新增查询重写器、翻译器、压缩器和多查询扩展器

src/main/java/com/wok/supportbot/app/AssistantApp.java

@@ -1,19 +1,31 @@
 package com.wok.supportbot.app;
 
 import com.wok.supportbot.advisor.MyLoggerAdvisor;
+import com.wok.supportbot.advisor.ReReadingAdvisor;
 import com.wok.supportbot.chatmemory.DatabaseChatMemory;
 import jakarta.annotation.Resource;
 import lombok.extern.slf4j.Slf4j;
 import org.springframework.ai.chat.client.ChatClient;
 import org.springframework.ai.chat.client.advisor.MessageChatMemoryAdvisor;
 import org.springframework.ai.chat.client.advisor.QuestionAnswerAdvisor;
-import org.springframework.ai.chat.memory.ChatMemory;
-import org.springframework.ai.chat.memory.InMemoryChatMemory;
+import org.springframework.ai.chat.client.advisor.RetrievalAugmentationAdvisor;
+import org.springframework.ai.chat.client.advisor.api.Advisor;
 import org.springframework.ai.chat.model.ChatModel;
 import org.springframework.ai.chat.model.ChatResponse;
+import org.springframework.ai.rag.Query;
+import org.springframework.ai.rag.generation.augmentation.ContextualQueryAugmenter;
+import org.springframework.ai.rag.preretrieval.query.expansion.MultiQueryExpander;
+import org.springframework.ai.rag.preretrieval.query.transformation.QueryTransformer;
+import org.springframework.ai.rag.preretrieval.query.transformation.RewriteQueryTransformer;
+import org.springframework.ai.rag.retrieval.search.VectorStoreDocumentRetriever;
+import org.springframework.ai.vectorstore.SearchRequest;
 import org.springframework.ai.vectorstore.VectorStore;
+import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.stereotype.Component;
 
+import java.util.ArrayList;
+import java.util.List;
+
 import static org.springframework.ai.chat.client.advisor.AbstractChatMemoryAdvisor.CHAT_MEMORY_CONVERSATION_ID_KEY;
 import static org.springframework.ai.chat.client.advisor.AbstractChatMemoryAdvisor.CHAT_MEMORY_RETRIEVE_SIZE_KEY;
 
@@ -38,6 +50,7 @@ public class AssistantApp {
 
     /**
      * 初始化 ChatClient
+     *
      * @param dashscopeChatModel
      */
     public AssistantApp(ChatModel dashscopeChatModel, DatabaseChatMemory chatMemory) {
@@ -61,6 +74,7 @@ public class AssistantApp {
 
     /**
      * AI 基础对话（支持多轮对话记忆）
+     *
      * @param message
      * @param chatId
      * @return
@@ -79,6 +93,7 @@ public class AssistantApp {
 
