升级到solon版本，上传文件自动生成多级章节

llm-back/ruoyi-agent/pom.xml

     </description>
 
     <properties>
-        <solon.version>3.3.3</solon.version>
+        <solon.version>3.4.3</solon.version>
     </properties>
 
     <dependencies>
         <dependency>
             <groupId>org.noear</groupId>
             <artifactId>solon-ai-mcp</artifactId>
-            <exclusions>
-                <exclusion>
-                    <groupId>org.slf4j</groupId>
-                    <artifactId>*</artifactId>
-                </exclusion>
-            </exclusions>
         </dependency>
 
         <dependency>

llm-back/ruoyi-agent/src/main/java/com/ruoyi/agent/service/impl/McpServiceImpl.java

 import org.noear.solon.ai.chat.ChatSessionDefault;
 import org.noear.solon.ai.chat.message.AssistantMessage;
 import org.noear.solon.ai.chat.message.ChatMessage;
+import org.noear.solon.ai.chat.session.InMemoryChatSession;
 import org.noear.solon.ai.mcp.server.annotation.McpServerEndpoint;
 import org.noear.solon.annotation.Param;
 import org.springframework.stereotype.Service;
 
     private static final EmbeddingModel embeddingModel = new BgeSmallZhV15EmbeddingModel();
 
+    private static final String llmServiceUrl = "http://192.168.28.188:8000/v1/chat/completions";
+
     private static final MilvusServiceClient milvusClient = new MilvusServiceClient(
             ConnectParam.newBuilder()
                     .withHost("192.168.28.188")
                     .withPort(19530)
                     .build());
+
     /**
      * 调用LLM+RAG（外部文件+知识库）生成回答
      */
                                            @Param(description = "技术文件地址") String templatePath) throws IOException
     {
             try {
-                title = String.join(",", extractSubTitles( "/upload/agent/template/technical.docx", title));
+                templatePath = templatePath.replace("/dev-api/profile", Solon.cfg().getProperty("cmc.profile"));
+                title = String.join(",", extractSubTitles(templatePath, title));
 //                List<JSONObject> contexts = retrieveFromMilvus(milvusClient, embeddingModel, collectionName, title, 10);
-//                return generateAnswerWithDocumentAndCollection(embeddingModel, agentName, templatePath, title, contexts, "http://192.168.28.188:8000/v1/chat/completions");
-                return generateAnswerWithDocumentAndCollection(embeddingModel, agentName, templatePath, title, new ArrayList<>(), "http://192.168.28.188:8000/v1/chat/completions");
+//                return generateAnswerWithDocumentAndCollection(embeddingModel, agentName, templatePath, title, contexts, llmServiceUrl);
+                return generateAnswerWithDocumentAndCollection(embeddingModel, agentName, templatePath, title, new ArrayList<>(), llmServiceUrl);
             } catch (IOException e) {
                 throw new RuntimeException(e);
             }
      */
     public AssistantMessage generateAnswerWithDocumentAndCollection(EmbeddingModel embeddingModel, String agentName, String templatePath, String question, List<JSONObject> contexts, String llmServiceUrl) throws IOException {
         StringBuilder sb = new StringBuilder("招标文件内容：\n\n");
-        String filename = templatePath.replace("/dev-api/profile", Solon.cfg().getProperty("cmc.profile")).replace("_" + agentName, "");
+        String filename = templatePath.replace("_" + agentName, "");
         File profilePath = new File(filename);
         if (!profilePath.exists()) {
             filename = filename.replace(".docx", ".doc");
             profilePath = new File(filename);
         }
+        InMemoryEmbeddingStore<TextSegment> embeddingStore = new InMemoryEmbeddingStore<>();
         List<TextSegment> segments = splitDocument(profilePath);
         List<Embedding> embeddings = embeddingModel.embedAll(segments).content();
-        InMemoryEmbeddingStore<TextSegment> embeddingStore = new InMemoryEmbeddingStore<>();
         embeddingStore.addAll(embeddings, segments);
         Embedding queryEmbedding = embeddingModel.embed(question).content();
         EmbeddingSearchRequest embeddingSearchRequest = EmbeddingSearchRequest.builder()
      * @return
      */
     public AssistantMessage generateAnswer(String prompt, String question, String templatePath, String llmServiceUrl) throws IOException {
-        ChatSession chatSession = new ChatSessionDefault();
         ChatModel chatModel = ChatModel.of(llmServiceUrl)
-                .provider("openai")
+                
                 .model("Qwen2.5-1.5B-Instruct")
                 .build();
 
