Initial commit: Fintec AI Framework with Agent, RAG, and MCP modules
This commit is contained in:
limqsh
47
agent-demo/pom.xml
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47
agent-demo/pom.xml
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<?xml version="1.0" encoding="UTF-8"?>
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<project xmlns="http://maven.apache.org/POM/4.0.0"
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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.ccb.fintec</groupId>
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<artifactId>fintec-framework-parent</artifactId>
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<version>1.0.0</version>
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</parent>
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<artifactId>agent-demo</artifactId>
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<dependencies>
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<!-- Spring Boot Starter -->
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<dependency>
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<groupId>org.springframework.boot</groupId>
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<artifactId>spring-boot-starter-web</artifactId>
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</dependency>
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<!-- Agent Starter -->
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<dependency>
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<groupId>com.ccb.fintec</groupId>
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<artifactId>fintec-framework-agent-spring-boot-starter</artifactId>
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<version>${project.version}</version>
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</dependency>
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</dependencies>
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<build>
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<plugins>
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<plugin>
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<groupId>org.springframework.boot</groupId>
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<artifactId>spring-boot-maven-plugin</artifactId>
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<version>${spring-boot.version}</version>
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<executions>
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<execution>
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<goals>
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<goal>repackage</goal>
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</goals>
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</execution>
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</executions>
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</plugin>
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</plugins>
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</build>
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</project>
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package com.ccb.fintec.agent.demo;
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import org.springframework.boot.SpringApplication;
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import org.springframework.boot.autoconfigure.SpringBootApplication;
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@SpringBootApplication
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public class AgentDemoApplication {
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public static void main(String[] args) {
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SpringApplication.run(AgentDemoApplication.class, args);
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}
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}
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package com.ccb.fintec.agent.demo.controller;
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import com.ccb.fintec.agent.autoconfigure.template.AgentTemplate;
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import com.ccb.fintec.agent.demo.dto.UserInfo;
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import com.ccb.fintec.core.dto.AiResponse;
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import org.springframework.ai.chat.client.ChatClient;
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import org.springframework.web.bind.annotation.*;
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import reactor.core.publisher.Flux;
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import java.util.HashMap;
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import java.util.Map;
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/**
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* Agent 演示控制器 - 展示封装后的简化用法
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*
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* 核心优势：
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* 1. 自动使用公司统一的默认系统提示词
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* 2. 内置会话记忆，无需手动配置
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* 3. 支持所有常用场景：基础问答、流式、工具调用、多模态、结构化输出
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* 4. 提供逃生通道，可获取底层 ChatClient 进行高级定制
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*/
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@RestController
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@RequestMapping("/api/agent")
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public class AgentController {
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private final AgentTemplate agentTemplate;
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public AgentController(AgentTemplate agentTemplate) {
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this.agentTemplate = agentTemplate;
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}
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/**
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* 1. 最简单的问答 - 自动使用配置的默认系统提示词
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*
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* 示例：GET /api/agent/ask?question=什么是Spring AI?
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*/
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@GetMapping("/ask")
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public Map<String, Object> ask(@RequestParam String question) {
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// ✅ 只需一行代码，自动应用公司统一的系统提示词
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String answer = agentTemplate.ask(question);
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Map<String, Object> result = new HashMap<>();
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result.put("question", question);
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result.put("answer", answer);
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result.put("note", "使用了 fintec.ai.agent.default-system-prompt 配置的系统提示词");
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return result;
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}
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/**
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* 2. 带会话记忆的对话 - 自动管理上下文
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*
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* 示例：
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* GET /api/agent/ask-with-memory?conversationId=user123&question=我叫张三
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* GET /api/agent/ask-with-memory?conversationId=user123&question=我叫什么名字？
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*/
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@GetMapping("/ask-with-memory")
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public Map<String, Object> askWithMemory(
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@RequestParam String conversationId,
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@RequestParam String question) {
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// ✅ 自动使用会话记忆，无需手动配置 Advisor
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String answer = agentTemplate.ask(question, conversationId);
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Map<String, Object> result = new HashMap<>();
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result.put("conversationId", conversationId);
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result.put("question", question);
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result.put("answer", answer);
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result.put("note", "自动使用 MessageWindowChatMemory，窗口大小由 fintec.ai.agent.memory-window-size 配置");
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return result;
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}
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/**
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* 3. 自定义系统提示词的问答
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*
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* 示例：GET /api/agent/ask-custom?systemPrompt=你是数学老师&conversationId=math01&question=1+1=?
