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src/main/java/xyz/wbsite/ai/RagTest.java

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+package xyz.wbsite.ai;
+
+import dev.langchain4j.data.document.*;
+import dev.langchain4j.data.document.loader.FileSystemDocumentLoader;
+import dev.langchain4j.data.document.parser.TextDocumentParser;
+import dev.langchain4j.data.segment.TextSegment;
+import dev.langchain4j.memory.chat.MessageWindowChatMemory;
+import dev.langchain4j.model.chat.ChatLanguageModel;
+import dev.langchain4j.model.ollama.OllamaChatModel;
+import dev.langchain4j.model.openai.OpenAiChatModel;
+import dev.langchain4j.rag.content.Content;
+import dev.langchain4j.rag.content.retriever.EmbeddingStoreContentRetriever;
+import dev.langchain4j.rag.query.Query;
+import dev.langchain4j.service.AiServices;
+import dev.langchain4j.service.SystemMessage;
+import dev.langchain4j.store.embedding.EmbeddingStoreIngestor;
+import dev.langchain4j.store.embedding.inmemory.InMemoryEmbeddingStore;
+
+import java.io.IOException;
+import java.io.InputStream;
+import java.util.List;
+
+public class RagTest {
+
+    public static void main(String[] args) {
+
+        List<Document> documents = FileSystemDocumentLoader.loadDocuments("D:\\wbSource\\starter-ai\\src\\main\\resources");
+        InMemoryEmbeddingStore<TextSegment> embeddingStore = new InMemoryEmbeddingStore<>();
+        EmbeddingStoreIngestor.ingest(documents, embeddingStore);
+
+        EmbeddingStoreContentRetriever embeddingStoreContentRetriever = EmbeddingStoreContentRetriever.from(embeddingStore);
+
+        List<Content> retrieve = embeddingStoreContentRetriever.retrieve(new Query("java中会存在内存泄漏吗，请简单描述"));
+
+        System.out.println();
+
+//        ChatLanguageModel model = OllamaChatModel.builder()
+//                .baseUrl("http://36.138.207.178:11434")
+//                .modelName("deepseek-r1:32B")
+//                .build();
+//
+//        Assistant assistant = AiServices.create(Assistant.class,model);
+//                .chatMemory(MessageWindowChatMemory.withMaxMessages(10))
+//                .contentRetriever(EmbeddingStoreContentRetriever.from(embeddingStore))
+//                .build();
+//
+//        String chat = assistant.chat("java中会存在内存泄漏吗，请简单描述。");
+//        System.out.println(chat);
+    }
+
+
+    interface Assistant {
+
+//        @SystemMessage("请扮演一名小学生,根据输入的文章题目写一篇100字以内的作文")
+        String chat(String userMessage);
+    }
+
+}