新增千问3重排序模型，并附带新增sql文件

docs/script/sql/update/updat-0420.sql

@@ -0,0 +1,46 @@
+/*
+ Navicat Premium Dump SQL
+
+ Source Server         : localhost-mysql
+ Source Server Type    : MySQL
+ Source Server Version : 80045 (8.0.45)
+ Source Host           : localhost:3306
+ Source Schema         : ruoyi-ai
+
+ Target Server Type    : MySQL
+ Target Server Version : 80045 (8.0.45)
+ File Encoding         : 65001
+
+ Date: 20/04/2026 15:30:00
+*/
+
+SET NAMES utf8mb4;
+SET FOREIGN_KEY_CHECKS = 0;
+
+-- ----------------------------
+-- 新增：重排序模型（chat_model）
+-- ----------------------------
+INSERT INTO `chat_model`
+(id, category, model_name, provider_code, model_describe, model_dimension, model_show, api_host, api_key, create_dept, create_by, create_time, update_by, update_time, remark, tenant_id)
+VALUES(2045071617578237953, 'rerank', 'rerank', 'zhipu', '智谱重排序', NULL, 'Y', 'https://open.bigmodel.cn', 'e9xx', 103, 1, '2026-04-17 17:27:24', 1, '2026-04-20 15:21:48', '智谱重排序', 0);
+
+INSERT INTO `chat_model`
+(id, category, model_name, provider_code, model_describe, model_dimension, model_show, api_host, api_key, create_dept, create_by, create_time, update_by, update_time, remark, tenant_id)
+VALUES(2046119803482902530, 'rerank', 'qwen3-rerank', 'qianwen', '千问3重排序', NULL, NULL, 'https://dashscope.aliyuncs.com', 'sk-xx', 103, 1, '2026-04-20 14:52:31', 1, '2026-04-20 15:03:13', '千问3文本重排序', 0);
+
+-- ----------------------------
+-- 新增：字典类型 - 重排序模型分类
+-- ----------------------------
+INSERT INTO `sys_dict_data`
+(dict_code, tenant_id, dict_sort, dict_label, dict_value, dict_type, css_class, list_class, is_default, create_dept, create_by, create_time, update_by, update_time, remark)
+VALUES(2045070879435259905, '000000', 4, '重排序', 'rerank', 'chat_model_category', NULL, '#000000', 'N', 103, 1, '2026-04-17 17:24:28', 1, '2026-04-19 01:02:20', '重排序模型');
+
+-- ----------------------------
+-- 修改表：knowledge_info 增加重排序相关字段
+-- ----------------------------
+ALTER TABLE `knowledge_info` ADD COLUMN `enable_rerank` tinyint DEFAULT 0 NULL COMMENT '是否启用重排序（0否 1是）';
+ALTER TABLE `knowledge_info` ADD COLUMN `rerank_score_threshold` double NULL COMMENT '重排序相关性分数阈值';
+ALTER TABLE `knowledge_info` ADD COLUMN `rerank_top_n` int NULL COMMENT '重排序后返回的文档数量';
+ALTER TABLE `knowledge_info` ADD COLUMN `rerank_model` varchar(100) NULL COMMENT '重排序模型名称';
+
+SET FOREIGN_KEY_CHECKS = 1;

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/domain/dto/request/AliBaiLianRerankRequest.java

@@ -0,0 +1,55 @@
+package org.ruoyi.domain.dto.request;
+
+import com.fasterxml.jackson.annotation.JsonInclude;
+import com.fasterxml.jackson.annotation.JsonProperty;
+import com.fasterxml.jackson.core.JsonProcessingException;
+import com.fasterxml.jackson.databind.ObjectMapper;
+
+import java.util.List;
+
+/**
+ * 阿里百炼重排序请求DTO（OpenAI兼容格式）
+ *
+ * @author yang
+ * @date 2026-04-20
+ */
+@JsonInclude(JsonInclude.Include.NON_NULL)
+public record AliBaiLianRerankRequest(
+        String model,
+        List<String> documents,
+        String query,
+        @JsonProperty("top_n")
+        Integer topN,
+        String instruct,
+        @JsonProperty("return_documents")
+        Boolean returnDocuments
+) {
+    private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
+
+    /**
+     * 创建文本重排序请求
+     */
+    public static AliBaiLianRerankRequest create(String modelName, String query,
+                                                  List<String> documents, Integer topN,
+                                                  Boolean returnDocuments) {
+        return new AliBaiLianRerankRequest(
+                modelName,
+                documents,
+                query,
+                topN != null ? topN : documents.size(),
+                null,
+                returnDocuments != null ? returnDocuments : true
+        );
+    }
+
+    /**
+     * 转换为JSON字符串
+     */
+    public String toJson() {
+        try {
+            return OBJECT_MAPPER.writeValueAsString(this);
+        } catch (JsonProcessingException e) {
+            throw new IllegalArgumentException("序列化阿里百炼重排序请求失败", e);
+        }
+    }
+}