-        chatSession.addMessage(ChatMessage.ofUser(prompt));
-
+        List<ChatMessage> messages = new ArrayList<>();
+        messages.add(ChatMessage.ofUser(prompt));
+        ChatSession chatSession =  InMemoryChatSession.builder().messages(messages).build();
         ChatResponse response = chatModel.prompt(chatSession).call();
         String content = response.lastChoice().getMessage().getContent() + "\n\n" +
-                "招标文件分析完成，章节内容已写入【<a href='" + templatePath + "'> 技术文件" + "</a>】，请查阅";
+                "招标文件分析完成，章节内容已写入【<a href='" + templatePath.replace(Solon.cfg().getProperty("cmc.profile"), "/dev-api/profile") + "'> 技术文件" + "</a>】，请查阅\n\n" +
+                "如需修改，请输入技术文件已有内容的章节标题\n\n" +
+                extractTitles(templatePath);
         String absolutePath = templatePath.replace("/dev-api/profile", Solon.cfg().getProperty("cmc.profile"));
         writeContent(response.lastChoice().getMessage().getContent(), question, absolutePath);
         return ChatMessage.ofAssistant(content);
      * @return
      */
     public void writeContent(String content, String question, String absolutePath) throws IOException {
+        String[] contentLines = content.split("\n");
+        Map<String, String> map = new HashMap<>();
+        String[] titles = question.split(",");
         File file = new File(absolutePath);
         FileInputStream fileInputStream = new FileInputStream(file);
         try (XWPFDocument document = new XWPFDocument(fileInputStream)) {
-            String[] contentLines = content.split("\n");
-            Map<String, String> map = new HashMap<>();
-            String[] titles = question.split(",");
-
             for (int i = 0; i < titles.length; i++) {
                 int startIndex = Arrays.asList(contentLines).indexOf(titles[i]);
                 StringBuilder text = new StringBuilder();
     public List<String> extractSubTitles(String filename, String question) throws IOException {
         List<String> subTitles = new ArrayList<>();
         boolean inTargetSection = false;
-        filename = Solon.cfg().getProperty("cmc.profile") + filename;
         InputStream fileInputStream = new FileInputStream(filename);
         try (XWPFDocument document = new XWPFDocument(fileInputStream)) {
             for (XWPFParagraph paragraph : document.getParagraphs()) {
         return subTitles;
     }
 
+    /**
+     * 获取二、三级标题列表
+     */
+    public String extractTitles(String filename) throws IOException {
+        StringBuilder subTitles = new StringBuilder();
+        InputStream fileInputStream = new FileInputStream(filename);
+        try (XWPFDocument document = new XWPFDocument(fileInputStream)) {
+            for (XWPFParagraph paragraph : document.getParagraphs()) {
+                String text = paragraph.getText().trim();
+                if (paragraph.getStyle() != null) {
+                    // 判断主标题
+                    if (paragraph.getStyle().equals("3") || paragraph.getStyle().equals("4") ) {
+                        subTitles.append(text).append("\n");
+                    }
+                }
+            }
+        }
+        return subTitles.toString();
+    }
+
     /**
      * 检索知识库
      */

llm-back/ruoyi-llm/pom.xml

         <dependency>
             <groupId>dev.langchain4j</groupId>
             <artifactId>langchain4j-milvus</artifactId>
-            <version>0.35.0</version> <!-- 版本需与核心一致 -->
+            <version>0.35.0</version>
         </dependency>
 
         <!-- LangChain4j embedding 集成 -->
         <dependency>
             <groupId>org.noear</groupId>
             <artifactId>solon-ai-mcp</artifactId>
-            <version>3.3.1</version>
-            <exclusions>
-                <exclusion>
-                    <groupId>org.slf4j</groupId>
-                    <artifactId>*</artifactId>
-                </exclusion>
-            </exclusions>
+            <version>3.4.3</version>
         </dependency>
 
     </dependencies>

llm-back/ruoyi-llm/src/main/java/com/ruoyi/web/llm/controller/CmcTopicController.java

