Update class level javadoc in some vector stores to match builder signatures

2024-12-23 10:41:01 -05:00
parent c257220d85
commit 3bb49c3fd6
11 changed files with 24 additions and 55 deletions
--- a/vector-stores/spring-ai-cassandra-store/src/main/java/org/springframework/ai/vectorstore/cassandra/CassandraVectorStore.java
+++ b/vector-stores/spring-ai-cassandra-store/src/main/java/org/springframework/ai/vectorstore/cassandra/CassandraVectorStore.java
@@ -104,9 +104,8 @@ import org.springframework.util.Assert;
 * Basic usage example:
 * </p>
 * <pre>{@code
- * CassandraVectorStore vectorStore = CassandraVectorStore.builder()
+ * CassandraVectorStore vectorStore = CassandraVectorStore.builder(embeddingModel)
 *     .session(cqlSession)
- *     .embeddingModel(embeddingModel)
 *     .keyspace("my_keyspace")
 *     .table("my_vectors")
 *     .build();
@@ -130,9 +129,8 @@ import org.springframework.util.Assert;
 * Advanced configuration example:
 * </p>
 * <pre>{@code
- * CassandraVectorStore vectorStore = CassandraVectorStore.builder()
+ * CassandraVectorStore vectorStore = CassandraVectorStore.builder(embeddingModel)
 *     .session(cqlSession)
- *     .embeddingModel(embeddingModel)
 *     .keyspace("my_keyspace")
 *     .table("my_vectors")
 *     .partitionKeys(List.of(new SchemaColumn("id", DataTypes.TEXT)))
--- a/vector-stores/spring-ai-elasticsearch-store/src/main/java/org/springframework/ai/vectorstore/elasticsearch/ElasticsearchVectorStore.java
+++ b/vector-stores/spring-ai-elasticsearch-store/src/main/java/org/springframework/ai/vectorstore/elasticsearch/ElasticsearchVectorStore.java
@@ -83,9 +83,7 @@ import org.springframework.util.Assert;
 * Basic usage example:
 * </p>
 * <pre>{@code
- * ElasticsearchVectorStore vectorStore = ElasticsearchVectorStore.builder()
- *     .restClient(restClient)
- *     .embeddingModel(embeddingModel)
+ * ElasticsearchVectorStore vectorStore = ElasticsearchVectorStore.builder(restClient, embeddingModel)
 *     .initializeSchema(true)
 *     .build();
 *
@@ -113,9 +111,7 @@ import org.springframework.util.Assert;
 * options.setSimilarity(SimilarityFunction.dot_product);
 * options.setDimensions(1536);
 *
- * ElasticsearchVectorStore vectorStore = ElasticsearchVectorStore.builder()
- *     .restClient(restClient)
- *     .embeddingModel(embeddingModel)
+ * ElasticsearchVectorStore vectorStore = ElasticsearchVectorStore.builder(restClient, embeddingModel)
 *     .options(options)
 *     .initializeSchema(true)
 *     .batchingStrategy(new TokenCountBatchingStrategy())
--- a/vector-stores/spring-ai-mariadb-store/src/main/java/org/springframework/ai/vectorstore/mariadb/MariaDBVectorStore.java
+++ b/vector-stores/spring-ai-mariadb-store/src/main/java/org/springframework/ai/vectorstore/mariadb/MariaDBVectorStore.java
@@ -33,6 +33,7 @@ import org.springframework.ai.embedding.EmbeddingOptionsBuilder;
 import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.observation.conventions.VectorStoreSimilarityMetric;