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/domain/dto/response/AliBaiLianRerankResponse.java

@@ -0,0 +1,81 @@
+package org.ruoyi.domain.dto.response;
+
+import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
+import com.fasterxml.jackson.annotation.JsonProperty;
+import org.ruoyi.domain.bo.rerank.RerankResult;
+
+import java.util.List;
+import java.util.Map;
+import java.util.stream.Collectors;
+
+/**
+ * 阿里百炼重排序响应DTO（OpenAI兼容格式）
+ *
+ * @author yang
+ * @date 2026-04-20
+ */
+@JsonIgnoreProperties(ignoreUnknown = true)
+public record AliBaiLianRerankResponse(
+        String id,
+        String object,
+        List<ResultItem> results,
+        UsageInfo usage
+) {
+    /**
+     * 单个重排序结果项
+     */
+    @JsonIgnoreProperties(ignoreUnknown = true)
+    public record ResultItem(
+            Integer index,
+            @JsonProperty("relevance_score")
+            Double relevanceScore,
+            Object document
+    ) {
+        /**
+         * 获取文档文本内容
+         */
+        public String getDocumentText() {
+            if (document == null) return null;
+            if (document instanceof String) return (String) document;
+            if (document instanceof Map) {
+                Object text = ((Map<?, ?>) document).get("text");
+                return text != null ? text.toString() : null;
+            }
+            return document.toString();
+        }
+    }
+
+    /**
+     * Token使用信息
+     */
+    @JsonIgnoreProperties(ignoreUnknown = true)
+    public record UsageInfo(
+            @JsonProperty("total_tokens")
+            Integer totalTokens,
+            @JsonProperty("prompt_tokens")
+            Integer promptTokens
+    ) {}
+
+    /**
+     * 转换为通用RerankResult
+     */
+    public RerankResult toRerankResult(int totalDocs, long durationMs) {
+        if (results == null || results.isEmpty()) {
+            return RerankResult.empty();
+        }
+
+        List<RerankResult.RerankDocument> documents = results.stream()
+                .map(item -> RerankResult.RerankDocument.builder()
+                        .index(item.index())
+                        .relevanceScore(item.relevanceScore())
+                        .document(item.getDocumentText())
+                        .build())
+                .collect(Collectors.toList());
+
+        return RerankResult.builder()
+                .documents(documents)
+                .totalDocuments(totalDocs)
+                .durationMs(durationMs)
+                .build();
+    }
+}

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/domain/dto/response/ZhipuRerankResponse.java

@@ -1,5 +1,6 @@
 package org.ruoyi.domain.dto.response;
 
+import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
 import com.fasterxml.jackson.annotation.JsonProperty;
 import org.ruoyi.domain.bo.rerank.RerankResult;
 
@@ -12,6 +13,7 @@ import java.util.stream.Collectors;
  * @author yang
  * @date 2026-04-19
  */
+@JsonIgnoreProperties(ignoreUnknown = true)
 public record ZhipuRerankResponse(
         String model,
         String object,
@@ -31,6 +33,7 @@ public record ZhipuRerankResponse(
     /**
      * Token使用信息
      */
+    @JsonIgnoreProperties(ignoreUnknown = true)
     public record UsageInfo(
             @JsonProperty("total_tokens")
             Integer totalTokens,

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/rerank/impl/AliBaiLianRerankModelService.java