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*/
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@GetMapping("/ask-custom")
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public Map<String, Object> askCustom(
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@RequestParam String systemPrompt,
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@RequestParam String conversationId,
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@RequestParam String question) {
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String answer = agentTemplate.ask(systemPrompt, question, conversationId);
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Map<String, Object> result = new HashMap<>();
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result.put("systemPrompt", systemPrompt);
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result.put("conversationId", conversationId);
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result.put("question", question);
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result.put("answer", answer);
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return result;
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}
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/**
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* 4. 结构化输出 - AI 自动填充 Java 对象
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*
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* 示例：GET /api/agent/ask-for-object?question=生成一个用户信息，姓名李四，年龄25岁，邮箱lisi@example.com
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*/
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@GetMapping("/ask-for-object")
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public UserInfo askForObject(@RequestParam String question) {
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// ✅ AI 自动将回答转换为 UserInfo 对象
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return agentTemplate.askForObject(question, UserInfo.class);
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}
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/**
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* 5. 带元数据的问答（包含 Token 使用量、耗时等）
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*
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* 示例：GET /api/agent/ask-with-metadata?question=解释一下量子计算
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*/
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@GetMapping("/ask-with-metadata")
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public AiResponse askWithMetadata(@RequestParam String question) {
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// ✅ 自动收集 Token 使用量、耗时等元数据
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return agentTemplate.askWithMetadata(question);
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}
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/**
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* 6. 流式输出 - Server-Sent Events
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*
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* 示例：curl -N http://localhost:8083/api/agent/stream?question=讲个故事
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*/
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@GetMapping(value = "/stream", produces = "text/event-stream")
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public Flux<String> stream(@RequestParam String question) {
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// ✅ 自动应用默认系统提示词
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return agentTemplate.stream(question);
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}
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/**
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* 7. 带会话记忆的流式输出
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*
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* 示例：curl -N "http://localhost:8083/api/agent/stream-with-memory?conversationId=user123&question=继续"
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*/
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@GetMapping(value = "/stream-with-memory", produces = "text/event-stream")
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public Flux<String> streamWithMemory(
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@RequestParam String conversationId,
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@RequestParam String question) {
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// ✅ 流式 + 记忆组合
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return agentTemplate.stream(question, conversationId);
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}
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/**
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* 8. 逃生通道：获取底层 ChatClient 进行高级定制
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*
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* 示例：GET /api/agent/advanced-usage?question=测试高级用法
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*/
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@GetMapping("/advanced-usage")
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public Map<String, Object> advancedUsage(@RequestParam String question) {
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// ✅ 获取底层 ChatClient，完全自定义
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ChatClient client = agentTemplate.getChatClient();
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String answer = client.prompt()
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.system("完全自定义的系统提示词")
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.user(question)
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.call()
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.content();
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Map<String, Object> result = new HashMap<>();
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result.put("question", question);
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result.put("answer", answer);
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result.put("note", "通过 getChatClient() 获取底层对象，进行高级定制");
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return result;
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}
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/**
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* 9. 健康检查
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*/
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@GetMapping("/health")
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public Map<String, Object> health() {
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Map<String, Object> result = new HashMap<>();
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result.put("status", "UP");
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result.put("service", "Agent Demo");
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result.put("features", new String[]{
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"基础问答",
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"会话记忆（JDBC/内存自动选择）",
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"流式输出",
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"结构化输出",
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"工具调用",
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"多模态支持",
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"元数据收集",
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"逃生通道"
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});
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return result;
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}
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}
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package com.ccb.fintec.agent.demo.controller;
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import org.springframework.http.*;
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import org.springframework.web.bind.annotation.GetMapping;
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import org.springframework.web.bind.annotation.RequestMapping;
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import org.springframework.web.bind.annotation.RequestParam;
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import org.springframework.web.bind.annotation.RestController;
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import org.springframework.web.client.RestTemplate;
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import java.util.HashMap;
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import java.util.List;
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import java.util.Map;
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/**
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* 直接测试 OpenRouter API，不经过 Spring AI
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*/
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@RestController
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@RequestMapping("/api/test")
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public class DirectOpenRouterTestController {
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@GetMapping("/openrouter")
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public Map<String, Object> testDirectCall(@RequestParam(defaultValue = "你好") String question) {
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String apiKey = "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";
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String baseUrl = "https://openrouter.ai/api/v1/chat/completions";
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// 构造请求体（与 Python 相同）
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Map<String, Object> requestBody = new HashMap<>();
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requestBody.put("model", "openrouter/free");
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requestBody.put("messages", List.of(
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Map.of("role", "system", "content", "你是一个助手"),
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Map.of("role", "user", "content", question)
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));
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// 构造请求头
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HttpHeaders headers = new HttpHeaders();
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headers.setContentType(MediaType.APPLICATION_JSON);
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headers.setBearerAuth(apiKey);
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// OpenRouter 推荐的 headers
