调整项目结构

llm-back/pom.xml

@@ -220,8 +220,8 @@
 
             <!-- 智能体-->
             <dependency>
-                <groupId>com.cmc</groupId>
-                <artifactId>cmc-agent</artifactId>
+                <groupId>com.ruoyi</groupId>
+                <artifactId>ruoyi-agent</artifactId>
                 <version>${ruoyi.version}</version>
             </dependency>
 
@@ -229,8 +229,8 @@
     </dependencyManagement>
 
     <modules>
-        <module>cmc-agent</module>
         <module>ruoyi-admin</module>
+        <module>ruoyi-agent</module>
         <module>ruoyi-framework</module>
         <module>ruoyi-system</module>
         <module>ruoyi-quartz</module>

llm-back/ruoyi-admin/pom.xml

@@ -39,8 +39,9 @@
 
          <!-- Mysql驱动包 -->
         <dependency>
-            <groupId>mysql</groupId>
-            <artifactId>mysql-connector-java</artifactId>
+            <groupId>com.mysql</groupId>
+            <artifactId>mysql-connector-j</artifactId>
+            <version>8.0.33</version>
         </dependency>
 
         <!-- 核心模块-->
@@ -61,6 +62,12 @@
             <artifactId>ruoyi-generator</artifactId>
         </dependency>
 
+        <!-- 智能体-->
+        <dependency>
+            <groupId>com.ruoyi</groupId>
+            <artifactId>ruoyi-agent</artifactId>
+        </dependency>
+
     </dependencies>
 
     <build>

llm-back/cmc-agent/pom.xml → llm-back/ruoyi-agent/pom.xml

@@ -8,8 +8,8 @@
         <version>3.8.9</version>
     </parent>
     <modelVersion>4.0.0</modelVersion>
-    <packaging>jar</packaging>
-    <artifactId>cmc-agent</artifactId>
+
+    <artifactId>ruoyi-agent</artifactId>
 
     <description>
         cmc智能体
@@ -74,34 +74,4 @@
 
     </dependencies>
 
-    <build>
-        <plugins>
-            <plugin>
-                <groupId>org.springframework.boot</groupId>
-                <artifactId>spring-boot-maven-plugin</artifactId>
-                <version>2.5.15</version>
-                <configuration>
-                    <fork>true</fork> <!-- 如果没有该配置，devtools不会生效 -->
-                </configuration>
-                <executions>
-                    <execution>
-                        <goals>
-                            <goal>repackage</goal>
-                        </goals>
-                    </execution>
-                </executions>
-            </plugin>
-            <plugin>   
-                <groupId>org.apache.maven.plugins</groupId>   
-                <artifactId>maven-war-plugin</artifactId>   
-                <version>3.1.0</version>   
-                <configuration>
-                    <failOnMissingWebXml>false</failOnMissingWebXml>
-                    <warName>${project.artifactId}</warName>
-                </configuration>   
-           </plugin>   
-        </plugins>
-        <finalName>${project.artifactId}</finalName>
-    </build>
-
 </project>

llm-back/ruoyi-agent/src/main/java/com/ruoyi/agent/controller/KnowLedgeController.java