@@ -0,0 +1,115 @@
+package org.ruoyi.service.rerank.impl;
+
+import com.fasterxml.jackson.databind.ObjectMapper;
+import lombok.extern.slf4j.Slf4j;
+import okhttp3.*;
+import org.ruoyi.common.chat.domain.vo.chat.ChatModelVo;
+import org.ruoyi.domain.bo.rerank.RerankRequest;
+import org.ruoyi.domain.bo.rerank.RerankResult;
+import org.ruoyi.domain.dto.request.AliBaiLianRerankRequest;
+import org.ruoyi.domain.dto.response.AliBaiLianRerankResponse;
+import org.ruoyi.service.rerank.RerankModelService;
+import org.springframework.stereotype.Component;
+
+import java.io.IOException;
+import java.util.concurrent.TimeUnit;
+
+/**
+ * 阿里百炼重排序模型实现
+ * 参考设计模式：AliBaiLianMultiEmbeddingProvider
+ *
+ * @author yang
+ * @date 2026-04-20
+ */
+@Slf4j
+@Component("qianwenRerank")
+public class AliBaiLianRerankModelService implements RerankModelService {
+
+    private final OkHttpClient okHttpClient;
+    private final ObjectMapper objectMapper = new ObjectMapper();
+    private ChatModelVo chatModelVo;
+
+    public AliBaiLianRerankModelService() {
+        this.okHttpClient = new OkHttpClient.Builder()
+                .connectTimeout(30, TimeUnit.SECONDS)
+                .readTimeout(60, TimeUnit.SECONDS)
+                .writeTimeout(30, TimeUnit.SECONDS)
+                .build();
+    }
+
+    @Override
+    public void configure(ChatModelVo config) {
+        this.chatModelVo = config;
+    }
+
+    @Override
+    public RerankResult rerank(RerankRequest rerankRequest) {
+        long startTime = System.currentTimeMillis();
+
+        try {
+            // 构建请求
+            AliBaiLianRerankRequest request = buildRequest(rerankRequest);
+            AliBaiLianRerankResponse response = executeRequest(request);
+
+            return response.toRerankResult(
+                    rerankRequest.getDocuments().size(),
+                    System.currentTimeMillis() - startTime
+            );
+
+        } catch (Exception e) {
+            log.error("阿里百炼重排序失败: {}", e.getMessage(), e);
+            throw new RuntimeException("重排序服务调用失败: " + e.getMessage(), e);
+        }
+    }
+
+    /**
+     * 构建请求对象
+     */
+    private AliBaiLianRerankRequest buildRequest(RerankRequest rerankRequest) {
+        return AliBaiLianRerankRequest.create(
+                chatModelVo.getModelName(),
+                rerankRequest.getQuery(),
+                rerankRequest.getDocuments(),
+                rerankRequest.getTopN(),
+                rerankRequest.getReturnDocuments()
+        );
+    }
+
+    /**
+     * 执行HTTP请求并解析响应
+     */
+    private AliBaiLianRerankResponse executeRequest(AliBaiLianRerankRequest request) throws IOException {
+        String jsonBody = request.toJson();
+        RequestBody body = RequestBody.create(jsonBody, MediaType.get("application/json"));
+
+        // 阿里百炼重排序 OpenAI兼容端点
+        String url = chatModelVo.getApiHost() + "/compatible-api/v1/reranks";
+        Request httpRequest = new Request.Builder()
+                .url(url)
+                .addHeader("Authorization", "Bearer " + chatModelVo.getApiKey())
+                .addHeader("Content-Type", "application/json")
+                .post(body)
+                .build();
+
+        try (Response response = okHttpClient.newCall(httpRequest).execute()) {
+            if (!response.isSuccessful()) {
+                String err = response.body() != null ? response.body().string() : "无错误信息";
+                throw new IllegalArgumentException("阿里百炼API调用失败: " + response.code() + " - " + err);
+            }
+
+            ResponseBody responseBody = response.body();
+            if (responseBody == null) {
+                throw new IllegalArgumentException("响应体为空");
+            }
+
+            return parseResponse(responseBody.string());
+        }
+    }
+
+    /**
+     * 解析响应
+     */
+    private AliBaiLianRerankResponse parseResponse(String responseBody) throws IOException {
+        return objectMapper.readValue(responseBody, AliBaiLianRerankResponse.class);
+    }
+}

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/rerank/impl/JinaRerankModelService.java