+import org.springframework.ai.observation.conventions.VectorStoreSimilarityMetric;
 import org.springframework.ai.util.JacksonUtils;
 import org.springframework.ai.vectorstore.AbstractVectorStoreBuilder;
 import org.springframework.ai.vectorstore.SearchRequest;
@@ -73,8 +74,7 @@ import org.springframework.util.StringUtils;
 * Basic usage example:
 * </p>
 * <pre>{@code
- * MariaDBVectorStore vectorStore = MariaDBVectorStore.builder(jdbcTemplate)
- *     .embeddingModel(embeddingModel)
+ * MariaDBVectorStore vectorStore = MariaDBVectorStore.builder(jdbcTemplate, embeddingModel)
 *     .initializeSchema(true)
 *     .build();
 *
@@ -97,8 +97,7 @@ import org.springframework.util.StringUtils;
 * Advanced configuration example:
 * </p>
 * <pre>{@code
- * MariaDBVectorStore vectorStore = MariaDBVectorStore.builder(jdbcTemplate)
- *     .embeddingModel(embeddingModel)
+ * MariaDBVectorStore vectorStore = MariaDBVectorStore.builder(jdbcTemplate, embeddingModel)
 *     .schemaName("mydb")
 *     .distanceType(MariaDBDistanceType.COSINE)
 *     .dimensions(1536)
@@ -295,7 +294,8 @@ public class MariaDBVectorStore extends AbstractObservationVectorStore implement
 		this.vectorTableName = builder.vectorTableName.isEmpty() ? DEFAULT_TABLE_NAME
 				: MariaDBSchemaValidator.validateAndEnquoteIdentifier(builder.vectorTableName.trim(), false);

-		logger.info("Using the vector table name: {}. Is empty: {}", this.vectorTableName, vectorTableName.isEmpty());
+		logger.info("Using the vector table name: {}. Is empty: {}", this.vectorTableName,
+				builder.vectorTableName.isEmpty());

 		this.schemaName = builder.schemaName == null ? null
 				: MariaDBSchemaValidator.validateAndEnquoteIdentifier(builder.schemaName, false);
--- a/vector-stores/spring-ai-milvus-store/src/main/java/org/springframework/ai/milvus/vectorstore/MilvusVectorStore.java
+++ b/vector-stores/spring-ai-milvus-store/src/main/java/org/springframework/ai/milvus/vectorstore/MilvusVectorStore.java
@@ -92,16 +92,12 @@ import org.springframework.util.StringUtils;
 * <p>
 * Example usage: <pre>{@code
 * // Create a basic Milvus vector store
- * MilvusVectorStore vectorStore = MilvusVectorStore.builder()
- *     .milvusClient(milvusClient)
- *     .embeddingModel(embeddingModel)
+ * MilvusVectorStore vectorStore = MilvusVectorStore.builder(milvusServiceClient, embeddingModel)
 *     .initializeSchema(true)
 *     .build();
 *
 * // Create a customized Milvus vector store
- * MilvusVectorStore customVectorStore = MilvusVectorStore.builder()
- *     .milvusClient(milvusClient)
- *     .embeddingModel(embeddingModel)
+ * MilvusVectorStore customVectorStore = MilvusVectorStore.builder(milvusServiceClient, embeddingModel)
 *     .databaseName("my_database")
 *     .collectionName("my_collection")
 *     .metricType(MetricType.COSINE)
@@ -267,8 +263,8 @@ public class MilvusVectorStore extends AbstractObservationVectorStore implements
 	 * recommended way to instantiate a MilvusBuilder.
