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Merge branch 'main' of github.com:LangMem/mem4j into feat-winston
2 parents 61d7617 + e70f25d commit 044d5af

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‎.gitignore‎

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@@ -187,3 +187,4 @@ qdrant_storage/
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.crossnote
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testing.ipynb
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checkstyle-report.xml
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.flattened-pom.xml

‎mem4j-autoconfigure/src/main/java/io/github/mem4j/autoconfigure/MemoryAutoConfiguration.java‎

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@EnableConfigurationProperties(MemoryConfig.class)
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public class MemoryAutoConfiguration {
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private static final Logger logger = LoggerFactory.getLogger(MemoryAutoConfiguration.class);
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private static final Logger logger = LoggerFactory.getLogger(MemoryAutoConfiguration.class);
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/**
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* Creates the main Memory bean with all required dependencies. This bean will be
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* created only if no other Memory bean exists.
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*
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* @param memoryConfig the memory configuration properties
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* @param vectorStoreService the vector store service (auto-selected based on config)
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* @param llmService the LLM service (auto-selected based on config)
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* @param embeddingService the embedding service (auto-selected based on config)
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* @return configured Memory instance
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*/
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@Bean
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@ConditionalOnMissingBean
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public Memory memory(MemoryConfig memoryConfig, VectorStoreService vectorStoreService, LLMService llmService, EmbeddingService embeddingService) {
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logger.info("Creating Memory bean with vector store type: {}", memoryConfig.getVectorStore().getType());
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return new Memory(memoryConfig, vectorStoreService, llmService, embeddingService);
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}
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/**
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* Creates the main Memory bean with all required dependencies. This bean will be
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* created only if no other Memory bean exists.
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* @param memoryConfig the memory configuration properties
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* @param vectorStoreService the vector store service (auto-selected based on config)
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* @param llmService the LLM service (auto-selected based on config)
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* @param embeddingService the embedding service (auto-selected based on config)
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* @return configured Memory instance
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*/
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@Bean
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@ConditionalOnMissingBean
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public Memory memory(MemoryConfig memoryConfig, VectorStoreService vectorStoreService, LLMService llmService,
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EmbeddingService embeddingService) {
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logger.info("Creating Memory bean with vector store type: {}", memoryConfig.getVectorStore().getType());
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return new Memory(memoryConfig, vectorStoreService, llmService, embeddingService);
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}
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/**
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* Creates an InMemoryVectorStore service when no other VectorStore is configured or
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* when explicitly configured to use 'inmemory' type.
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*
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* @return InMemoryVectorStoreService instance
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*/
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@Bean
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@ConditionalOnMissingBean
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@ConditionalOnProperty(prefix = "mem4j.vector-store", name = "type", havingValue = "inmemory", matchIfMissing = true)
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public VectorStoreService inMemoryVectorStoreService() {
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logger.info("Creating InMemoryVectorStoreService");
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return new InMemoryVectorStoreService();
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}
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/**
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* Creates an InMemoryVectorStore service when no other VectorStore is configured or
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* when explicitly configured to use 'inmemory' type.
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* @return InMemoryVectorStoreService instance
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*/
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@Bean
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@ConditionalOnMissingBean
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@ConditionalOnProperty(prefix = "mem4j.vector-store", name = "type", havingValue = "inmemory",
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matchIfMissing = true)
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public VectorStoreService inMemoryVectorStoreService() {
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logger.info("Creating InMemoryVectorStoreService");
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return new InMemoryVectorStoreService();
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}
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/**
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* Creates a Qdrant VectorStore service when configured to use 'qdrant' type. This
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* bean will only be created if the Qdrant client classes are available on the
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* classpath.
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*
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* @param memoryConfig the memory configuration properties
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* @return QdrantVectorStoreService instance
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*/
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@Bean
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@ConditionalOnMissingBean
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@ConditionalOnProperty(prefix = "mem4j.vector-store", name = "type", havingValue = "qdrant")
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@ConditionalOnClass(name = "io.qdrant.client.QdrantClient")
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public VectorStoreService qdrantVectorStoreService(MemoryConfig memoryConfig) {
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logger.info("Creating QdrantVectorStoreService");
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return new QdrantVectorStoreService(memoryConfig);
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}
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/**
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* Creates a Qdrant VectorStore service when configured to use 'qdrant' type. This
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* bean will only be created if the Qdrant client classes are available on the
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* classpath.
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* @param memoryConfig the memory configuration properties
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* @return QdrantVectorStoreService instance
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*/
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@Bean
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@ConditionalOnMissingBean
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@ConditionalOnProperty(prefix = "mem4j.vector-store", name = "type", havingValue = "qdrant")
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@ConditionalOnClass(name = "io.qdrant.client.QdrantClient")
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public VectorStoreService qdrantVectorStoreService(MemoryConfig memoryConfig) {
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logger.info("Creating QdrantVectorStoreService");
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return new QdrantVectorStoreService(memoryConfig);
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}
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/**
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* Creates a Milvus VectorStore service when configured to use 'milvus' type. This
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* bean will only be created if the Milvus client classes are available on the
