())
-                .username(embeddingStore.getUsername())
+                .username(storeProperties.getUsername())
-                .password(embeddingStore.getPassword())
+                .password(storeProperties.getPassword())
-                .consistencyLevel(embeddingStore.getConsistencyLevel())
+                .consistencyLevel(storeProperties.getConsistencyLevel())
-                .retrieveEmbeddingsOnSearch(embeddingStore.getRetrieveEmbeddingsOnSearch())
+                .retrieveEmbeddingsOnSearch(storeProperties.getRetrieveEmbeddingsOnSearch())
-                .databaseName(embeddingStore.getDatabaseName())
+                .autoFlushOnInsert(storeProperties.getAutoFlushOnInsert())
+                .databaseName(storeProperties.getDatabaseName())
                 .build();
     }
 }

common/src/main/java/dev/langchain4j/store/embedding/BaseEmbeddingStoreFactory.java

@@ -0,0 +1,16 @@
+package dev.langchain4j.store.embedding;
+
+import dev.langchain4j.data.segment.TextSegment;
+
+import java.util.Map;
+import java.util.concurrent.ConcurrentHashMap;
+
+public abstract class BaseEmbeddingStoreFactory implements EmbeddingStoreFactory {
+    protected static final Map<String, EmbeddingStore<TextSegment>> collectionNameToStore = new ConcurrentHashMap<>();
+
+    public EmbeddingStore<TextSegment> create(String collectionName) {
+        return collectionNameToStore.computeIfAbsent(collectionName, this::createEmbeddingStore);
+    }
+
+    public abstract EmbeddingStore<TextSegment> createEmbeddingStore(String collectionName);
+}

common/src/main/java/dev/langchain4j/store/embedding/EmbeddingStoreFactory.java

@@ -5,4 +5,5 @@ import dev.langchain4j.data.segment.TextSegment;
 public interface EmbeddingStoreFactory {
 
     EmbeddingStore<TextSegment> create(String collectionName);
+
 }

common/src/main/java/dev/langchain4j/store/embedding/milvus/MilvusEmbeddingStore.java

