Merge pull request #258 from StevenJack666/v3.0.0

修改千问模型调用逻辑

ruoyi-admin/src/main/java/org/ruoyi/RuoYiAIApplication.java

@@ -16,7 +16,7 @@ public class RuoYiAIApplication {
         SpringApplication application = new SpringApplication(RuoYiAIApplication.class);
         application.setApplicationStartup(new BufferingApplicationStartup(2048));
         application.run(args);
-        System.out.println("(♥◠‿◠)ﾉﾞ  RuoYi-AI启动成功   ლ(´ڡ`ლ)ﾞ");
+        System.out.println("(♥◠‿◠)ﾉﾞ   RuoYi-AI启动成功   ლ(´ڡ`ლ)ﾞ");
     }
 
 }

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/agent/EchartsAgent.java

@@ -0,0 +1,89 @@
+package org.ruoyi.agent;
+
+import dev.langchain4j.agentic.Agent;
+import dev.langchain4j.service.SystemMessage;
+import dev.langchain4j.service.UserMessage;
+import dev.langchain4j.service.V;
+
+/**
+ * Text2SQL and Echarts Chart Generation Agent
+ * An intelligent assistant that converts natural language queries into SQL,
+ * executes database queries, and generates Echarts visualizations.
+ */
+public interface EchartsAgent {
+
+    @SystemMessage("""
+        You are a data visualization assistant that generates Echarts chart configurations.
+        
+        CRITICAL OUTPUT REQUIREMENTS:
+        - Return Echarts JSON wrapped in markdown code block
+        - Use this exact format: ```json\n{...}\n```
+        - The JSON inside must be valid Echarts configuration
+        - Frontend expects markdown format for proper parsing
+
+        Your workflow:
+        1. Use MCP tools to query the database and get data
+        2. The MCP tool returns data in this structure:
+           {"data": [{"dict_type": "value1", "count": 10}, {"dict_type": "value2", "count": 20}, ...]}
+        3. Transform this data into Echarts configuration
+        4. Return ONLY the Echarts JSON
+
+        Data transformation rules:
+        - Extract array elements into xAxis categories and series data
+        - For the example above: xAxis.data = ["value1", "value2"], series.data = [10, 20]
+        - Choose chart type based on request: bar (default), line, pie, etc.
+
+        Expected output format (bar chart example):
+        ```json
+        {
+          "title": {
+            "text": "Dict Type Distribution",
+            "left": "center"
+          },
+          "tooltip": {
+            "trigger": "axis"
+          },
+          "xAxis": {
+            "type": "category",
+            "data": ["type1", "type2", "type3"]
+          },
+          "yAxis": {
+            "type": "value"
+          },
+          "series": [
+            {
+              "name": "数量",
+              "type": "bar",
+              "data": [10, 20, 15]
+            }
+          ]
+        }
+        ```
+
+        For pie charts:
+        {
+          "title": {"text": "Chart Title", "left": "center"},
+          "tooltip": {"trigger": "item"},
+          "series": [{
+            "type": "pie",
+            "radius": "50%",
+            "data": [
+              {"value": 10, "name": "Category1"},
+              {"value": 20, "name": "Category2"}
+            ]
+          }]
+        }
+
+        REMEMBER:
+        - Always wrap JSON in ```json and ``` markers
+        - Use proper formatting with indentation
+        - This is the expected format for frontend parsing
+        """)
+    @UserMessage("""
+        Generate an Echarts chart for: {{query}}
+        
+        IMPORTANT: Return the Echarts configuration JSON wrapped in markdown code block (```json...```).
+        """)
+    @Agent("Data visualization assistant that returns Echarts JSON configurations for frontend rendering")
+    String search(@V("query") String query);
+}

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/agent/GetNameInfo.java

@@ -0,0 +1,38 @@
+package org.ruoyi.agent;
+
+import dev.langchain4j.agentic.Agent;
+import dev.langchain4j.service.SystemMessage;
+import dev.langchain4j.service.UserMessage;
+import dev.langchain4j.service.V;
+
+/**
+ * User Name Retrieval Agent
+ * A simple assistant that retrieves user names using the get_name tool.
+ */
+public interface GetNameInfo {
+
+    @SystemMessage("""
+        You are a user identity assistant. You MUST always use tools to get information.
+
+        MANDATORY REQUIREMENTS:
+        - You MUST call the get_user_name_by_id tool for ANY question about names or identity
+        - NEVER respond without calling the get_user_name_by_id tool first
+        - Return ONLY the exact string returned by the get_user_name_by_id tool
+        - Do not make up names like "John Doe" or any other default names
+        - Do not use your knowledge to answer - ALWAYS use the tool
+
+        Your workflow:
+        1. Extract userId from the query (if mentioned), or use "1" as default
+        2. ALWAYS call the get_user_name_by_id tool with the userId parameter
+        3. Return the exact result as plain text with no additions
+
+        CRITICAL: If you don't call the get_user_name_by_id tool, your response is wrong.
+        """)
+    @UserMessage("""
+        Get the user name using the get_user_name_by_id tool. Query: {{query}}
+
+        IMPORTANT: Return only the exact result from the tool.
+        """)
+    @Agent("User identity assistant that returns user name from get_name tool")
+    String search(@V("query") String query);
+}

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

@@ -73,6 +73,9 @@ public abstract class AbstractStreamingChatService implements IChatService {
      */
     private static final Map<Object, MessageWindowChatMemory> memoryCache = new ConcurrentHashMap<>();
 
+
+
+    
     /**
      * 定义聊天流程骨架
      */

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/chat/impl/provider/QianWenChatServiceImpl.java

@@ -1,6 +1,18 @@
 package org.ruoyi.service.chat.impl.provider;
 