     /**
      * 和 RAG 知识库进行对话
+     *
      * @param message
      * @param chatId
      * @return
@@ -90,7 +105,49 @@ public class AssistantApp {
                 .advisors(spec -> spec.param(CHAT_MEMORY_CONVERSATION_ID_KEY, chatId)
                         .param(CHAT_MEMORY_RETRIEVE_SIZE_KEY, 10))
                 // 应用 RAG 知识库问答
-                .advisors(new QuestionAnswerAdvisor(vectorStore))
+                .advisors(QuestionAnswerAdvisor.builder(vectorStore)
+                        // 相似度阈值为 0.0，并返回最相关的前 4 个结果
+                        .searchRequest(SearchRequest.builder().similarityThreshold(0.0).topK(4).build())
+                        .build())
+                .call()
+                .chatResponse();
+        return chatResponse.getResult().getOutput().getText();
+    }
+
+
+    @Autowired
+    private List<QueryTransformer> queryTransformers;
+    @Autowired
+    private MultiQueryExpander multiQueryExpander;
+
+    /**
+     * 和 RAG 知识库进行对话
+     *
+     * @param message
+     * @param chatId
+     * @return
+     */
+    public String doChatWithRagEnhance(String message, String chatId) {
+        Advisor retrievalAugmentationAdvisor = RetrievalAugmentationAdvisor.builder()
+                //.queryTransformers(queryTransformers)
+                //.queryExpander(multiQueryExpander)
+                .documentRetriever(VectorStoreDocumentRetriever.builder()
+                        .vectorStore(vectorStore)
+                        .similarityThreshold(0.5)
+                        .topK(4)
+                        .build())
+                .queryAugmenter(ContextualQueryAugmenter.builder()
+                        .allowEmptyContext(false) // 不允许模型在没有找到相关文档的情况下也生成回答
+                        .build())
+                .build();
+
+        ChatResponse chatResponse = chatClient
+                .prompt()
+                .user(message)
+                .advisors(spec -> spec.param(CHAT_MEMORY_CONVERSATION_ID_KEY, chatId)
+                        .param(CHAT_MEMORY_RETRIEVE_SIZE_KEY, 10))
+                // 应用 RAG 知识库问答
+                .advisors(retrievalAugmentationAdvisor)
                 .call()
                 .chatResponse();
         return chatResponse.getResult().getOutput().getText();

src/main/java/com/wok/supportbot/config/QueryExpanderConfig.java

@@ -0,0 +1,20 @@
+package com.wok.supportbot.config;
+
+import org.springframework.ai.chat.client.ChatClient;
+import org.springframework.ai.chat.model.ChatModel;
+import org.springframework.ai.rag.preretrieval.query.expansion.MultiQueryExpander;
+import org.springframework.context.annotation.Bean;
+import org.springframework.context.annotation.Configuration;
+
+@Configuration
+public class QueryExpanderConfig {
+
+    @Bean
+    public MultiQueryExpander multiQueryExpander(ChatModel dashscopeChatModel) {
+        return MultiQueryExpander.builder()
+                .chatClientBuilder(ChatClient.builder(dashscopeChatModel))
+                .numberOfQueries(3)
+                .includeOriginal(true)
+                .build();
+    }
+}

src/main/java/com/wok/supportbot/config/QueryTransformerConfig.java

@@ -0,0 +1,41 @@
+package com.wok.supportbot.config;
+
+import org.springframework.ai.chat.client.ChatClient;
+import org.springframework.ai.chat.client.advisor.RetrievalAugmentationAdvisor;
+import org.springframework.ai.chat.model.ChatModel;
+import org.springframework.ai.rag.preretrieval.query.expansion.MultiQueryExpander;
+import org.springframework.ai.rag.preretrieval.query.transformation.CompressionQueryTransformer;
+import org.springframework.ai.rag.preretrieval.query.transformation.QueryTransformer;
+import org.springframework.ai.rag.preretrieval.query.transformation.RewriteQueryTransformer;
+import org.springframework.ai.rag.preretrieval.query.transformation.TranslationQueryTransformer;
+import org.springframework.ai.rag.retrieval.search.DocumentRetriever;
+import org.springframework.context.annotation.Bean;
+import org.springframework.context.annotation.Configuration;
+
+import java.util.List;
+
+@Configuration
+public class QueryTransformerConfig {
+
+    @Bean
+    public QueryTransformer rewriteQueryTransformer(ChatModel dashscopeChatModel) {
+        return RewriteQueryTransformer.builder()
+                .chatClientBuilder(ChatClient.builder(dashscopeChatModel))
+                .build();
+    }
+
+    @Bean
+    public QueryTransformer translationQueryTransformer(ChatModel dashscopeChatModel) {
+        return TranslationQueryTransformer.builder()
+                .chatClientBuilder(ChatClient.builder(dashscopeChatModel))
+                .targetLanguage("chinese")
+                .build();
+    }
+
+    @Bean
+    public QueryTransformer compressionQueryTransformer(ChatModel dashscopeChatModel) {
+        return CompressionQueryTransformer.builder()
+                .chatClientBuilder(ChatClient.builder(dashscopeChatModel))
+                .build();
+    }
+}

src/main/java/com/wok/supportbot/load/PgVectorStoreConfig.java

@@ -22,9 +22,9 @@ import static org.springframework.ai.vectorstore.pgvector.PgVectorStore.PgIndexT
 public class PgVectorStoreConfig {
 