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* classpath.
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*
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* @param memoryConfig the memory configuration properties
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* @return MilvusVectorStoreService instance
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*/
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@Bean
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@ConditionalOnMissingBean
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@ConditionalOnProperty(prefix = "mem4j.vector-store", name = "type", havingValue = "milvus", matchIfMissing = true)
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@ConditionalOnClass(name = "io.milvus.client.MilvusClient")
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public VectorStoreService milvusVectorStoreService(MemoryConfig memoryConfig) {
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logger.info("Creating MilvusVectorStoreService");
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return new MilvusVectorStoreService(memoryConfig);
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}
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/**
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* Creates a Milvus VectorStore service when configured to use 'milvus' type. This
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* bean will only be created if the Milvus client classes are available on the
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* classpath.
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* @param memoryConfig the memory configuration properties
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* @return MilvusVectorStoreService instance
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*/
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@Bean
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@ConditionalOnMissingBean
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@ConditionalOnProperty(prefix = "mem4j.vector-store", name = "type", havingValue = "milvus", matchIfMissing = true)
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@ConditionalOnClass(name = "io.milvus.client.MilvusClient")
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public VectorStoreService milvusVectorStoreService(MemoryConfig memoryConfig) {
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logger.info("Creating MilvusVectorStoreService");
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return new MilvusVectorStoreService(memoryConfig);
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}
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/**
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* Creates the appropriate LLM service based on configuration. Supports OpenAI and
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* DashScope implementations.
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*
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* @param memoryConfig the memory configuration properties
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* @return LLMService instance based on configuration
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*/
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@Bean
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@ConditionalOnMissingBean
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public LLMService llmService(MemoryConfig memoryConfig) {
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String llmType = memoryConfig.getLlm().getType();
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logger.info("Creating LLM service of type: {}", llmType);
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/**
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* Creates the appropriate LLM service based on configuration. Supports OpenAI and
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* DashScope implementations.
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* @param memoryConfig the memory configuration properties
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* @return LLMService instance based on configuration
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*/
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@Bean
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@ConditionalOnMissingBean
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public LLMService llmService(MemoryConfig memoryConfig) {
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String llmType = memoryConfig.getLlm().getType();
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logger.info("Creating LLM service of type: {}", llmType);
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return switch (llmType.toLowerCase()) {
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case "dashscope" -> new DashScopeLLMService(memoryConfig);
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case "openai" -> new OpenAILLMService(memoryConfig);
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default -> {
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logger.warn("Unknown LLM type: {}, falling back to OpenAI", llmType);
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yield new OpenAILLMService(memoryConfig);
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}
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};
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}
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return switch (llmType.toLowerCase()) {
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case "dashscope" -> new DashScopeLLMService(memoryConfig);
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case "openai" -> new OpenAILLMService(memoryConfig);
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default -> {
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logger.warn("Unknown LLM type: {}, falling back to OpenAI", llmType);
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yield new OpenAILLMService(memoryConfig);
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}
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};
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}
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/**
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* Creates the appropriate Embedding service based on configuration. Supports OpenAI
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* and DashScope implementations.
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*
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* @param memoryConfig the memory configuration properties
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* @return EmbeddingService instance based on configuration
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*/
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@Bean
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@ConditionalOnMissingBean
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public EmbeddingService embeddingService(MemoryConfig memoryConfig) {
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String embeddingType = memoryConfig.getEmbeddings().getType();
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logger.info("Creating Embedding service of type: {}", embeddingType);
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/**
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* Creates the appropriate Embedding service based on configuration. Supports OpenAI
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* and DashScope implementations.
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* @param memoryConfig the memory configuration properties
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* @return EmbeddingService instance based on configuration
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*/
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@Bean
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@ConditionalOnMissingBean
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public EmbeddingService embeddingService(MemoryConfig memoryConfig) {
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String embeddingType = memoryConfig.getEmbeddings().getType();
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logger.info("Creating Embedding service of type: {}", embeddingType);
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return switch (embeddingType.toLowerCase()) {
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case "dashscope" -> new DashScopeEmbeddingService(memoryConfig);
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case "openai" -> new OpenAIEmbeddingService(memoryConfig);
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default -> {
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logger.warn("Unknown embedding type: {}, falling back to OpenAI", embeddingType);
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yield new OpenAIEmbeddingService(memoryConfig);
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}
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};
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}
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return switch (embeddingType.toLowerCase()) {
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case "dashscope" -> new DashScopeEmbeddingService(memoryConfig);
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case "openai" -> new OpenAIEmbeddingService(memoryConfig);
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default -> {
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logger.warn("Unknown embedding type: {}, falling back to OpenAI", embeddingType);
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yield new OpenAIEmbeddingService(memoryConfig);
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}
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};
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}
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}

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