             String[] chatIds = new String[cmcChatList.size()];
             for (int i = 0; i < cmcChatList.size(); i++)
                 chatIds[i] = cmcChatList.get(i).getChatId();
-            cmcChatService.deleteCmcChatByChatIds(chatIds);
+            if (chatIds.length > 0)
+                cmcChatService.deleteCmcChatByChatIds(chatIds);
             for (String chatId : chatIds) {
                 CmcDocument cmcDocument = new CmcDocument();
                 cmcDocument.setChatId(chatId);
                 String[] documentIds = new String[cmcDocumentList.size()];
                 for (int i = 0; i < cmcDocumentList.size(); i++)
                     documentIds[i] = cmcDocumentList.get(i).getDocumentId();
-                cmcDocumentService.deleteCmcDocumentByDocumentIds(documentIds);
+                if (documentIds.length > 0)
+                    cmcDocumentService.deleteCmcDocumentByDocumentIds(documentIds);
             }
         }
         return success(cmcTopicService.deleteCmcTopicByTopicIds(topicIds));

llm-back/ruoyi-llm/src/main/java/com/ruoyi/web/llm/controller/McpController.java

 import org.noear.solon.ai.chat.ChatModel;
 import org.noear.solon.ai.chat.ChatResponse;
 import org.noear.solon.ai.chat.ChatSession;
-import org.noear.solon.ai.chat.ChatSessionDefault;
 import org.noear.solon.ai.chat.message.AssistantMessage;
 import org.noear.solon.ai.chat.message.ChatMessage;
+import org.noear.solon.ai.chat.session.InMemoryChatSession;
 import org.noear.solon.ai.mcp.client.McpClientProvider;
 import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.web.bind.annotation.GetMapping;
 
     private static final EmbeddingModel embeddingModel = new BgeSmallZhV15EmbeddingModel();
 
+    private static final String llmServiceUrl = "http://192.168.28.188:8000/v1/chat/completions";
+
     private static final MilvusServiceClient milvusClient = new MilvusServiceClient(
             ConnectParam.newBuilder()
                     .withHost("192.168.28.188")
 //        McpClientProvider clientProvider = McpClientProvider.builder()
 //                .apiUrl("http://localhost:8080/llm/mcp/sse")
 //                .build();
-//        ChatModel chatModel = ChatModel.of("http://192.168.28.188:8000/v1/chat/completions")
-//                .provider("openai")
+//        ChatModel chatModel = ChatModel.of(llmServiceUrl)
 //                .model("Qwen2.5-1.5B-Instruct")
 //                .defaultToolsAdd(clientProvider)
 //                .build();
         McpClientProvider clientProvider = McpClientProvider.builder()
                 .apiUrl("http://localhost:8080/llm/mcp/sse")
                 .build();
-        ChatSession chatSession = new ChatSessionDefault(topicId);
-        ChatModel chatModel = ChatModel.of("http://192.168.28.188:8000/v1/chat/completions")
-                .provider("openai")
+        ChatModel chatModel = ChatModel.of(llmServiceUrl)
                 .model("Qwen2.5-1.5B-Instruct")
                 .defaultToolsAdd(clientProvider)
                 .build();
 
+        List<ChatMessage> messages = new ArrayList<>();
         CmcChat cmcChat = new CmcChat();
         cmcChat.setTopicId(topicId);
         List<CmcChat> cmcChatList = cmcChatService.selectCmcChatList(cmcChat);
         for (CmcChat chat : cmcChatList) {
-            chatSession.addMessage(ChatMessage.ofUser(chat.getInput()));
-            chatSession.addMessage(ChatMessage.ofAssistant(chat.getOutput()));
+            messages.add(ChatMessage.ofUser(chat.getInput()));
+            messages.add(ChatMessage.ofAssistant(chat.getOutput()));
         }
-
-        chatSession.addMessage(ChatMessage.ofUser(question));
+        messages.add(ChatMessage.ofUser(question));
+        ChatSession chatSession =  InMemoryChatSession.builder().messages(messages).build();
         ChatResponse response = chatModel.prompt(chatSession).call();
         String resultContent = response.lastChoice().getMessage().getResultContent();
         AssistantMessage assistantMessage;
     {
         question = String.join(",", langChainMilvusService.extractSubTitles(RuoYiConfig.getProfile() + "/upload/agent/template/technical.docx", question));
         List<JSONObject> requests = langChainMilvusService.retrieveFromMilvus(milvusClient, embeddingModel, collectionName, question, 10);
-        return langChainMilvusService.generateAnswerWithDocumentAndCollection(embeddingModel, topicId, question, requests, "http://192.168.28.188:8000/v1/chat/completions");
+        return langChainMilvusService.generateAnswerWithDocumentAndCollection(embeddingModel, topicId, question, requests, llmServiceUrl);
     }
 
