feat(ai): 集成多种大模型并支持会话记忆功能

- 新增 Ollama、智谱 AI 和 OpenAI 大模型接入配置- 实现基于 ChatMemory 的会话上下文管理
- 添加流式输出接口以提升响应体验
- 更新加密工具类密钥及测试数据
- 引入多个 AI 控制器用于不同模型的服务调用
- 在 pom.xml 中添加相关依赖项以支持多模型集成

src/main/java/com/hanserwei/airobot/config/ChatClientConfig.java

@@ -1,14 +1,19 @@
 package com.hanserwei.airobot.config;
 
 import com.hanserwei.airobot.advisor.MyLoggerAdvisor;
+import jakarta.annotation.Resource;
 import org.springframework.ai.chat.client.ChatClient;
+import org.springframework.ai.chat.client.advisor.MessageChatMemoryAdvisor;
 import org.springframework.ai.chat.client.advisor.SimpleLoggerAdvisor;
+import org.springframework.ai.chat.memory.ChatMemory;
 import org.springframework.ai.deepseek.DeepSeekChatModel;
 import org.springframework.context.annotation.Bean;
 import org.springframework.context.annotation.Configuration;
 
 @Configuration
 public class ChatClientConfig {
+    @Resource
+    private ChatMemory chatMemory;
 
     /**
      * 初始化 ChatClient 客户端

src/main/java/com/hanserwei/airobot/config/ChatMemoryConfig.java

@@ -0,0 +1,30 @@
+package com.hanserwei.airobot.config;
+
+import jakarta.annotation.Resource;
+import org.springframework.ai.chat.memory.ChatMemory;
+import org.springframework.ai.chat.memory.ChatMemoryRepository;
+import org.springframework.ai.chat.memory.MessageWindowChatMemory;
+import org.springframework.context.annotation.Bean;
+import org.springframework.context.annotation.Configuration;
+
+@Configuration
+public class ChatMemoryConfig {
+
+    /**
+     * 记忆存储
+     */
+    @Resource
+    private ChatMemoryRepository chatMemoryRepository;
+
+    /**
+     * 初始化一个 ChatMemory 实例，并注入到 Spring 容器中
+     * @return ChatMemory
+     */
+    @Bean
+    public ChatMemory chatMemory() {
+        return MessageWindowChatMemory.builder()
+                .maxMessages(50) // 最大消息窗口为 50，默认值为 20
+                .chatMemoryRepository(chatMemoryRepository) // 记忆存储
+                .build();
+    }
+}

src/main/java/com/hanserwei/airobot/controller/ChatClientController.java

@@ -2,6 +2,7 @@ package com.hanserwei.airobot.controller;
 
 import jakarta.annotation.Resource;
 import org.springframework.ai.chat.client.ChatClient;
+import org.springframework.ai.chat.memory.ChatMemory;
 import org.springframework.web.bind.annotation.GetMapping;
 import org.springframework.web.bind.annotation.RequestMapping;
 import org.springframework.web.bind.annotation.RequestParam;
@@ -36,9 +37,11 @@ public class ChatClientController {
      * @return 对话结果
      */
     @GetMapping(value = "/generateStream", produces = "text/html;charset=utf-8")
-    public Flux<String> generateStream(@RequestParam(value = "message", defaultValue = "你是谁？") String message) {
+    public Flux<String> generateStream(@RequestParam(value = "message", defaultValue = "你是谁？") String message,
+                                       @RequestParam(value = "chatId") String chatId) {
         return chatClient.prompt()
                 .user(message) // 提示词
+                .advisors(a -> a.param(ChatMemory.CONVERSATION_ID, chatId))
                 .stream() // 流式输出
                 .content();
 

src/main/java/com/hanserwei/airobot/controller/OllamaController.java

@@ -0,0 +1,33 @@
+package com.hanserwei.airobot.controller;
+
+import jakarta.annotation.Resource;
+import org.springframework.ai.chat.model.ChatResponse;
+import org.springframework.ai.chat.prompt.Prompt;
+import org.springframework.ai.ollama.OllamaChatModel;
+import org.springframework.web.bind.annotation.GetMapping;
+import org.springframework.web.bind.annotation.RequestMapping;
+import org.springframework.web.bind.annotation.RequestParam;
+import org.springframework.web.bind.annotation.RestController;
+
+@RestController
+@RequestMapping("/v3/ai")
+public class OllamaController {
+
+    @Resource
+    private OllamaChatModel chatModel;
+
+    /**
+     * 普通对话
+     * @param message 对话输入内容
+     * @return 对话结果
+     */
+    @GetMapping("/generate")
+    public String generate(@RequestParam(value = "message", defaultValue = "你是谁？") String message) {
+        // 构建提示词，调用大模型
+        ChatResponse chatResponse = chatModel.call(new Prompt(message));
+
+        // 响应回答内容
+        return chatResponse.getResult().getOutput().getText();
+    }
+
+}