 	 * @return a new MilvusBuilder instance
 	 */
-	public static Builder builder(MilvusServiceClient milvusClient, EmbeddingModel embeddingModel) {
-		return new Builder(milvusClient, embeddingModel);
+	public static Builder builder(MilvusServiceClient milvusServiceClient, EmbeddingModel embeddingModel) {
+		return new Builder(milvusServiceClient, embeddingModel);
 	}

 	@Override
--- a/vector-stores/spring-ai-mongodb-atlas-store/src/main/java/org/springframework/ai/vectorstore/mongodb/atlas/MongoDBAtlasVectorStore.java
+++ b/vector-stores/spring-ai-mongodb-atlas-store/src/main/java/org/springframework/ai/vectorstore/mongodb/atlas/MongoDBAtlasVectorStore.java
@@ -72,9 +72,7 @@ import org.springframework.util.Assert;
 * Basic usage example:
 * </p>
 * <pre>{@code
- * MongoDBAtlasVectorStore vectorStore = MongoDBAtlasVectorStore.builder()
- *     .mongoTemplate(mongoTemplate)
- *     .embeddingModel(embeddingModel)
+ * MongoDBAtlasVectorStore vectorStore = MongoDBAtlasVectorStore.builder(mongoTemplate, embeddingModel)
 *     .collectionName("vector_store")
 *     .initializeSchema(true)
 *     .build();
@@ -98,9 +96,7 @@ import org.springframework.util.Assert;
 * Advanced configuration example:
 * </p>
 * <pre>{@code
- * MongoDBAtlasVectorStore vectorStore = MongoDBAtlasVectorStore.builder()
- *     .mongoTemplate(mongoTemplate)
- *     .embeddingModel(embeddingModel)
+ * MongoDBAtlasVectorStore vectorStore = MongoDBAtlasVectorStore.builder(mongoTemplate, embeddingModel)
 *     .collectionName("custom_vectors")
 *     .vectorIndexName("custom_vector_index")
 *     .pathName("custom_embedding")
--- a/vector-stores/spring-ai-neo4j-store/src/main/java/org/springframework/ai/vectorstore/neo4j/Neo4jVectorStore.java
+++ b/vector-stores/spring-ai-neo4j-store/src/main/java/org/springframework/ai/vectorstore/neo4j/Neo4jVectorStore.java
@@ -72,9 +72,7 @@ import org.springframework.util.StringUtils;
 * Basic usage example:
 * </p>
 * <pre>{@code
- * Neo4jVectorStore vectorStore = Neo4jVectorStore.builder()
- *     .driver(driver)
- *     .embeddingModel(embeddingModel)
+ * Neo4jVectorStore vectorStore = Neo4jVectorStore.builder(driver, embeddingModel)
 *     .initializeSchema(true)
 *     .build();
 *
@@ -97,9 +95,7 @@ import org.springframework.util.StringUtils;
 * Advanced configuration example:
 * </p>
 * <pre>{@code
- * Neo4jVectorStore vectorStore = Neo4jVectorStore.builder()
- *     .driver(driver)
- *     .embeddingModel(embeddingModel)
+ * Neo4jVectorStore vectorStore = Neo4jVectorStore.builder(driver, embeddingModel)
 *     .databaseName("neo4j")
 *     .distanceType(Neo4jDistanceType.COSINE)
 *     .dimensions(1536)
--- a/vector-stores/spring-ai-opensearch-store/src/main/java/org/springframework/ai/vectorstore/opensearch/OpenSearchVectorStore.java
+++ b/vector-stores/spring-ai-opensearch-store/src/main/java/org/springframework/ai/vectorstore/opensearch/OpenSearchVectorStore.java
@@ -82,9 +82,7 @@ import org.springframework.util.Assert;
 * Basic usage example:
 * </p>
 * <pre>{@code
- * OpenSearchVectorStore vectorStore = OpenSearchVectorStore.builder()
- *     .openSearchClient(openSearchClient)
- *     .embeddingModel(embeddingModel)
+ * OpenSearchVectorStore vectorStore = OpenSearchVectorStore.builder(openSearchClient, embeddingModel)
 *     .initializeSchema(true)
 *     .build();
 *
@@ -107,9 +105,7 @@ import org.springframework.util.Assert;
 * Advanced configuration example:
 * </p>
 * <pre>{@code
- * OpenSearchVectorStore vectorStore = OpenSearchVectorStore.builder()
- *     .openSearchClient(openSearchClient)
- *     .embeddingModel(embeddingModel)
+ * OpenSearchVectorStore vectorStore = OpenSearchVectorStore.builder(openSearchClient, embeddingModel)
 *     .index("custom-index")
 *     .mappingJson(customMapping)