     /**
         McpClientProvider clientProvider = McpClientProvider.builder()
                     .apiUrl("http://localhost:8080/llm/mcp/sse")
                     .build();
-        ChatModel chatModel = ChatModel.of("http://192.168.28.188:8000/v1/chat/completions")
-                .provider("openai")
+        ChatModel chatModel = ChatModel.of(llmServiceUrl)
+                
                 .model("DeepSeek-R1-Distill-Qwen-1.5B")
                 .defaultToolsAdd(clientProvider)
                 .build();

llm-back/ruoyi-llm/src/main/java/com/ruoyi/web/llm/service/impl/LangChainMilvusServiceImpl.java

 import org.noear.solon.ai.chat.ChatModel;
 import org.noear.solon.ai.chat.ChatResponse;
 import org.noear.solon.ai.chat.ChatSession;
-import org.noear.solon.ai.chat.ChatSessionDefault;
 import org.noear.solon.ai.chat.message.AssistantMessage;
 import org.noear.solon.ai.chat.message.ChatMessage;
+import org.noear.solon.ai.chat.session.InMemoryChatSession;
 import org.reactivestreams.Publisher;
 import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.stereotype.Service;
      */
     @Override
     public Flux<AssistantMessage> generateAnswer(String topicId, String prompt, String llmServiceUrl) {
-        ChatSession chatSession = new ChatSessionDefault(topicId);
         ChatModel chatModel = ChatModel.of(llmServiceUrl)
-                .provider("openai")
+                
                 .model("Qwen2.5-1.5B-Instruct")
                 .build();
 
+        List<ChatMessage> messages = new ArrayList<>();
         if (topicId != null) {
             CmcChat cmcChat = new CmcChat();
             cmcChat.setTopicId(topicId);
             List<CmcChat> cmcChatList = cmcChatService.selectCmcChatList(cmcChat);
             for (CmcChat chat : cmcChatList) {
-                chatSession.addMessage(ChatMessage.ofUser(chat.getInput()));
-                chatSession.addMessage(ChatMessage.ofAssistant(chat.getOutput()));
+                messages.add(ChatMessage.ofUser(chat.getInput()));
+                messages.add(ChatMessage.ofAssistant(chat.getOutput()));
             }
         }
-        chatSession.addMessage(ChatMessage.ofUser(prompt));
-
+        messages.add(ChatMessage.ofUser(prompt));
+        ChatSession chatSession =  InMemoryChatSession.builder().messages(messages).build();
         Publisher<ChatResponse> publisher = chatModel.prompt(chatSession).stream();
         return Flux.from(publisher)
                 .map(response -> {
         StringBuilder sb = new StringBuilder("问题: " + question + "\n\n").append("根据以下上下文回答问题：\n\n");
         for (CmcDocument document : documentList) {
             File profilePath = new File(RuoYiConfig.getProfile() + document.getPath());
+            InMemoryEmbeddingStore<TextSegment> embeddingStore = new InMemoryEmbeddingStore<>();
             List<TextSegment> segments = splitDocument(profilePath);
             List<Embedding> embeddings = embeddingModel.embedAll(segments).content();
-            InMemoryEmbeddingStore<TextSegment> embeddingStore = new InMemoryEmbeddingStore<>();
             embeddingStore.addAll(embeddings, segments);
             Embedding queryEmbedding = embeddingModel.embed(question).content();
             EmbeddingSearchRequest embeddingSearchRequest = EmbeddingSearchRequest.builder()
             if (documentList.size() == 1) {
                 for (CmcDocument document : documentList) {
                     File profilePath = new File(RuoYiConfig.getProfile() + document.getPath());
+                    InMemoryEmbeddingStore<TextSegment> embeddingStore = new InMemoryEmbeddingStore<>();
                     List<TextSegment> segments = splitDocument(profilePath);
                     List<Embedding> embeddings = embeddingModel.embedAll(segments).content();
-                    InMemoryEmbeddingStore<TextSegment> embeddingStore = new InMemoryEmbeddingStore<>();
                     embeddingStore.addAll(embeddings, segments);
                     Embedding queryEmbedding = embeddingModel.embed(question).content();
                     EmbeddingSearchRequest embeddingSearchRequest = EmbeddingSearchRequest.builder()
                             .queryEmbedding(queryEmbedding)
-                            .maxResults(3)
+                            .minScore(0.7)
                             .build();
-                    for (EmbeddingMatch embeddingMatch : embeddingStore.search(embeddingSearchRequest).matches()) {
+                    List<EmbeddingMatch<TextSegment>> results = embeddingStore.search(embeddingSearchRequest).matches();
+                    results.sort(Comparator.comparingDouble(EmbeddingMatch<TextSegment>::score).reversed());
+                    for (EmbeddingMatch<TextSegment> embeddingMatch : results) {
                         String requests = embeddingMatch.embedded().toString();
                         sb.append(requests).append("\n\n");
                     }
     /**
      * 检索知识库
      */
-    private List<TextSegment> splitDocument(File transferFile) throws IOException {
+    private List<TextSegment> splitDocument(File transferFile) throws FileNotFoundException {
         // 加载文档
         Document document;
         InputStream fileInputStream = new FileInputStream(transferFile);