-import dev.langchain4j.agent.tool.ToolSpecification;
+import java.util.ArrayList;
+import java.util.List;
+
+import org.ruoyi.agent.EchartsAgent;
+import org.ruoyi.common.chat.domain.dto.request.ChatRequest;
+import org.ruoyi.common.chat.domain.vo.chat.ChatModelVo;
+import org.ruoyi.config.McpSseConfig;
+import org.ruoyi.enums.ChatModeType;
+import org.ruoyi.service.chat.impl.AbstractStreamingChatService;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.stereotype.Service;
+import org.springframework.util.CollectionUtils;
+
 import dev.langchain4j.agentic.AgenticServices;
 import dev.langchain4j.agentic.supervisor.SupervisorAgent;
 import dev.langchain4j.agentic.supervisor.SupervisorResponseStrategy;
@@ -13,23 +25,11 @@ import dev.langchain4j.mcp.McpToolProvider;
 import dev.langchain4j.mcp.client.DefaultMcpClient;
 import dev.langchain4j.mcp.client.McpClient;
 import dev.langchain4j.mcp.client.transport.McpTransport;
-import dev.langchain4j.mcp.client.transport.http.StreamableHttpMcpTransport;
+import dev.langchain4j.mcp.client.transport.stdio.StdioMcpTransport;
 import dev.langchain4j.model.chat.StreamingChatModel;
 import dev.langchain4j.model.chat.response.StreamingChatResponseHandler;
 import dev.langchain4j.service.tool.ToolProvider;
 import lombok.extern.slf4j.Slf4j;
-import org.ruoyi.agent.McpAgent;
-import org.ruoyi.config.McpSseConfig;
-import org.ruoyi.enums.ChatModeType;
-import org.ruoyi.service.chat.impl.AbstractStreamingChatService;
-import org.springframework.beans.factory.annotation.Autowired;
-import org.springframework.stereotype.Service;
-import org.springframework.util.CollectionUtils;
-import org.ruoyi.common.chat.domain.dto.request.ChatRequest;
-import org.ruoyi.common.chat.domain.vo.chat.ChatModelVo;
-
-import java.util.ArrayList;
-import java.util.List;
 
 /**
  * qianWenAI服务调用
@@ -41,13 +41,6 @@ import java.util.List;
 @Slf4j
 public class QianWenChatServiceImpl extends AbstractStreamingChatService {
 
-    @Autowired
-    private McpSseConfig mcpSseConfig;
-
-    /**
-     * 千问开发者默认地址
-     */
-    private static final String QWEN_API_HOST = "https://dashscope.aliyuncs.com/api/v1";
 
     // 添加文档解析的前缀字段
     private static final String UPLOAD_FILE_API_PREFIX = "fileid";
@@ -108,49 +101,45 @@ public class QianWenChatServiceImpl extends AbstractStreamingChatService {
      * @return 返回LLM信息
      */
     protected String doAgent(String userMessage,ChatModelVo chatModelVo) {
-        // 判断是否开启MCP服务
-        if (!mcpSseConfig.isEnabled()) {
-            return "";
-        }
-
-        // 步骤1：根据SSE对外暴露端点连接
-        McpTransport httpMcpTransport = new StreamableHttpMcpTransport.Builder().
-            url(mcpSseConfig.getUrl()).
-            logRequests(true).
-            build();
-
-        // 步骤2：开启客户端连接
-        McpClient mcpClient = new DefaultMcpClient.Builder()
-            .transport(httpMcpTransport)
-            .build();
-
-        // 获取所有mcp工具
-        List<ToolSpecification> toolSpecifications = mcpClient.listTools();
-        System.out.println(toolSpecifications);
-
-        // 步骤3：将mcp对象包装
-        ToolProvider toolProvider = McpToolProvider.builder()
-            .mcpClients(List.of(mcpClient))
-            .build();
-
+   
         // 步骤4：加载LLM模型对话
         QwenChatModel qwenChatModel = QwenChatModel.builder()
-            .baseUrl(QWEN_API_HOST)
             .apiKey(chatModelVo.getApiKey())
             .modelName(chatModelVo.getModelName())
             .build();
-
-        // 步骤5：将MCP对象由智能体Agent管控
-        McpAgent mcpAgent = AgenticServices.agentBuilder(McpAgent.class)
-            .chatModel(qwenChatModel)
-            .toolProvider(toolProvider)
+        McpTransport echart = new StdioMcpTransport.Builder()
+            .command(List.of("uv",
+                "--directory",
+                "/Users/zhangmingming/data/coder/LLM/MCP/cicd-pipeline-example/",
+                "run",
+                "text2sql-mcp"
+            ))
+            .logEvents(true)
             .build();
 
+        // 步骤2: 创建MCP客户端
+        McpClient echartClient = new DefaultMcpClient.Builder()
+            .transport(echart)
+            .build();
+
+        // 步骤3: 配置工具提供者
+        ToolProvider echartToolProvider = McpToolProvider.builder()
+            .mcpClients(List.of(
+                        echartClient))
+                .build();
+            
+        EchartsAgent chartGenerationAgent = AgenticServices.agentBuilder(
+                EchartsAgent.class)
+            .chatModel(qwenChatModel)
+            .toolProvider(echartToolProvider)
+            .build();
+
+
         // 步骤6：将所有MCP对象由超级智能体管控
         SupervisorAgent supervisor = AgenticServices
             .supervisorBuilder()
             .chatModel(qwenChatModel)
-            .subAgents(mcpAgent)
+            .subAgents(chartGenerationAgent)
             .responseStrategy(SupervisorResponseStrategy.LAST)
             .build();