@@ -0,0 +1,375 @@
+package dev.langchain4j.store.embedding.milvus;
+
+import dev.langchain4j.data.document.Metadata;
+import dev.langchain4j.data.embedding.Embedding;
+import dev.langchain4j.data.segment.TextSegment;
+import dev.langchain4j.internal.Utils;
+import dev.langchain4j.store.embedding.EmbeddingMatch;
+import dev.langchain4j.store.embedding.EmbeddingSearchRequest;
+import dev.langchain4j.store.embedding.EmbeddingSearchResult;
+import dev.langchain4j.store.embedding.EmbeddingStore;
+import dev.langchain4j.store.embedding.filter.Filter;
+import io.milvus.client.MilvusServiceClient;
+import io.milvus.common.clientenum.ConsistencyLevelEnum;
+import io.milvus.param.ConnectParam;
+import io.milvus.param.IndexType;
+import io.milvus.param.MetricType;
+import io.milvus.param.dml.InsertParam;
+import io.milvus.param.dml.SearchParam;
+import io.milvus.response.SearchResultsWrapper;
+
+import java.util.ArrayList;
+import java.util.List;
+
+import static dev.langchain4j.internal.Utils.getOrDefault;
+import static dev.langchain4j.internal.ValidationUtils.ensureNotNull;
+import static dev.langchain4j.store.embedding.milvus.CollectionOperationsExecutor.createCollection;
+import static dev.langchain4j.store.embedding.milvus.CollectionOperationsExecutor.createIndex;
+import static dev.langchain4j.store.embedding.milvus.CollectionOperationsExecutor.flush;
+import static dev.langchain4j.store.embedding.milvus.CollectionOperationsExecutor.hasCollection;
+import static dev.langchain4j.store.embedding.milvus.CollectionOperationsExecutor.insert;
+import static dev.langchain4j.store.embedding.milvus.CollectionOperationsExecutor.loadCollectionInMemory;
+import static dev.langchain4j.store.embedding.milvus.CollectionRequestBuilder.buildSearchRequest;
+import static dev.langchain4j.store.embedding.milvus.Generator.generateRandomIds;
+import static dev.langchain4j.store.embedding.milvus.Mapper.toEmbeddingMatches;
+import static dev.langchain4j.store.embedding.milvus.Mapper.toMetadataJsons;
+import static dev.langchain4j.store.embedding.milvus.Mapper.toScalars;
+import static dev.langchain4j.store.embedding.milvus.Mapper.toVectors;
+import static io.milvus.common.clientenum.ConsistencyLevelEnum.EVENTUALLY;
+import static io.milvus.param.IndexType.FLAT;
+import static io.milvus.param.MetricType.COSINE;
+import static java.util.Collections.singletonList;
+import static java.util.stream.Collectors.toList;
+
+/**
+ * Represents an <a href="https://milvus.io/">Milvus</a> index as an embedding store.
+ * <br>
+ * Supports both local and <a href="https://zilliz.com/">managed</a> Milvus instances.
+ * <br>
+ * Supports storing {@link Metadata} and filtering by it using a {@link Filter}
+ * (provided inside an {@link EmbeddingSearchRequest}).
+ */
+public class MilvusEmbeddingStore implements EmbeddingStore<TextSegment> {
+
+    static final String ID_FIELD_NAME = "id";
+    static final String TEXT_FIELD_NAME = "text";
+    static final String METADATA_FIELD_NAME = "metadata";
+    static final String VECTOR_FIELD_NAME = "vector";
+
+    private final MilvusServiceClient milvusClient;
+    private final String collectionName;
+    private final MetricType metricType;
+    private final ConsistencyLevelEnum consistencyLevel;
+    private final boolean retrieveEmbeddingsOnSearch;
+
+    private final boolean autoFlushOnInsert;
+
+    public MilvusEmbeddingStore(
+            String host,
+            Integer port,
+            String collectionName,
+            Integer dimension,
+            IndexType indexType,
+            MetricType metricType,
+            String uri,
+            String token,
+            String username,
+            String password,
+            ConsistencyLevelEnum consistencyLevel,
+            Boolean retrieveEmbeddingsOnSearch,
+            Boolean autoFlushOnInsert,
+            String databaseName
+    ) {
+        ConnectParam.Builder connectBuilder = ConnectParam
+                .newBuilder()
+                .withHost(getOrDefault(host, "localhost"))
+                .withPort(getOrDefault(port, 19530))
+                .withUri(uri)
+                .withToken(token)
+                .withAuthorization(username, password);
+
+        if (databaseName != null) {
+            connectBuilder.withDatabaseName(databaseName);
+        }
+
+        this.milvusClient = new MilvusServiceClient(connectBuilder.build());
+        this.collectionName = getOrDefault(collectionName, "default");
+        this.metricType = getOrDefault(metricType, COSINE);
+        this.consistencyLevel = getOrDefault(consistencyLevel, EVENTUALLY);
+        this.retrieveEmbeddingsOnSearch = getOrDefault(retrieveEmbeddingsOnSearch, false);
+        this.autoFlushOnInsert = getOrDefault(autoFlushOnInsert, false);
+        if (!hasCollection(milvusClient, this.collectionName)) {
+            createCollection(milvusClient, this.collectionName, ensureNotNull(dimension, "dimension"));
+            createIndex(milvusClient, this.collectionName, getOrDefault(indexType, FLAT), this.metricType);
+        }
+
+        loadCollectionInMemory(milvusClient, collectionName);
+    }
+
+    public void dropCollection(String collectionName) {
+        CollectionOperationsExecutor.dropCollection(milvusClient, collectionName);
+    }
+
+    public String add(Embedding embedding) {
+        String id = Utils.randomUUID();
+        add(id, embedding);
+        return id;
+    }
+
+    public void add(String id, Embedding embedding) {
+        addInternal(id, embedding, null);
+    }
+
+    public String add(Embedding embedding, TextSegment textSegment) {
+        String id = Utils.randomUUID();
+        addInternal(id, embedding, textSegment);
+        return id;
+    }
+
+    public List<String> addAll(List<Embedding> embeddings) {
+        List<String> ids = generateRandomIds(embeddings.size());
+        addAllInternal(ids, embeddings, null);
+        return ids;
+    }
+
+    public List<String> addAll(List<Embedding> embeddings, List<TextSegment> embedded) {
+        List<String> ids = generateRandomIds(embeddings.size());
+        addAllInternal(ids, embeddings, embedded);
+        return ids;
+    }
+
+    @Override
+    public EmbeddingSearchResult<TextSegment> search(EmbeddingSearchRequest embeddingSearchRequest) {
+
+        SearchParam searchParam = buildSearchRequest(
+                collectionName,
+                embeddingSearchRequest.queryEmbedding().vectorAsList(),
+                embeddingSearchRequest.filter(),
+                embeddingSearchRequest.maxResults(),
+                metricType,
+                consistencyLevel
+        );
+
+        SearchResultsWrapper resultsWrapper = CollectionOperationsExecutor.search(milvusClient, searchParam);
+
+        List<EmbeddingMatch<TextSegment>> matches = toEmbeddingMatches(
+                milvusClient,
+                resultsWrapper,
+                collectionName,
+                consistencyLevel,
+                retrieveEmbeddingsOnSearch
+        );
+
+        List<EmbeddingMatch<TextSegment>> result = matches.stream()
+                .filter(match -> match.score() >= embeddingSearchRequest.minScore())
+                .collect(toList());
+
+        return new EmbeddingSearchResult<>(result);
+    }
+
+    private void addInternal(String id, Embedding embedding, TextSegment textSegment) {
+        addAllInternal(
+                singletonList(id),