@@ -1,107 +0,0 @@
-package org.ruoyi.service.rerank.impl;
-
-import com.fasterxml.jackson.databind.ObjectMapper;
-import dev.langchain4j.http.client.*;
-import lombok.extern.slf4j.Slf4j;
-import org.ruoyi.common.chat.domain.vo.chat.ChatModelVo;
-import org.ruoyi.domain.bo.rerank.RerankRequest;
-import org.ruoyi.domain.bo.rerank.RerankResult;
-import org.ruoyi.service.rerank.RerankModelService;
-import org.springframework.stereotype.Component;
-
-import java.util.ArrayList;
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
-
-/**
- * Jina AI 重排序模型实现
- * 参考设计模式：OpenAiEmbeddingProvider
- * 使用 Jina 官方重排序API
- *
- * @author yang
- * @date 2026-04-19
- */
-@Slf4j
-@Component("jina")
-public class JinaRerankModelService implements RerankModelService {
-
-    protected ChatModelVo chatModelVo;
-    protected HttpClient httpClient;
-    protected final ObjectMapper objectMapper = new ObjectMapper();
-
-    @Override
-    public void configure(ChatModelVo config) {
-        this.chatModelVo = config;
-        HttpClientBuilder httpClientBuilder = HttpClientBuilderLoader.loadHttpClientBuilder();
-        this.httpClient = httpClientBuilder.build();
-    }
-
-    @Override
-    public RerankResult rerank(RerankRequest rerankRequest) {
-        long startTime = System.currentTimeMillis();
-
-        try {
-            // 构建Jina重排序请求体
-            Map<String, Object> requestBody = new HashMap<>();
-            requestBody.put("model", chatModelVo.getModelName());
-            requestBody.put("query", rerankRequest.getQuery());
-            requestBody.put("documents", rerankRequest.getDocuments());
-            requestBody.put("top_n", rerankRequest.getTopN() != null ?
-                    rerankRequest.getTopN() : rerankRequest.getDocuments().size());
-            requestBody.put("return_documents", rerankRequest.getReturnDocuments());
-
-            // 构建HTTP请求
-            HttpRequest httpRequest = HttpRequest.builder()
-                    .url(chatModelVo.getApiHost())
-                    .method(HttpMethod.POST)
-                    .addHeader("Content-Type", "application/json")
-                    .addHeader("Authorization", "Bearer " + chatModelVo.getApiKey())
-                    .body(objectMapper.writeValueAsString(requestBody))
-                    .build();
-
-            // 发送请求
-            SuccessfulHttpResponse httpResponse = httpClient.execute(httpRequest);
-
-            // 解析响应
-            @SuppressWarnings("unchecked")
-            Map<String, Object> response = objectMapper.readValue(httpResponse.body(), Map.class);
-            return parseResponse(response, rerankRequest.getDocuments().size(),
-                    System.currentTimeMillis() - startTime);
-
-        } catch (Exception e) {
-            log.error("Jina重排序失败: {}", e.getMessage(), e);
-            throw new RuntimeException("重排序服务调用失败: " + e.getMessage(), e);
-        }
-    }
-
-    /**
-     * 解析Jina API响应
-     */
-    @SuppressWarnings("unchecked")
-    private RerankResult parseResponse(Map<String, Object> response, int totalDocs, long durationMs) {
-        List<Map<String, Object>> results = (List<Map<String, Object>>) response.get("results");
-        if (results == null || results.isEmpty()) {
-            return RerankResult.empty();
-        }
-
-        List<RerankResult.RerankDocument> documents = new ArrayList<>();
-        for (Map<String, Object> result : results) {
-            Integer index = (Integer) result.get("index");
-            Double score = ((Number) result.get("relevance_score")).doubleValue();
-            String document = (String) result.get("document");
-
-            documents.add(RerankResult.RerankDocument.builder()
-                    .index(index)
-                    .relevanceScore(score)
-                    .document(document)
-                    .build());
-        }
-
-        return RerankResult.builder()
-                .documents(documents)
-                .totalDocuments(totalDocs)
-                .durationMs(durationMs)
-                .build();
-    }
-}

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/rerank/impl/ZhiPuRerankModelService.java