 *     .similarityFunction("l2")
--- a/vector-stores/spring-ai-pgvector-store/src/main/java/org/springframework/ai/vectorstore/pgvector/PgVectorStore.java
+++ b/vector-stores/spring-ai-pgvector-store/src/main/java/org/springframework/ai/vectorstore/pgvector/PgVectorStore.java
@@ -85,9 +85,7 @@ import org.springframework.util.StringUtils;
 * Basic usage example:
 * </p>
 * <pre>{@code
- * PgVectorStore vectorStore = PgVectorStore.builder()
- *     .jdbcTemplate(jdbcTemplate)
- *     .embeddingModel(embeddingModel)
+ * PgVectorStore vectorStore = PgVectorStore.builder(jdbcTemplate, embeddingModel)
 *     .dimensions(1536) // Optional: defaults to model dimensions or 1536
 *     .distanceType(PgDistanceType.COSINE_DISTANCE)
 *     .indexType(PgIndexType.HNSW)
@@ -112,9 +110,7 @@ import org.springframework.util.StringUtils;
 * Advanced configuration example:
 * </p>
 * <pre>{@code
- * PgVectorStore vectorStore = PgVectorStore.builder()
- *     .jdbcTemplate(jdbcTemplate)
- *     .embeddingModel(embeddingModel)
+ * PgVectorStore vectorStore = PgVectorStore.builder(jdbcTemplate, embeddingModel)
 *     .schemaName("custom_schema")
 *     .vectorTableName("custom_vectors")
 *     .distanceType(PgDistanceType.NEGATIVE_INNER_PRODUCT)
--- a/vector-stores/spring-ai-qdrant-store/src/main/java/org/springframework/ai/vectorstore/qdrant/QdrantVectorStore.java
+++ b/vector-stores/spring-ai-qdrant-store/src/main/java/org/springframework/ai/vectorstore/qdrant/QdrantVectorStore.java
@@ -101,8 +101,7 @@ import org.springframework.util.Assert;
 * Advanced configuration example:
 * </p>
 * <pre>{@code
- * QdrantVectorStore vectorStore = QdrantVectorStore.builder(qdrantClient)
- *     .embeddingModel(embeddingModel)
+ * QdrantVectorStore vectorStore = QdrantVectorStore.builder(qdrantClient, embeddingModel)
 *     .collectionName("custom-collection")
 *     .initializeSchema(true)
 *     .batchingStrategy(new TokenCountBatchingStrategy())
--- a/vector-stores/spring-ai-redis-store/src/main/java/org/springframework/ai/vectorstore/redis/RedisVectorStore.java
+++ b/vector-stores/spring-ai-redis-store/src/main/java/org/springframework/ai/vectorstore/redis/RedisVectorStore.java
@@ -102,9 +102,7 @@ import org.springframework.util.StringUtils;
 * Basic usage example:
 * </p>
 * <pre>{@code
- * RedisVectorStore vectorStore = RedisVectorStore.builder()
- *     .jedis(jedisPooled)
- *     .embeddingModel(embeddingModel)
+ * RedisVectorStore vectorStore = RedisVectorStore.builder(jedisPooled, embeddingModel)
 *     .indexName("custom-index")     // Optional: defaults to "spring-ai-index"
 *     .prefix("custom-prefix")       // Optional: defaults to "embedding:"
 *     .vectorAlgorithm(Algorithm.HNSW)
--- a/vector-stores/spring-ai-weaviate-store/src/main/java/org/springframework/ai/vectorstore/weaviate/WeaviateVectorStore.java
+++ b/vector-stores/spring-ai-weaviate-store/src/main/java/org/springframework/ai/vectorstore/weaviate/WeaviateVectorStore.java
@@ -76,9 +76,7 @@ import org.springframework.util.StringUtils;
 * </p>
 * <pre>{@code
 * // Create the vector store with builder
- * WeaviateVectorStore vectorStore = WeaviateVectorStore.builder()
- *     .weaviateClient(weaviateClient)            // Required: Configure Weaviate client
- *     .embeddingModel(embeddingModel)            // Required: Configure embedding model
+ * WeaviateVectorStore vectorStore = WeaviateVectorStore.builder(weaviateClient, embeddingModel)
 *     .objectClass("CustomClass")                // Optional: Custom class name (default: SpringAiWeaviate)
 *     .consistencyLevel(ConsistentLevel.QUORUM)  // Optional: Set consistency level (default: ONE)
 *     .filterMetadataFields(List.of(             // Optional: Configure filterable metadata fields