src/main/java/com/hanserwei/airobot/controller/OpenAIController.java

@@ -0,0 +1,53 @@
+package com.hanserwei.airobot.controller;
+
+import jakarta.annotation.Resource;
+import org.springframework.ai.chat.messages.UserMessage;
+import org.springframework.ai.chat.model.Generation;
+import org.springframework.ai.chat.prompt.Prompt;
+import org.springframework.ai.openai.OpenAiChatModel;
+import org.springframework.web.bind.annotation.GetMapping;
+import org.springframework.web.bind.annotation.RequestMapping;
+import org.springframework.web.bind.annotation.RequestParam;
+import org.springframework.web.bind.annotation.RestController;
+import reactor.core.publisher.Flux;
+
+import java.util.Objects;
+
+@RestController
+@RequestMapping("/v5/ai")
+public class OpenAIController {
+
+    @Resource
+    private OpenAiChatModel chatModel;
+
+    /**
+     * 普通对话
+     * @param message 对话输入内容
+     * @return 对话结果
+     */
+    @GetMapping("/generate")
+    public String generate(@RequestParam(value = "message", defaultValue = "你是谁？") String message) {
+        // 一次性返回结果
+        return chatModel.call(message);
+    }
+
+    /**
+     * 流式对话
+     * @param message 对话输入内容
+     * @return 对话结果
+     */
+    @GetMapping(value = "/generateStream", produces = "text/html;charset=utf-8")
+    public Flux<String> generateStream(@RequestParam(value = "message", defaultValue = "你是谁？") String message) {
+        // 构建提示词
+        Prompt prompt = new Prompt(new UserMessage(message));
+
+        // 流式输出
+        return chatModel.stream(prompt)
+                .mapNotNull(chatResponse -> {
+                    Generation generation = chatResponse.getResult();
+                    return generation.getOutput().getText();
+                });
+
+    }
+
+}

src/main/java/com/hanserwei/airobot/controller/ZhiPuController.java

@@ -0,0 +1,47 @@
+package com.hanserwei.airobot.controller;
+
+import jakarta.annotation.Resource;
+import org.springframework.ai.chat.messages.UserMessage;
+import org.springframework.ai.chat.prompt.Prompt;
+import org.springframework.ai.zhipuai.ZhiPuAiChatModel;
+import org.springframework.web.bind.annotation.GetMapping;
+import org.springframework.web.bind.annotation.RequestMapping;
+import org.springframework.web.bind.annotation.RequestParam;
+import org.springframework.web.bind.annotation.RestController;
+import reactor.core.publisher.Flux;
+
+@RestController
+@RequestMapping("/v4/ai")
+public class ZhiPuController {
+
+    @Resource
+    private ZhiPuAiChatModel chatModel;
+
+    /**
+     * 普通对话
+     * @param message 对话输入内容
+     * @return 对话结果
+     */
+    @GetMapping("/generate")
+    public String generate(@RequestParam(value = "message", defaultValue = "你是谁？") String message) {
+        // 一次性返回结果
+        return chatModel.call(message);
+    }
+
+    /**
+     * 流式对话
+     * @param message 对话输入内容
+     * @return 对话结果
+     */
+    @GetMapping(value = "/generateStream", produces = "text/html;charset=utf-8")
+    public Flux<String> generateStream(@RequestParam(value = "message", defaultValue = "你是谁？") String message) {
+        // 构建提示词
+        Prompt prompt = new Prompt(new UserMessage(message));
+
+        // 流式输出
+        return chatModel.stream(prompt)
+                .mapNotNull(chatResponse -> chatResponse.getResult().getOutput().getText());
+
+    }
+
+}

src/main/java/com/hanserwei/airobot/utils/EncryptorUtil.java

@@ -5,7 +5,7 @@ import org.jasypt.util.text.AES256TextEncryptor;
 public class EncryptorUtil {
     public static void main(String[] args) {
         AES256TextEncryptor textEncryptor = new AES256TextEncryptor();
-        textEncryptor.setPassword("password");
-        System.out.println(textEncryptor.encrypt("sk-xxxxxxxxxxxxxx"));
+        textEncryptor.setPassword("hanserwei");
+        System.out.println(textEncryptor.encrypt("sk-QXBlsyIonybNTcG5tt5GvmMpg2WpdMLPTvU55TXrt9urWpL8"));
     }
 }