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add orchestrator workflow
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‎spring-ai-agent/pom.xml‎

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<modules>
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<module>spring-ai-workflow</module>
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<module>spring-ai-agent-orchestrator</module>
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</modules>
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</project>

‎spring-ai-agent/spring-ai-agent-orchestrator/pom.xml‎

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<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
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xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
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<modelVersion>4.0.0</modelVersion>
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<parent>
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<groupId>com.glmapper</groupId>
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<artifactId>spring-ai-agent</artifactId>
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<version>0.0.1</version>
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</parent>
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<artifactId>spring-ai-agent-orchestrator</artifactId>
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<packaging>jar</packaging>
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<name>spring-ai-agent-orchestrator</name>
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<dependencies>
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<dependency>
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<groupId>org.springframework.ai</groupId>
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<artifactId>spring-ai-starter-model-openai</artifactId>
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</dependency>
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<dependency>
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<groupId>org.springframework.boot</groupId>
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<artifactId>spring-boot-starter-test</artifactId>
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<scope>test</scope>
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</dependency>
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</dependencies>
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</project>

‎spring-ai-agent/spring-ai-agent-orchestrator/src/main/java/com/glmapper/ai/workflow/OrchestratorWorkersWorkflowApplication.java‎

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package com.glmapper.ai.workflow;
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import org.springframework.boot.SpringApplication;
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import org.springframework.boot.autoconfigure.SpringBootApplication;
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/**
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* Hello world!
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*/
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@SpringBootApplication
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public class OrchestratorWorkersWorkflowApplication {
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public static void main(String[] args) {
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SpringApplication.run(OrchestratorWorkersWorkflowApplication.class, args);
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}
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}

‎spring-ai-agent/spring-ai-agent-orchestrator/src/main/java/com/glmapper/ai/workflow/config/OpenaiChatClientConfigs.java‎

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package com.glmapper.ai.workflow.config;
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import org.springframework.ai.chat.client.ChatClient;
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import org.springframework.ai.openai.OpenAiChatModel;
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import org.springframework.context.annotation.Bean;
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import org.springframework.context.annotation.Configuration;
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/**
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* @Classname OpenaiChatClientConfigs
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* @Description 注入 ChatClient
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*
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* @Date 2025/6/10 09:23
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* @Created by Gepeng18
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*/
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@Configuration
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public class OpenaiChatClientConfigs {
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/**
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* 注入ChatClient
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*
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* @param chatModel
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* @return
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*/
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@Bean
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public ChatClient chatClient(OpenAiChatModel chatModel) {
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return ChatClient.builder(chatModel)
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.build();
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}
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}

‎spring-ai-agent/spring-ai-agent-orchestrator/src/main/java/com/glmapper/ai/workflow/workflow/OrchestratorWorkersWorkflow.java‎

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package com.glmapper.ai.workflow.workflow;
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import com.fasterxml.jackson.core.type.TypeReference;
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import com.fasterxml.jackson.databind.ObjectMapper;
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import com.glmapper.ai.workflow.workflow.model.WorkflowResponse;
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import org.springframework.ai.chat.client.ChatClient;
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import org.springframework.ai.chat.messages.SystemMessage;
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import org.springframework.ai.chat.messages.UserMessage;
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import org.springframework.ai.chat.prompt.Prompt;
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import org.springframework.beans.factory.annotation.Autowired;
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import org.springframework.stereotype.Component;
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import java.util.Arrays;
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import java.util.List;
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import java.util.concurrent.CompletableFuture;
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import java.util.stream.Collectors;
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/**
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* @Classname OrchestratorWorkersWorkflow
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* @Description Orchestrator 用大模型拆解任务，Worker 并行处理，合并结果
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* @Date 2025/6/12 20:19
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* @Created by glmapper
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*/
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@Component
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public class OrchestratorWorkersWorkflow {
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@Autowired
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private ChatClient chatClient;
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private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
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public WorkflowResponse process(String taskDescription) {
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try {
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// 1. 用大模型拆解任务
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LlmSubtaskResult subtaskResult = callLlmForSubtasks(taskDescription);
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List<String> subtasks = subtaskResult.subtasks;
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String analysis = subtaskResult.analysis;
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if (subtasks == null || subtasks.isEmpty()) {
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return WorkflowResponse.builder()
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.success(false)
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.errorMessage("大模型未能拆解出子任务")
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.analysis(analysis)
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.subtasks(subtasks)
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.build();
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}
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// 2. Workers process subtasks in parallel
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List<String> workerResponses = subtasks.stream()
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.map(subtask -> CompletableFuture.supplyAsync(() -> workerProcess(subtask)))
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.collect(Collectors.toList())
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.stream()
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.map(CompletableFuture::join)
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.collect(Collectors.toList());
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// 3. Results are combined into final response
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String combined = String.join("\n", workerResponses);
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return WorkflowResponse.builder()
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.content(combined)
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.success(true)
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.analysis(analysis)
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.subtasks(subtasks)
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.workerResponses(workerResponses)
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.build();
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} catch (Exception e) {
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return WorkflowResponse.builder()
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.success(false)
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.errorMessage("Orchestrator/Worker 执行失败: " + e.getMessage())
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.build();
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}
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}
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// 用大模型拆解任务，返回原始分析和子任务列表
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private LlmSubtaskResult callLlmForSubtasks(String taskDescription) throws Exception {
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List messages = List.of(new SystemMessage("你是一个任务拆解专家。请将用户输入的复杂任务描述拆解为若干可以独立执行的子任务，输出格式为 JSON 数组，每个元素为一个子任务字符串。"), new UserMessage(taskDescription));
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Prompt prompt = new Prompt(messages);
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String modelResult = chatClient.prompt(prompt).call().content();
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// 解析为 List<String>
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List<String> subtasks;
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try {
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subtasks = OBJECT_MAPPER.readValue(modelResult, new TypeReference<List<String>>() {
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});
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} catch (Exception e) {
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// 容错：如果模型返回不是严格 JSON 数组，尝试简单分割
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subtasks = Arrays.stream(modelResult.split("[。,.，\n]"))
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.map(String::trim)
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.filter(s -> !s.isEmpty())
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.collect(Collectors.toList());
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}
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return new LlmSubtaskResult(modelResult, subtasks);
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}
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// 内部类：封装大模型分析结果
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private record LlmSubtaskResult(String analysis, List<String> subtasks) {
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}
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private String workerProcess(String subtask) {
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try {
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// 你可以根据业务自定义 system prompt
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String systemPrompt = "你是一个高效的AI助手，请认真完成以下子任务：";
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List messages = List.of(new SystemMessage(systemPrompt), new UserMessage(subtask));
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Prompt prompt = new Prompt(messages);
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// 直接用 chatClient 让大模型"执行"子任务
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return chatClient.prompt(prompt).call().content();
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} catch (Exception e) {
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// 失败时返回错误信息，便于排查
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return "[Worker Error] " + e.getMessage();
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}
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}
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}