     @Bean
-    @Primary
+    @Primary // 默认使用pgsql储存向量
     public VectorStore pgVectorVectorStore(JdbcTemplate jdbcTemplate, EmbeddingModel dashscopeEmbeddingModel) {
-        VectorStore vectorStore = PgVectorStore.builder(jdbcTemplate, dashscopeEmbeddingModel)
+        return PgVectorStore.builder(jdbcTemplate, dashscopeEmbeddingModel)
                 .dimensions(1536)                    // Optional: defaults to model dimensions or 1536
                 .distanceType(COSINE_DISTANCE)       // Optional: defaults to COSINE_DISTANCE
                 .indexType(HNSW)                     // Optional: defaults to HNSW
@@ -33,6 +33,5 @@ public class PgVectorStoreConfig {
                 .vectorTableName("vector_store")     // Optional: defaults to "vector_store"
                 .maxDocumentBatchSize(10000)         // Optional: defaults to 10000
                 .build();
-        return vectorStore;
     }
 }

src/main/java/com/wok/supportbot/preretrieval/CompressionQueryRewriter.java

@@ -0,0 +1,46 @@
+package com.wok.supportbot.preretrieval;
+
+import org.springframework.ai.chat.client.ChatClient;
+
+import org.springframework.ai.chat.messages.AssistantMessage;
+import org.springframework.ai.chat.messages.Message;
+import org.springframework.ai.chat.messages.UserMessage;
+import org.springframework.ai.chat.model.ChatModel;
+import org.springframework.ai.rag.Query;
+import org.springframework.ai.rag.preretrieval.query.transformation.CompressionQueryTransformer;
+import org.springframework.ai.rag.preretrieval.query.transformation.QueryTransformer;
+import org.springframework.stereotype.Component;
+
+import java.util.List;
+
+/**
+ * 查询压缩器 - CompressionQueryTransformer
+ */
+@Component
+public class CompressionQueryRewriter {
+
+    private final QueryTransformer queryTransformer;
+
+    public CompressionQueryRewriter(ChatModel dashscopeChatModel) {
+        ChatClient.Builder builder = ChatClient.builder(dashscopeChatModel);
+        queryTransformer = CompressionQueryTransformer.builder()
+                .chatClientBuilder(builder)
+                .build();
+    }
+
+    /**
+     * 执行查询压缩（带对话历史）
+     *
+     * @param prompt 当前查询文本
+     * @return 压缩后的查询文本
+     */
+    public String doQueryRewrite(String prompt, List<Message> history) {
+        Query query = Query.builder()
+                .text(prompt)
+                .history(history)
+                .build();
+
+        Query transformed = queryTransformer.transform(query);
+        return transformed.text();
+    }
+}