+                singletonList(embedding),
+                textSegment == null ? null : singletonList(textSegment)
+        );
+    }
+
+    private void addAllInternal(List<String> ids, List<Embedding> embeddings, List<TextSegment> textSegments) {
+        List<InsertParam.Field> fields = new ArrayList<>();
+        fields.add(new InsertParam.Field(ID_FIELD_NAME, ids));
+        fields.add(new InsertParam.Field(TEXT_FIELD_NAME, toScalars(textSegments, ids.size())));
+        fields.add(new InsertParam.Field(METADATA_FIELD_NAME, toMetadataJsons(textSegments, ids.size())));
+        fields.add(new InsertParam.Field(VECTOR_FIELD_NAME, toVectors(embeddings)));
+
+        insert(milvusClient, collectionName, fields);
+        if (autoFlushOnInsert) {
+            flush(this.milvusClient, this.collectionName);
+        }
+    }
+
+    public static Builder builder() {
+        return new Builder();
+    }
+
+    public static class Builder {
+
+        private String host;
+        private Integer port;
+        private String collectionName;
+        private Integer dimension;
+        private IndexType indexType;
+        private MetricType metricType;
+        private String uri;
+        private String token;
+        private String username;
+        private String password;
+        private ConsistencyLevelEnum consistencyLevel;
+        private Boolean retrieveEmbeddingsOnSearch;
+        private Boolean autoFlushOnInsert;
+        private String databaseName;
+
+        /**
+         * @param host The host of the self-managed Milvus instance.
+         *             Default value: "localhost".
+         * @return builder
+         */
+        public Builder host(String host) {
+            this.host = host;
+            return this;
+        }
+
+        /**
+         * @param port The port of the self-managed Milvus instance.
+         *             Default value: 19530.
+         * @return builder
+         */
+        public Builder port(Integer port) {
+            this.port = port;
+            return this;
+        }
+
+        /**
+         * @param collectionName The name of the Milvus collection.
+         *                       If there is no such collection yet, it will be created automatically.
+         *                       Default value: "default".
+         * @return builder
+         */
+        public Builder collectionName(String collectionName) {
+            this.collectionName = collectionName;
+            return this;
+        }
+
+        /**
+         * @param dimension The dimension of the embedding vector. (e.g. 384)
+         *                  Mandatory if a new collection should be created.
+         * @return builder
+         */
+        public Builder dimension(Integer dimension) {
+            this.dimension = dimension;
+            return this;
+        }
+
+        /**
+         * @param indexType The type of the index.
+         *                  Default value: FLAT.
+         * @return builder
+         */
+        public Builder indexType(IndexType indexType) {
+            this.indexType = indexType;
+            return this;
+        }
+
+        /**
+         * @param metricType The type of the metric used for similarity search.
+         *                   Default value: COSINE.
+         * @return builder
+         */
+        public Builder metricType(MetricType metricType) {
+            this.metricType = metricType;
+            return this;
+        }
+
+        /**
+         * @param uri The URI of the managed Milvus instance. (e.g. "https://xxx.api.gcp-us-west1.zillizcloud.com")
+         * @return builder
+         */
+        public Builder uri(String uri) {
+            this.uri = uri;
+            return this;
+        }
+
+        /**
+         * @param token The token (API key) of the managed Milvus instance.
+         * @return builder
+         */
+        public Builder token(String token) {
+            this.token = token;
+            return this;
+        }
+
+        /**
+         * @param username The username. See details <a href="https://milvus.io/docs/authenticate.md">here</a>.
+         * @return builder
+         */
+        public Builder username(String username) {
+            this.username = username;
+            return this;
+        }
+
+        /**
+         * @param password The password. See details <a href="https://milvus.io/docs/authenticate.md">here</a>.
+         * @return builder
+         */
+        public Builder password(String password) {
+            this.password = password;
+            return this;
+        }
+
+        /**
+         * @param consistencyLevel The consistency level used by Milvus.
+         *                         Default value: EVENTUALLY.
+         * @return builder
+         */
+        public Builder consistencyLevel(ConsistencyLevelEnum consistencyLevel) {
+            this.consistencyLevel = consistencyLevel;
+            return this;
+        }
+
+        /**
+         * @param retrieveEmbeddingsOnSearch During a similarity search in Milvus (when calling findRelevant()),
+         *                                   the embedding itself is not retrieved.
+         *                                   To retrieve the embedding, an additional query is required.
+         *                                   Setting this parameter to "true" will ensure that embedding is retrieved.
+         *                                   Be aware that this will impact the performance of the search.
+         *                                   Default value: false.
+         * @return builder
+         */
+        public Builder retrieveEmbeddingsOnSearch(Boolean retrieveEmbeddingsOnSearch) {
+            this.retrieveEmbeddingsOnSearch = retrieveEmbeddingsOnSearch;
+            return this;
+        }
+
+        /**
+         * @param autoFlushOnInsert Whether to automatically flush after each insert
+         *                          ({@code add(...)} or {@code addAll(...)} methods).
+         *                          Default value: false.
+         *                          More info can be found
+         *                          <a href="https://milvus.io/api-reference/pymilvus/v2.4.x/ORM/Collection/flush.md">here</a>.
+         * @return builder
+         */
+        public Builder autoFlushOnInsert(Boolean autoFlushOnInsert) {
+            this.autoFlushOnInsert = autoFlushOnInsert;
+            return this;
+        }
+
+        /**
+         * @param databaseName Milvus name of database.
+         *                     Default value: null. In this case default Milvus database name will be used.
+         * @return builder
+         */
+        public Builder databaseName(String databaseName) {
+            this.databaseName = databaseName;
+            return this;
+        }
+
+        public MilvusEmbeddingStore build() {
+            return new MilvusEmbeddingStore(
+                    host,
+                    port,
+                    collectionName,
+                    dimension,
+                    indexType,
+                    metricType,
+                    uri,
+                    token,
+                    username,
+                    password,
+                    consistencyLevel,
+                    retrieveEmbeddingsOnSearch,
+                    autoFlushOnInsert,
+                    databaseName
+            );
+        }
+    }
+}

