diff --git a/src/main/java/com/ai/config/AssistantInit.java b/src/main/java/com/ai/config/AssistantInit.java index 7e20d53..2199000 100644 --- a/src/main/java/com/ai/config/AssistantInit.java +++ b/src/main/java/com/ai/config/AssistantInit.java @@ -13,6 +13,7 @@ import dev.langchain4j.service.AiServices; import dev.langchain4j.store.embedding.EmbeddingStoreIngestor; import dev.langchain4j.store.embedding.inmemory.InMemoryEmbeddingStore; import lombok.RequiredArgsConstructor; +import org.springframework.beans.factory.annotation.Value; import org.springframework.context.annotation.Bean; import org.springframework.context.annotation.Configuration; @@ -24,11 +25,17 @@ public class AssistantInit { // All files in a directory, txt seems to be faster + @Value("${langchain4j.api-key}") + private String apiKey; + + @Value("${langchain4j.model}") + private String model; + @Bean public Assist init() { ChatLanguageModel qwenModel = QwenChatModel.builder() - .apiKey("sk-2f703a41fff0488e9b6888013d2ee58a") - .modelName("deepseek-v3") + .apiKey(apiKey) + .modelName(model) .build(); List documents = FileSystemDocumentLoader.loadDocuments("E:\\ideaProject\\liang-ai"); // for simplicity, we will use an in-memory one: @@ -38,7 +45,7 @@ public class AssistantInit { .chatMemoryProvider(memoryId -> MessageWindowChatMemory.withMaxMessages(10)) .chatLanguageModel(qwenModel) .contentRetriever(EmbeddingStoreContentRetriever.from(embeddingStore)) - .tools(new MyCalculator()) +// .tools(new MyCalculator()) .build(); } } diff --git a/src/main/resources/application.properties b/src/main/resources/application.properties index 6c95218..8b201cd 100644 --- a/src/main/resources/application.properties +++ b/src/main/resources/application.properties @@ -2,3 +2,7 @@ server.port=8080 langchain4j.community.dashscope.chat-model.api-key=sk-2f703a41fff0488e9b6888013d2ee58a langchain4j.community.dashscope.chat-model.model-name=deepseek-v3 + + +langchain4j.api-key=sk-2f703a41fff0488e9b6888013d2ee58a +langchain4j.model=deepseek-v3 \ No newline at end of file