llm-back/ruoyi-system/pom.xml

             <groupId>dev.langchain4j</groupId>
             <artifactId>langchain4j-document-parser-apache-pdfbox</artifactId>
             <version>0.35.0</version>
-            <scope>compile</scope>
         </dependency>
 
         <dependency>
             <groupId>dev.langchain4j</groupId>
             <artifactId>langchain4j-embeddings-bge-small-zh-v15</artifactId>
             <version>0.35.0</version>
-            <scope>compile</scope>
         </dependency>
 
         <dependency>
             <groupId>org.noear</groupId>
-            <artifactId>solon-ai-mcp</artifactId>
-            <version>3.3.1</version>
-            <exclusions>
-                <exclusion>
-                    <groupId>org.slf4j</groupId>
-                    <artifactId>*</artifactId>
-                </exclusion>
-            </exclusions>
+            <artifactId>solon-ai</artifactId>
+            <version>3.4.3</version>
+        </dependency>
+
+        <dependency>
+            <groupId>io.milvus</groupId>
+            <artifactId>milvus-sdk-java</artifactId>
+            <version>2.3.3</version>
         </dependency>
 
     </dependencies>

llm-back/ruoyi-system/src/main/java/com/ruoyi/llm/service/impl/CmcAgentServiceImpl.java

 
 import java.io.*;
 import java.util.*;
+import java.util.stream.Collectors;
 
 import com.alibaba.fastjson2.JSONObject;
 import com.ruoyi.common.config.RuoYiConfig;
 import dev.langchain4j.store.embedding.EmbeddingMatch;
 import dev.langchain4j.store.embedding.EmbeddingSearchRequest;
 import dev.langchain4j.store.embedding.inmemory.InMemoryEmbeddingStore;
+import io.milvus.client.MilvusServiceClient;
+import io.milvus.grpc.SearchResults;
+import io.milvus.param.ConnectParam;
+import io.milvus.param.MetricType;
+import io.milvus.param.R;
+import io.milvus.param.RpcStatus;
+import io.milvus.param.collection.LoadCollectionParam;
+import io.milvus.param.collection.ReleaseCollectionParam;
+import io.milvus.param.dml.SearchParam;
+import io.milvus.response.SearchResultsWrapper;
 import org.apache.poi.extractor.ExtractorFactory;
 import org.apache.poi.extractor.POITextExtractor;
 import org.apache.poi.xwpf.usermodel.BreakType;
 import org.noear.solon.ai.chat.ChatModel;
 import org.noear.solon.ai.chat.ChatResponse;
 import org.noear.solon.ai.chat.ChatSession;
-import org.noear.solon.ai.chat.ChatSessionDefault;
 import org.noear.solon.ai.chat.message.ChatMessage;
+import org.noear.solon.ai.chat.session.InMemoryChatSession;
 import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.stereotype.Service;
 import com.ruoyi.llm.mapper.CmcAgentMapper;
 
     private static final String llmServiceUrl = "http://192.168.28.188:8000/v1/chat/completions";
 