src/main/java/com/wok/supportbot/preretrieval/MultiQueryExpanderRewriter.java

@@ -0,0 +1,41 @@
+package com.wok.supportbot.preretrieval;
+
+import org.springframework.ai.chat.client.ChatClient;
+import org.springframework.ai.chat.model.ChatModel;
+import org.springframework.ai.rag.Query;
+import org.springframework.ai.rag.preretrieval.query.expansion.MultiQueryExpander;
+import org.springframework.stereotype.Component;
+
+import java.util.List;
+import java.util.stream.Collectors;
+
+/**
+ * 多查询扩展器 - MultiQueryExpander
+ */
+@Component
+public class MultiQueryExpanderRewriter {
+
+    private final MultiQueryExpander queryExpander;
+
+    public MultiQueryExpanderRewriter(ChatModel dashscopeChatModel) {
+        ChatClient.Builder builder = ChatClient.builder(dashscopeChatModel);
+        queryExpander = MultiQueryExpander.builder()
+                .chatClientBuilder(builder)
+                .numberOfQueries(3)
+                .includeOriginal(true) //在扩展查询列表中包含原始查询
+                .build();
+    }
+
+    /**
+     * 执行查询扩展，返回多个查询文本
+     *
+     * @param prompt 原始查询
+     * @return 多个语义不同的查询文本列表
+     */
+    public List<String> doQueryRewrite(String prompt) {
+        List<Query> queries = queryExpander.expand(new Query(prompt));
+        return queries.stream()
+                .map(Query::text)
+                .collect(Collectors.toList());
+    }
+}

src/main/java/com/wok/supportbot/preretrieval/RewriteQueryRewriter.java

@@ -0,0 +1,39 @@
+package com.wok.supportbot.preretrieval;
+
+import org.springframework.ai.chat.client.ChatClient;
+import org.springframework.ai.chat.model.ChatModel;
+import org.springframework.ai.rag.Query;
+import org.springframework.ai.rag.preretrieval.query.transformation.QueryTransformer;
+import org.springframework.ai.rag.preretrieval.query.transformation.RewriteQueryTransformer;
+import org.springframework.stereotype.Component;
+
+/**
+ * 查询重写器 - RewriteQueryTransformer
+ */
+@Component
+public class RewriteQueryRewriter {
+
+    private final QueryTransformer queryTransformer;
+
+    public RewriteQueryRewriter(ChatModel dashscopeChatModel) {
+        ChatClient.Builder builder = ChatClient.builder(dashscopeChatModel);
+        // 创建查询重写转换器
+        queryTransformer = RewriteQueryTransformer.builder()
+                .chatClientBuilder(builder)
+                .build();
+    }
+
+    /**
+     * 执行查询重写
+     *
+     * @param prompt
+     * @return
+     */
+    public String doQueryRewrite(String prompt) {
+        Query query = new Query(prompt);
+        // 执行查询重写
+        Query transformedQuery = queryTransformer.transform(query);
+        // 输出重写后的查询
+        return transformedQuery.text();
+    }
+}

src/main/java/com/wok/supportbot/preretrieval/TranslationQueryRewriter.java

@@ -0,0 +1,37 @@
+package com.wok.supportbot.preretrieval;
+
+import org.springframework.ai.chat.client.ChatClient;
+import org.springframework.ai.chat.model.ChatModel;
+import org.springframework.ai.rag.Query;
+import org.springframework.ai.rag.preretrieval.query.transformation.QueryTransformer;
+import org.springframework.ai.rag.preretrieval.query.transformation.TranslationQueryTransformer;
+import org.springframework.stereotype.Component;
+
+/**
+ * 查询翻译器 - TranslationQueryTransformer
+ */
+@Component
+public class TranslationQueryRewriter {
+
+    private final QueryTransformer queryTransformer;
+
+    public TranslationQueryRewriter(ChatModel dashscopeChatModel) {
+        ChatClient.Builder builder = ChatClient.builder(dashscopeChatModel);
+        queryTransformer = TranslationQueryTransformer.builder()
+                .chatClientBuilder(builder)
+                .targetLanguage("chinese")
+                .build();
+    }
+
+    /**
+     * 执行查询翻译
+     *
+     * @param prompt 原始查询文本
+     * @return 翻译后的查询文本
+     */
+    public String doQueryRewrite(String prompt) {
+        Query query = new Query(prompt);
+        Query transformedQuery = queryTransformer.transform(query);
+        return transformedQuery.text();
+    }
+}

src/test/java/com/wok/supportbot/PgVectorVectorStoreConfigTest.java

@@ -1,5 +1,6 @@
 package com.wok.supportbot;
 