‎spring-ai-agent/spring-ai-agent-orchestrator/src/main/java/com/glmapper/ai/workflow/workflow/model/WorkflowRequest.java‎

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package com.glmapper.ai.workflow.workflow.model;
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import lombok.Builder;
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import lombok.Data;
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/**
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* @Classname WorkflowRequest
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* @Description 用户请求
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*
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* @Date 2025/6/10 11:23
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* @Created by Gepeng18
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*/
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@Data
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@Builder
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public class WorkflowRequest {
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/**
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* 请求内容
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*/
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private String question;
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}

‎spring-ai-agent/spring-ai-agent-orchestrator/src/main/java/com/glmapper/ai/workflow/workflow/model/WorkflowResponse.java‎

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package com.glmapper.ai.workflow.workflow.model;
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import lombok.Builder;
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import lombok.Data;
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/**
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* @Classname WorkflowResponse
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* @Description 工作流响应
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*
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* @Date 2025/6/10 14:32
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* @Created by Gepeng18
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*/
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@Data
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@Builder
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public class WorkflowResponse {
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/**
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* 大模型对任务的分析/拆解原始输出
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*/
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private String analysis;
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/**
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* 拆解出的所有子任务
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*/
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private java.util.List<String> subtasks;
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/**
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* 每个 worker 的输出结果
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*/
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private java.util.List<String> workerResponses;
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/**
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* 最终合成的内容（如汇总、总结、最终答案等）
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*/
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private String content;
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/**
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* 总体是否成功
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*/
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private boolean success;
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/**
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* 错误信息（如有）
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*/
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private String errorMessage;
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}

‎spring-ai-agent/spring-ai-agent-orchestrator/src/main/resources/application.yml‎

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server:
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port: 8080
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spring:
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application:
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name: spring-ai-workflow-orchestrator
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ai:
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openai:
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api-key: ${OPENAI_API_KEY}
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base-url: https://api.deepseek.com
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chat:
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options:
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model: deepseek-chat
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temperature: 0.7
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completions-path: /v1/chat/completions

‎spring-ai-agent/spring-ai-agent-orchestrator/src/test/java/com/glmapper/ai/workflow/OrchestratorWorkersWorkflowTest.java‎

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package com.glmapper.ai.workflow;
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import com.glmapper.ai.workflow.workflow.OrchestratorWorkersWorkflow;
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import com.glmapper.ai.workflow.workflow.model.WorkflowResponse;
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import org.junit.jupiter.api.Test;
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import org.springframework.beans.factory.annotation.Autowired;
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import org.springframework.boot.test.context.SpringBootTest;
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/**
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* Unit test for simple App.
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*/
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@SpringBootTest(classes = OrchestratorWorkersWorkflowApplication.class, webEnvironment = SpringBootTest.WebEnvironment.RANDOM_PORT)
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public class OrchestratorWorkersWorkflowTest {
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@Autowired
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private OrchestratorWorkersWorkflow orchestratorWorkersWorkflow;
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@Test
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public void test() {
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WorkflowResponse response = orchestratorWorkersWorkflow.process("Generate both technical and user-friendly documentation for a REST API endpoint");
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System.out.println("Analysis: " + response.getAnalysis());
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System.out.println("Worker Outputs: " + response.getWorkerResponses());
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}
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}

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