+    private static final MilvusServiceClient milvusClient = new MilvusServiceClient(
+            ConnectParam.newBuilder()
+                    .withHost("192.168.28.188")
+                    .withPort(19530)
+                    .build());
+
     /**
      * 查询智能体
      * 
                     doc.write(out);
                 }
             }
-            String chapters = generateAnswerWithDocument(embeddingModel, profilePath + "/" + file.getOriginalFilename(),
-                    RuoYiConfig.getProfile() + outputFilename, "工作大纲", llmServiceUrl);
+            String chapters = generateAnswerWithDocument(profilePath + "/" + file.getOriginalFilename(),
+                    RuoYiConfig.getProfile() + outputFilename, "工作大纲");
             message = "好的，我已经收到您上传的招标文件，我将给您提供技术文件模板，您可点击进行预览：" +
                     "【<a href='/profile" + outputFilename + "'> 模版 " + "</a>】\n\n" +
                     chapters + "\n\n" +
     /**
      * 调用LLM生成回答
      */
-    public String generateAnswerWithDocument(EmbeddingModel embeddingModel, String uploadFilePath, String templatePath, String question, String llmServiceUrl) throws IOException {
+    public String generateAnswerWithDocument(String uploadFilePath, String templatePath, String question) throws IOException {
         StringBuilder sb = new StringBuilder("招标文件内容：\n\n");
         File profilePath = new File(uploadFilePath);
+        InMemoryEmbeddingStore<TextSegment> embeddingStore = new InMemoryEmbeddingStore<>();
         List<TextSegment> segments = splitDocument(profilePath);
         List<Embedding> embeddings = embeddingModel.embedAll(segments).content();
-        InMemoryEmbeddingStore<TextSegment> embeddingStore = new InMemoryEmbeddingStore<>();
         embeddingStore.addAll(embeddings, segments);
         Embedding queryEmbedding = embeddingModel.embed(question).content();
         EmbeddingSearchRequest embeddingSearchRequest = EmbeddingSearchRequest.builder()
                 .append("6.1 XX\n" +
                 "6.2 XX\n" +
                 "6.3 XX");
-        return generateAnswer(sb.toString(), question, templatePath, llmServiceUrl);
+        return writeChapters(sb.toString(), templatePath);
+    }
+
+    /**
+     * 编排章节
+     * @return
+     */
+    public String writeChapters(String prompt, String templatePath) throws IOException {
+        String chapter2 = generateAnswer(prompt);
+
+        StringBuilder sb = new StringBuilder("二级标题如下：\n" + chapter2 + "\n 请根据参考内容编排三级标题，严格按以下格式列出")
+                .append(":\n").append("6.1.1 XX\n" +
+                        "6.1.2 XX\n" +
+                        "6.1.3 XX");
+        List<JSONObject> contexts = retrieveFromMilvus("technical", chapter2, 10);
+        for (JSONObject context : contexts) {
+            sb.append("参考内容").append(": ")
+                    .append(context.getString("content")).append("\n\n");
+        }
+        String chapter3 = generateAnswer(sb.toString());
+        sb = new StringBuilder("二级标题如下：\n" + chapter2 + "\n 三级标题如下：" + chapter3 + "帮我合并二三级标题，严格按以下格式列出")
+                .append(":\n").append("6.1 XX\n" +
+                        "6.1.1 XX\n" +
+                        "6.1.2 XX\n"+
+                        "6.2 XX\n" +
+                        "6.3 XX");
+        String content = generateAnswer(sb.toString());
+        writeContent(content, templatePath);
+        return content;
     }
 