+import com.wok.supportbot.preretrieval.RewriteQueryRewriter;
 import jakarta.annotation.Resource;
 import org.junit.jupiter.api.Assertions;
 import org.junit.jupiter.api.Test;

src/test/java/com/wok/supportbot/QueryTransformerTests.java

@@ -0,0 +1,76 @@
+package com.wok.supportbot;
+
+import com.wok.supportbot.preretrieval.CompressionQueryRewriter;
+import com.wok.supportbot.preretrieval.MultiQueryExpanderRewriter;
+import com.wok.supportbot.preretrieval.RewriteQueryRewriter;
+import com.wok.supportbot.preretrieval.TranslationQueryRewriter;
+import jakarta.annotation.Resource;
+import org.junit.jupiter.api.Test;
+import org.springframework.ai.chat.messages.AssistantMessage;
+import org.springframework.ai.chat.messages.Message;
+import org.springframework.ai.chat.messages.UserMessage;
+import org.springframework.ai.rag.Query;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.boot.test.context.SpringBootTest;
+
+import java.util.List;
+
+@SpringBootTest
+public class QueryTransformerTests {
+
+    @Autowired
+    private TranslationQueryRewriter translationQueryRewriter;
+
+    @Autowired
+    private CompressionQueryRewriter compressionQueryRewriter;
+
+    @Autowired
+    private MultiQueryExpanderRewriter multiQueryExpanderRewriter;
+
+    @Autowired
+    private RewriteQueryRewriter rewriteQueryRewriter;
+
+    @Test
+    void testRewriteQueryRewriter() {
+        // 构造输入
+        String originalQuery = "我想买一部拍照效果好的手机";
+        // 执行
+        String rewritten = rewriteQueryRewriter.doQueryRewrite(originalQuery);
+        // 输出结果
+        System.out.println("重写结果：" + rewritten);
+    }
+
+    @Test
+    public void testTranslationQueryRewriter() {
+        String prompt = "I want to buy a lightweight laptop suitable for students.";
+        String result = translationQueryRewriter.doQueryRewrite(prompt);
+        System.out.println("Translation result: " + result);
+    }
+
+    @Test
+    public void testCompressionQueryRewriter() {
+        // 当前追问，用户说得很模糊
+        String prompt = "那这款的电池续航如何？";
+
+        // 多轮上下文，用户逐渐缩小目标
+        List<Message> history = List.of(
+                new UserMessage("我想买一台适合出差用的轻薄笔记本"),
+                new AssistantMessage("你可以看看戴尔 XPS 13，性能不错而且轻便"),
+                new UserMessage("能不能推荐一款支持长续航的？"),
+                new AssistantMessage("荣耀 MagicBook X16 电池续航表现优秀，适合长时间外出使用")
+        );
+        // 执行压缩
+        String result = compressionQueryRewriter.doQueryRewrite(prompt, history);
+        // 输出压缩后的独立查询
+        System.out.println("Compression result: " + result);
+    }
+
+
+    @Test
+    public void testMultiQueryExpanderRewriter() {
+        String prompt = "推荐一些适合夏天穿的男士T恤";
+        List<String> expandedQueries = multiQueryExpanderRewriter.doQueryRewrite(prompt);
+        System.out.println("Expanded queries:");
+        expandedQueries.forEach(System.out::println);
+    }
+}

src/test/java/com/wok/supportbot/SupportBotApplicationTests.java

@@ -76,5 +76,13 @@ class SupportBotApplicationTests {
         Assertions.assertNotNull(answer);
     }
 
+    @Test
+    void doChatWithRagEnhance() {
+        String chatId = "1069b88d-eb85-47ac-bd2e-c393d118a5aa";
+        String message = "我之前询问了你什么问题？";
+        String answer =  assistantApp.doChatWithRagEnhance(message, chatId);
+        Assertions.assertNotNull(answer);
+    }
+
 
 }