@@ -0,0 +1,63 @@
+package com.ruoyi.agent.controller;
+
+import com.ruoyi.common.config.RuoYiConfig;
+import com.ruoyi.common.core.controller.BaseController;
+import com.ruoyi.common.core.domain.AjaxResult;
+import com.ruoyi.agent.service.LangChainMilvusService;
+import dev.langchain4j.model.embedding.onnx.bgesmallzhv15.BgeSmallZhV15EmbeddingModel;
+import dev.langchain4j.model.embedding.EmbeddingModel;
+import org.springframework.web.bind.annotation.*;
+import org.springframework.web.multipart.MultipartFile;
+
+import java.io.File;
+import java.io.IOException;
+
+/**
+ * cmc知识库Controller
+ * 
+ * @author cmc
+ * @date 2025-04-08
+ */
+@RestController
+@RequestMapping("/llm/knowledge")
+public class KnowLedgeController extends BaseController
+{
+    private static final EmbeddingModel embeddingModel = new BgeSmallZhV15EmbeddingModel();
+
+    /**
+     * 新建知识库
+     */
+    @PostMapping("/create")
+    public AjaxResult createKnowLedgeBase(String collectionName)
+    {
+        LangChainMilvusService langChainMilvusService = new LangChainMilvusService(
+                "192.168.28.188",
+                19530,
+                collectionName,
+                embeddingModel);
+        langChainMilvusService.createCollection(512);
+        return success();
+    }
+
+    /**
+     * 插入知识库文件
+     */
+    @PostMapping("/insert")
+    public AjaxResult insertKnowledge(MultipartFile file, String collectionName) throws IOException {
+        LangChainMilvusService langChainMilvusService = new LangChainMilvusService(
+                "192.168.28.188",
+                19530,
+                collectionName,
+                embeddingModel);
+
+        File profilePath = new File( RuoYiConfig.getProfile() + "/upload/knowledge");
+        if (!profilePath.exists())
+            profilePath.mkdirs();
+        File transferFile = new File( profilePath + "/" + file.getOriginalFilename());
+        if (!transferFile.exists())
+            file.transferTo(transferFile);
+        langChainMilvusService.insertLangchainEmbeddingDocument(transferFile);
+        return success();
+    }
+
+}

llm-back/ruoyi-agent/src/main/java/com/ruoyi/agent/controller/RagController.java

@@ -0,0 +1,45 @@
+package com.ruoyi.agent.controller;
+
+import com.ruoyi.common.core.controller.BaseController;
+import com.ruoyi.common.core.domain.AjaxResult;
+import com.ruoyi.agent.service.LangChainMilvusService;
+import dev.langchain4j.model.embedding.EmbeddingModel;
+import dev.langchain4j.model.embedding.onnx.bgesmallzhv15.BgeSmallZhV15EmbeddingModel;
+import org.springframework.web.bind.annotation.PostMapping;
+import org.springframework.web.bind.annotation.RequestMapping;
+import org.springframework.web.bind.annotation.RestController;
+
+import java.io.IOException;
+import java.util.List;
+
+/**
+ * cmc知识库Controller
+ * 
+ * @author cmc
+ * @date 2025-04-08
+ */
+@RestController
+@RequestMapping("/llm/rag")
+public class RagController extends BaseController
+{
+    private static final EmbeddingModel embeddingModel = new BgeSmallZhV15EmbeddingModel();
+
+    /**
+     * 增强检索生成回答
+     */
+    @PostMapping("/answer")
+    public AjaxResult answer(String question, String collectionName) throws IOException {
+        LangChainMilvusService langChainMilvusService = new LangChainMilvusService(
+                "192.168.28.188",
+                19530,
+                collectionName,
+                embeddingModel);
+
+        // 1. Milvus检索
+        List<String> contexts = langChainMilvusService.retrieveFromMilvus(question, 3);
+
+        // 2. 调用本地LLM或HTTP服务
+        return success(langChainMilvusService.generateAnswerWithRag(question, contexts));
+    }
+
+}

llm-back/ruoyi-agent/src/main/java/com/ruoyi/agent/controller/SessionController.java

@@ -0,0 +1,57 @@
+package com.ruoyi.agent.controller;
+
+import com.alibaba.fastjson2.JSONObject;
+import com.ruoyi.common.core.controller.BaseController;
+import com.ruoyi.common.core.domain.AjaxResult;
+import okhttp3.*;
+import org.springframework.web.bind.annotation.GetMapping;
+import org.springframework.web.bind.annotation.RequestMapping;
+import org.springframework.web.bind.annotation.RestController;
+
+import java.io.IOException;
+import java.util.concurrent.TimeUnit;
+
+/**
+ * cmc知识库Controller
+ * 
+ * @author cmc
+ * @date 2025-04-08
+ */
+@RestController
+@RequestMapping("/llm/session")
+public class SessionController extends BaseController
+{
+    /**
+     * 生成回答
+     */
+    @GetMapping("/answer")
+    public AjaxResult answer(String question) throws IOException {
+
+        // 1. 调用本地LLM或HTTP服务
+        return success(generateAnswer(question));
+    }
+
+    // 调用LLM生成回答
+    public String generateAnswer(String question) throws IOException {
+        // 构建带动态参数的URL
+        HttpUrl url = HttpUrl.parse("http://192.168.28.188:8080/generate")
+                .newBuilder()
+                .addQueryParameter("prompt", question)
+                .build();
+
+        Request request = new Request.Builder()
+                .url(url)
+                .build();
+
+        OkHttpClient client = new OkHttpClient.Builder()
+                .readTimeout(60, TimeUnit.SECONDS)      // 读取响应超时
+                .build();
+
+        try (Response response = client.newCall(request).execute()) {
+            String responseBody = response.body().string();
+            String responseResult = JSONObject.parseObject(responseBody).getString("generated_text");
+            return responseResult;
+        }
+    }
+
+}