     /**
      * 调用LLM生成回答
      * @return
      */
-    public String generateAnswer(String prompt, String question, String templatePath, String llmServiceUrl) throws IOException {
-        ChatSession chatSession = new ChatSessionDefault();
-        ChatModel chatModel = ChatModel.of(llmServiceUrl)
-                .provider("openai")
-                .model("Qwen2.5-1.5B-Instruct")
+    public String generateAnswer(String prompt) throws IOException {
+        ChatModel chatModel = ChatModel.of(llmServiceUrl).model("Qwen2.5-1.5B-Instruct").build();
+
+        List<ChatMessage> messages = new ArrayList<>();
+        messages.add(ChatMessage.ofUser(prompt));
+        ChatSession chatSession =  InMemoryChatSession.builder().messages(messages).build();
+        ChatResponse response = chatModel.prompt(chatSession).call();
+
+        return response.lastChoice().getMessage().getContent();
+    }
+
+    /**
+     * 从Milvus检索相关文档
+     * @return
+     */
+    public List<JSONObject> retrieveFromMilvus(String collectionName, String query, int topK) {
+        SearchResultsWrapper wrapper = retrieve(collectionName, query, topK);
+        return wrapper.getRowRecords(0).stream()
+                .map(record -> {
+                    JSONObject result = new JSONObject();
+                    result.put("content", record.get("content"));
+                    return result;
+                })
+                .collect(Collectors.toList());
+    }
+
+    /**
+     * 检索知识库
+     */
+    private SearchResultsWrapper retrieve(String collectionName, String query, int topK) {
+        List<List<Float>> queryVector = Collections.singletonList(embeddingModel.embed(query).content().vectorAsList());
+
+        //  加载集合
+        LoadCollectionParam loadParam = LoadCollectionParam.newBuilder()
+                .withCollectionName(collectionName)
                 .build();
 
-        chatSession.addMessage(ChatMessage.ofUser(prompt));
+        R<RpcStatus> loadResponse = milvusClient.loadCollection(loadParam);
+        if (loadResponse.getStatus() != R.Status.Success.getCode()) {
+            System.err.println("加载Collection失败: " + loadResponse.getMessage());
+            milvusClient.close();
+        }
 
-        ChatResponse response = chatModel.prompt(chatSession).call();
-        String content = response.lastChoice().getMessage().getContent();
-        writeContent(content, templatePath);
-        return content;
+        // 构建SearchParam
+        SearchParam searchParam = SearchParam.newBuilder()
+                .withCollectionName(collectionName)
+                .withVectors(queryVector)
+                .withTopK(topK)
+                .withOutFields(Arrays.asList("content"))
+                .withVectorFieldName("embedding")
+                .withMetricType(MetricType.COSINE)
+                .withParams("{\"nprobe\": 8}")
+                .build();
+
+        R<SearchResults> response = milvusClient.search(searchParam);
+        SearchResultsWrapper wrapper = new SearchResultsWrapper(response.getData().getResults());
+
+        // 释放集合
+        ReleaseCollectionParam param = ReleaseCollectionParam.newBuilder()
+                .withCollectionName(collectionName)
+                .build();
+        milvusClient.releaseCollection(param);
+
+        return wrapper;
     }
 
     /**
         String[] contentLines = content.split("\n");
         for (String line : contentLines) {
             if (line.contains("6."))
-                chapters.add(line.replace("*", "").replace("#", "").split(" ")[1]);
+                chapters.add(line.replace("*", "").replace("#", "").replace("-", ""));
         }
         File file = new File(templatePath);
         FileInputStream fileInputStream = new FileInputStream(file);
         try (XWPFDocument document = new XWPFDocument(fileInputStream)) {
-            for (int i = 0; i < chapters.size(); i++) {
-                XWPFParagraph contentParagraph = document.createParagraph();
-                contentParagraph.setStyle("3");
-                XWPFRun run = contentParagraph.createRun();
-                run.setText(chapters.get(i));
-                run.addBreak();
-                if (i < chapters.size() - 1)
-                    run.addBreak(BreakType.PAGE);
-            }
+           for (int i = 0; i < chapters.size(); i++) {
+               XWPFParagraph contentParagraph = document.createParagraph();
+               contentParagraph.setStyle("3");
+               boolean title2 = chapters.get(i).indexOf(".") == chapters.get(i).lastIndexOf(".");
+               if (!title2)
+                   contentParagraph.setStyle("4");
+
+               XWPFRun run = contentParagraph.createRun();
+               if (chapters.get(i).contains(" "))
+                   run.setText(chapters.get(i).split(" ")[1]);
+               run.addBreak();
+               if (i < chapters.size() - 1 && chapters.get(i + 1).indexOf(".") == chapters.get(i + 1).lastIndexOf("."))
+                   run.addBreak(BreakType.PAGE);
+           }
 
             try (FileOutputStream out = new FileOutputStream(templatePath)) {
                 document.write(out);