@@ -90,14 +90,15 @@ public class ZhiPuRerankModelService implements RerankModelService {
         // 生成智谱认证Token
         String token = generateToken(chatModelVo.getApiKey());
 
-        String url = chatModelVo.getApiHost() + "/" + chatModelVo.getModelName();
+        // 智谱重排序固定端点路径
+        String url = chatModelVo.getApiHost() + "/api/paas/v4/rerank";
         Request httpRequest = new Request.Builder()
                 .url(url)
                 .addHeader("Authorization", token)
                 .post(body)
                 .build();
 
-        try (okhttp3.Response response = okHttpClient.newCall(httpRequest).execute()) {
+        try (Response response = okHttpClient.newCall(httpRequest).execute()) {
             if (!response.isSuccessful()) {
                 String err = response.body() != null ? response.body().string() : "无错误信息";
                 throw new IllegalArgumentException("智谱API调用失败: " + response.code() + " - " + err);

ruoyi-modules/ruoyi-chat/src/test/java/org/ruoyi/service/rerank/impl/AliBaiLianRerankModelServiceTest.java

@@ -0,0 +1,126 @@
+package org.ruoyi.service.rerank.impl;
+
+import org.junit.jupiter.api.BeforeEach;
+import org.junit.jupiter.api.Test;
+import org.ruoyi.common.chat.domain.vo.chat.ChatModelVo;
+import org.ruoyi.domain.bo.rerank.RerankRequest;
+import org.ruoyi.domain.bo.rerank.RerankResult;
+
+import java.util.Arrays;
+import java.util.List;
+
+import static org.junit.jupiter.api.Assertions.*;
+
+/**
+ * 阿里百炼重排序模型测试类
+ * 运行前请设置环境变量 DASHSCOPE_API_KEY 或直接修改 apiKey
+ */
+class AliBaiLianRerankModelServiceTest {
+
+    private AliBaiLianRerankModelService service;
+
+    // 请替换为你的 API Key
+    private static final String API_KEY = System.getenv("DASHSCOPE_API_KEY");
+    private static final String API_HOST = "https://dashscope.aliyuncs.com";
+    private static final String MODEL_NAME = "qwen3-rerank";
+
+    @BeforeEach
+    void setUp() {
+        service = new AliBaiLianRerankModelService();
+    }
+
+    @Test
+    void testConfigure() {
+        ChatModelVo config = createConfig();
+        service.configure(config);
+        assertNotNull(service);
+    }
+
+    @Test
+    void testRerank() {
+        // 跳过测试如果没有配置 API Key
+        if (API_KEY == null || API_KEY.isEmpty()) {
+            System.out.println("跳过测试: 未设置环境变量 DASHSCOPE_API_KEY");
+            return;
+        }
+
+        ChatModelVo config = createConfig();
+        service.configure(config);
+
+        List<String> documents = Arrays.asList(
+                "文本排序模型广泛用于搜索引擎和推荐系统中，它们根据文本相关性对候选文本进行排序",
+                "量子计算是计算科学的一个前沿领域",
+                "预训练语言模型的发展给文本排序模型带来了新的进展"
+        );
+
+        RerankRequest request = RerankRequest.builder()
+                .query("什么是文本排序模型")
+                .documents(documents)
+                .topN(2)
+                .returnDocuments(true)
+                .build();
+
+        RerankResult result = service.rerank(request);
+
+        System.out.println("=== 重排序结果 ===");
+        System.out.println("总文档数: " + result.getTotalDocuments());
+        System.out.println("耗时: " + result.getDurationMs() + "ms");
+
+        result.getDocuments().forEach(doc -> {
+            System.out.println("索引: " + doc.getIndex() +
+                    ", 相关性分数: " + doc.getRelevanceScore() +
+                    ", 文档: " + doc.getDocument());
+        });
+
+        assertNotNull(result);
+        assertNotNull(result.getDocuments());
+        assertFalse(result.getDocuments().isEmpty());
+        assertEquals(2, result.getDocuments().size());
+    }
+
+    @Test
+    void testRerankWithFullDocuments() {
+        if (API_KEY == null || API_KEY.isEmpty()) {
+            System.out.println("跳过测试: 未设置环境变量 DASHSCOPE_API_KEY");
+            return;
+        }
+
+        ChatModelVo config = createConfig();
+        service.configure(config);
+
+        List<String> documents = Arrays.asList(
+                "Java是一种广泛使用的编程语言",
+                "Python是人工智能领域最流行的语言",
+                "Go语言由Google开发，适合并发编程"
+        );
+
+        RerankRequest request = RerankRequest.builder()
+                .query("哪种语言适合AI开发")
+                .documents(documents)
+                .build();
+
+        RerankResult result = service.rerank(request);
+
+        System.out.println("=== 重排序结果2 ===");
+        result.getDocuments().forEach(doc -> {
+            System.out.println("索引: " + doc.getIndex() +
+                    ", 分数: " + doc.getRelevanceScore() +
+                    ", 文档: " + doc.getDocument());
+        });
+
+        assertNotNull(result);
+        assertEquals(3, result.getDocuments().size());
+
+        // Python相关文档应该排在前面
+        assertEquals(1, result.getDocuments().get(0).getIndex());
+        assertTrue(result.getDocuments().get(0).getRelevanceScore() > 0.5);
+    }
+
+    private ChatModelVo createConfig() {
+        ChatModelVo config = new ChatModelVo();
+        config.setApiHost(API_HOST);
+        config.setApiKey(API_KEY != null ? API_KEY : "test-api-key");
+        config.setModelName(MODEL_NAME);
+        return config;
+    }
+}