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

@@ -0,0 +1,208 @@
+package com.ruoyi.agent.service;
+
+import com.google.gson.Gson;
+import dev.langchain4j.data.document.Document;
+import dev.langchain4j.data.document.parser.apache.pdfbox.ApachePdfBoxDocumentParser;
+import dev.langchain4j.data.document.splitter.DocumentByParagraphSplitter;
+import dev.langchain4j.data.segment.TextSegment;
+import dev.langchain4j.model.embedding.EmbeddingModel;
+
+import io.milvus.client.MilvusServiceClient;
+import io.milvus.grpc.DataType;
+import io.milvus.grpc.MutationResult;
+import io.milvus.grpc.SearchResults;
+import io.milvus.param.ConnectParam;
+import io.milvus.param.IndexType;
+import io.milvus.param.MetricType;
+import io.milvus.param.R;
+import io.milvus.param.collection.CreateCollectionParam;
+import io.milvus.param.collection.FieldType;
+import io.milvus.param.dml.InsertParam;
+import io.milvus.param.dml.SearchParam;
+import io.milvus.param.index.CreateIndexParam;
+import io.milvus.response.SearchResultsWrapper;
+import okhttp3.*;
+
+import java.io.File;
+import java.io.FileInputStream;
+import java.io.IOException;
+import java.io.InputStream;
+import java.util.*;
+import java.util.stream.Collectors;
+
+public class LangChainMilvusService {
+    private String LLM_SERVICE_URL;
+    private MilvusServiceClient milvusClient;
+    private String collectionName;
+    private EmbeddingModel embeddingModel;
+
+    /**
+     * 连接milvus知识库，加入langchain自带emdding
+     */
+    public LangChainMilvusService(String host, int port, String collectionName, EmbeddingModel embeddingModel) {
+        this.milvusClient = new MilvusServiceClient(
+                ConnectParam.newBuilder()
+                        .withHost(host)
+                        .withPort(port)
+                        .build()
+        );
+        this.LLM_SERVICE_URL = "http://" + host + ":8000/generate";
+        this.collectionName = collectionName;
+        this.embeddingModel = embeddingModel;
+    }
+
+    /**
+     * 不使用向量数据库
+     */
+    public LangChainMilvusService(String host, int port) {
+        this.milvusClient = new MilvusServiceClient(
+                ConnectParam.newBuilder()
+                        .withHost(host)
+                        .withPort(port)
+                        .build()
+        );
+        this.LLM_SERVICE_URL = "http://" + host + ":8000/generate";
+    }
+
+    /**
+     * 新建知识库Collection（含Schema、Field、Index）
+     */
+    public void createCollection(int dimension) {
+        FieldType idField = FieldType.newBuilder()
+                .withName("id")
+                .withDataType(DataType.Int64)
+                .withPrimaryKey(true)
+                .withAutoID(true)
+                .build();
+
+        FieldType fileNameField = FieldType.newBuilder()
+                .withName("file_name")
+                .withDataType(DataType.VarChar)
+                .withMaxLength(256)
+                .build();
+
+        FieldType contentField = FieldType.newBuilder()
+                .withName("content")
+                .withDataType(DataType.VarChar)
+                .withMaxLength(65535)
+                .build();
+
+        FieldType vectorField = FieldType.newBuilder()
+                .withName("embedding")
+                .withDataType(DataType.Float16Vector)
+                .withDimension(dimension)
+                .build();
+
+        CreateCollectionParam createCollectionParam = CreateCollectionParam.newBuilder()
+                .withCollectionName(collectionName)
+                .addFieldType(idField)
+                .addFieldType(fileNameField)
+                .addFieldType(contentField)
+                .addFieldType(vectorField)
+                .build();
+
+        milvusClient.createCollection(createCollectionParam);
+
+        // 创建索引
+        CreateIndexParam createIndexParam = CreateIndexParam.newBuilder()
+                .withCollectionName(collectionName)
+                .withFieldName("embedding")