launchers/standalone/src/main/resources/langchain4j-local.yaml

@@ -24,19 +24,19 @@ langchain4j:
     embedding-model:
       model-name: bge-small-zh
 
-    embedding-store:
+#    embedding-store:
-      persist-path: /tmp
+#      persist-path: /tmp
 
 #  chroma:
 #    embedding-store:
 #      baseUrl: http://0.0.0.0:8000
 #      timeout: 120s
 
-#  milvus:
+  milvus:
-#    embedding-store:
+    embedding-store:
-#      host: localhost
+      host: localhost
-#      port: 2379
+      port: 2379
-#      uri: http://0.0.0.0:19530
+      uri: http://0.0.0.0:19530
-#      token: demo
+      token: demo
-#      dimension: 512
+      dimension: 512
-#      timeout: 120s
+      timeout: 120s

launchers/standalone/src/test/resources/application-local.yaml

@@ -0,0 +1,15 @@
+spring:
+  datasource:
+    driver-class-name: org.h2.Driver
+    schema: classpath:db/schema-h2.sql
+    data: classpath:db/data-h2.sql
+    url: jdbc:h2:mem:semantic;DATABASE_TO_UPPER=false
+    username: root
+    password: semantic
+  h2:
+    console:
+      path: /h2-console/semantic
+      enabled: true
+  config:
+    import:
+      - classpath:langchain4j-local.yaml

launchers/standalone/src/test/resources/application.yaml

@@ -13,7 +13,6 @@ spring:
   config:
     import:
       - classpath:s2-config.yaml
-      - classpath:langchain4j-local.yaml
   autoconfigure:
     exclude:
       - spring.dev.langchain4j.spring.LangChain4jAutoConfig
@@ -22,17 +21,6 @@ spring:
       - spring.dev.langchain4j.azure.openai.spring.AutoConfig
       - spring.dev.langchain4j.azure.aisearch.spring.AutoConfig
       - spring.dev.langchain4j.anthropic.spring.AutoConfig
-  h2:
-    console:
-      path: /h2-console/semantic
-      enabled: true
-  datasource:
-    driver-class-name: org.h2.Driver
-    schema: classpath:db/schema-h2.sql
-    data: classpath:db/data-h2.sql
-    url: jdbc:h2:mem:semantic;DATABASE_TO_UPPER=false
-    username: root
-    password: semantic
 
 mybatis:
   mapper-locations=classpath:mappers/custom/*.xml,classpath*:/mappers/*.xml
@@ -40,4 +28,16 @@ mybatis:
 logging:
   level:
     dev.langchain4j: DEBUG
-    dev.ai4j.openai4j: DEBUG
+    dev.ai4j.openai4j: DEBUG
+
+swagger:
+  title: 'SuperSonic API Documentation'
+  base:
+    package: com.tencent.supersonic
+  description: 'SuperSonic API Documentation'
+  url: ''
+  contact:
+    name:
+    email:
+    url: ''
+  version: 3.0