ruoyi-modules/ruoyi-chat/src/test/java/org/ruoyi/service/rerank/impl/AliBaiLianRerankTestMain.java

@@ -0,0 +1,73 @@
+package org.ruoyi.service.rerank.impl;
+
+import org.ruoyi.common.chat.domain.vo.chat.ChatModelVo;
+import org.ruoyi.domain.bo.rerank.RerankRequest;
+import org.ruoyi.domain.bo.rerank.RerankResult;
+
+import java.util.Arrays;
+import java.util.List;
+
+/**
+ * 阿里百炼重排序模型测试 - Main方法直接运行
+ * 运行前请设置 API_KEY
+ */
+public class AliBaiLianRerankTestMain {
+
+    // 请替换为你的 API Key
+    private static final String API_KEY = "sk-your-api-key-here";
+    private static final String API_HOST = "https://dashscope.aliyuncs.com";
+    private static final String MODEL_NAME = "qwen3-rerank";
+
+    public static void main(String[] args) {
+        AliBaiLianRerankModelService service = new AliBaiLianRerankModelService();
+
+        // 配置
+        ChatModelVo config = new ChatModelVo();
+        config.setApiHost(API_HOST);
+        config.setApiKey(API_KEY);
+        config.setModelName(MODEL_NAME);
+        service.configure(config);
+
+        // 测试数据
+        List<String> documents = Arrays.asList(
+                "文本排序模型广泛用于搜索引擎和推荐系统中，它们根据文本相关性对候选文本进行排序",
+                "量子计算是计算科学的一个前沿领域",
+                "预训练语言模型的发展给文本排序模型带来了新的进展"
+        );
+
+        RerankRequest request = RerankRequest.builder()
+                .query("什么是文本排序模型")
+                .documents(documents)
+                .topN(2)
+                .returnDocuments(true)
+                .build();
+
+        System.out.println("=== 开始测试阿里百炼重排序 ===");
+        System.out.println("API Host: " + API_HOST);
+        System.out.println("Model: " + MODEL_NAME);
+        System.out.println("Query: 什么是文本排序模型");
+        System.out.println();
+
+        try {
+            RerankResult result = service.rerank(request);
+
+            System.out.println("=== 重排序结果 ===");
+            System.out.println("总文档数: " + result.getTotalDocuments());
+            System.out.println("耗时: " + result.getDurationMs() + "ms");
+            System.out.println();
+
+            result.getDocuments().forEach(doc -> {
+                System.out.println("索引: " + doc.getIndex());
+                System.out.println("相关性分数: " + doc.getRelevanceScore());
+                System.out.println("文档: " + doc.getDocument());
+                System.out.println("---");
+            });
+
+            System.out.println("=== 测试成功 ===");
+
+        } catch (Exception e) {
+            System.err.println("=== 测试失败 ===");
+            e.printStackTrace();
+        }
+    }
+}