+                .withIndexType(IndexType.IVF_FLAT)
+                .withMetricType(MetricType.COSINE)
+                .withExtraParam("{\"nlist\": 64}")
+                .build();
+
+        milvusClient.createIndex(createIndexParam);
+    }
+
+    public void insertLangchainEmbeddingDocument(File file) throws IOException {
+        // 加载文档
+        InputStream fileInputStream = new FileInputStream(file);
+        Document document = new ApachePdfBoxDocumentParser().parse(fileInputStream);
+        DocumentByParagraphSplitter splitter = new DocumentByParagraphSplitter(150,10);;
+        List<TextSegment> segments = splitter.split(document);
+
+        // 提取文本和生成嵌入
+        List<String> texts = new ArrayList<>();
+        List<List<Float>> embeddings = new ArrayList<>();
+
+        for (TextSegment segment : segments) {
+            String text = segment.text();
+            if (text.trim().isEmpty())
+                continue;
+            texts.add(text);
+            embeddings.add(embeddingModel.embed(text).content().vectorAsList());
+        }
+
+        // 准备插入数据
+        List<InsertParam.Field> fields = new ArrayList<>();
+        fields.add(new InsertParam.Field("file_name", Arrays.asList(file.getName())));
+        fields.add(new InsertParam.Field("content", Arrays.asList(texts)));
+        fields.add(new InsertParam.Field("embedding", Arrays.asList(embeddings)));
+
+        InsertParam insertParam = InsertParam.newBuilder()
+                .withCollectionName(collectionName)
+                .withFields(fields)
+                .build();
+
+        // 执行插入
+        R<MutationResult> insertResult = milvusClient.insert(insertParam);
+
+        if (insertResult.getStatus() != R.Status.Success.getCode()) {
+            throw new RuntimeException("Failed to insert document: " + insertResult.getMessage());
+        }
+    }
+
+    // 从Milvus检索相关文档
+    public List<String> retrieveFromMilvus(String query, int topK) throws IOException {
+        List<Float> queryVector = embeddingModel.embed(query).content().vectorAsList();
+
+        SearchParam searchParam = SearchParam.newBuilder()
+                .withCollectionName(collectionName)
+                .withVectors(queryVector)
+                .withTopK(topK)
+                .withOutFields(Arrays.asList("content"))
+                .build();
+
+        R<SearchResults> response = milvusClient.search(searchParam);
+        SearchResultsWrapper wrapper = new SearchResultsWrapper(response.getData().getResults());
+
+        return wrapper.getRowRecords(0).stream()
+                .map(record -> (String) record.get("content"))
+                .collect(Collectors.toList());
+    }
+
+    // 调用LLM+RAG生成回答
+    public String generateAnswerWithRag(String question, List<String> contexts) throws IOException {
+        String prompt = buildPrompt(question, contexts);
+        Gson gson = new Gson();
+        Map<String, String> hashMap = new HashMap<>();
+        hashMap.put("prompt", prompt);
+        hashMap.put("max_tokens", "512");
+        RequestBody body = RequestBody.create(
+                MediaType.parse("application/json"),
+                new Gson().toJson(hashMap));
+
+        Request request = new Request.Builder()
+                .url(LLM_SERVICE_URL)
+                .post(body)
+                .build();
+
+        try (Response response = new OkHttpClient().newCall(request).execute()) {
+            return gson.fromJson(response.body().string(), Map.class).get("generated_text").toString();
+        }
+    }
+
+    private String buildPrompt(String question, List<String> contexts) {
+        StringBuilder sb = new StringBuilder();
+        sb.append("根据以下上下文回答问题：\n\n");
+        for (int i = 0; i < contexts.size(); i++) {
+            sb.append("上下文").append(i+1).append(": ").append(contexts.get(i)).append("\n\n");
+        }
+        sb.append("问题: ").append(question).append("\n回答: ");
+        return sb.toString();
+    }
+    public void close() {
+        milvusClient.close();
+    }
+}