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headers.set("HTTP-Referer", "http://localhost:8083");
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headers.set("X-Title", "Fintec Agent Demo");
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HttpEntity<Map<String, Object>> entity = new HttpEntity<>(requestBody, headers);
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RestTemplate restTemplate = new RestTemplate();
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try {
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ResponseEntity<Map> response = restTemplate.exchange(
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baseUrl,
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HttpMethod.POST,
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entity,
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Map.class
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);
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Map<String, Object> result = new HashMap<>();
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result.put("success", true);
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result.put("statusCode", response.getStatusCode());
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result.put("body", response.getBody());
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return result;
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} catch (Exception e) {
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Map<String, Object> result = new HashMap<>();
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result.put("success", false);
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result.put("error", e.getMessage());
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return result;
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}
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}
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}
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@@ -0,0 +1,63 @@
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package com.ccb.fintec.agent.demo.dto;
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/**
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* 用户信息 DTO（用于结构化输出示例）
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*/
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public class UserInfo {
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private String name;
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private Integer age;
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private String email;
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private String occupation;
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public UserInfo() {}
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public UserInfo(String name, Integer age, String email, String occupation) {
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this.name = name;
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this.age = age;
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this.email = email;
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this.occupation = occupation;
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}
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// Getters and Setters
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public String getName() {
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return name;
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}
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public void setName(String name) {
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this.name = name;
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}
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public Integer getAge() {
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return age;
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}
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public void setAge(Integer age) {
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this.age = age;
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}
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public String getEmail() {
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return email;
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}
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public void setEmail(String email) {
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this.email = email;
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}
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public String getOccupation() {
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return occupation;
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}
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public void setOccupation(String occupation) {
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this.occupation = occupation;
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}
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@Override
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public String toString() {
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return "UserInfo{" +
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"name='" + name + '\'' +
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", age=" + age +
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", email='" + email + '\'' +
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", occupation='" + occupation + '\'' +
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'}';
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}
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}
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59
agent-demo/src/main/resources/application.properties
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59
agent-demo/src/main/resources/application.properties
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# ============================================
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# 服务器配置
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# ============================================
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server.port=8083
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# ============================================
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# 模型配置（业务系统根据需求选择模型提供商）
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# ============================================
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spring.ai.openai.api-key=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
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# Spring AI OpenAI starter 会自动追加 /v1/chat/completions，所以 base-url 只需要到 /api
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spring.ai.openai.base-url=https://openrouter.ai/api
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# 使用 openrouter/free 自动路由到免费模型
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spring.ai.openai.chat.options.model=openrouter/free
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# 单次请求最大 Token 数（Spring AI 原生配置）
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spring.ai.openai.chat.options.max-tokens=2048
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# ============================================
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# Agent 模块配置
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# ============================================
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# 默认系统提示词：定义 AI 助手的人设和行为准则
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fintec.ai.agent.default-system-prompt=你是一个专业的订单助手，请用中文简洁准确地回答订单相关问题。
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# 对话记忆窗口大小：保留最近 N 条消息作为上下文
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fintec.ai.agent.memory-window-size=15
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# ============================================
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# 安全防护配置
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# ============================================
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# 启用安全关键词过滤
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fintec.ai.safety.enabled=true
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# 需要拦截的敏感关键词列表
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fintec.ai.safety.block-keywords[0]=暴力
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fintec.ai.safety.block-keywords[1]=色情
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fintec.ai.safety.block-keywords[2]=赌博
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# ============================================
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# 限流配置（成本控制）
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# ============================================
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# 每分钟最大请求数
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fintec.ai.rate-limit.max-requests-per-minute=30
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# ============================================
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# 重试策略配置
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# ============================================
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# 启用自动重试
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fintec.ai.retry.enabled=true
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# 最大重试次数
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fintec.ai.retry.max-attempts=2
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# 重试退避时间（毫秒）
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fintec.ai.retry.backoff-ms=500
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# ============================================
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# 日志配置
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# ============================================
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logging.level.root=INFO
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logging.level.com.ccb.fintec=DEBUG
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# 启用 Spring AI 和 HTTP 客户端的详细日志
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logging.level.org.springframework.ai=DEBUG
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logging.level.org.springframework.web.client=DEBUG
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logging.level.io.micrometer.common.util.internal.logging=OFF
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