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

pom.xml

@@ -35,6 +35,23 @@
             <groupId>org.springframework.ai</groupId>
             <artifactId>spring-ai-starter-model-deepseek</artifactId>
         </dependency>
+        <!-- Ollama -->
+        <dependency>
+            <groupId>org.springframework.ai</groupId>
+            <artifactId>spring-ai-starter-model-ollama</artifactId>
+        </dependency>
+        <!-- 智谱AI -->
+        <dependency>
+            <groupId>org.springframework.ai</groupId>
+            <artifactId>spring-ai-starter-model-zhipuai</artifactId>
+        </dependency>
+        <!-- OpenAI -->
+        <dependency>
+            <groupId>org.springframework.ai</groupId>
+            <artifactId>spring-ai-starter-model-openai</artifactId>
+        </dependency>
+
+
 
         <dependency>
             <groupId>org.springframework.boot</groupId>

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");
+        textEncryptor.setPassword("hanserwei");
-        System.out.println(textEncryptor.encrypt("sk-xxxxxxxxxxxxxx"));
+        System.out.println(textEncryptor.encrypt("sk-QXBlsyIonybNTcG5tt5GvmMpg2WpdMLPTvU55TXrt9urWpL8"));
     }
 }

src/main/resources/application.yml

@@ -10,6 +10,27 @@ spring:
         options:
           model: deepseek-chat # 使用哪个模型
           temperature: 0.8 # 温度值
+    ollama:
+      base-url: http://localhost:11434 # Ollama 服务的访问地址, 11434 端口是 Ollama 默认的启动端口
+      chat:
+        options: # 模型参数
+          model: qwen3:14b # 指定 Ollama 使用的大模型名称，根据你实际安装的来，我运行的是 14b
+          temperature: 0.7 # 温度值
+    zhipuai:
+      base-url: https://open.bigmodel.cn/api/paas # 智谱 AI 的请求 URL, 可不填，默认值为 open.bigmodel.cn/api/paas
+      api-key: ENC(Rz1O0AygSzG3q4UrIpIPHRwFoTQXCUZkWZ54vNzl1kgdBkQECzCYa3LoOADM9NlGLlAwCKTMtkj0nd6cP98T59DohcKtzc3iYyiAoNRfH0rsiu483CpaCciyMwxCUi5O) # 填写智谱 AI 的 API Key, 该成你自己的
+      chat:
+        options: # 模型参数
+          model: GLM-4.6          # 模型名称，使用智谱 AI 哪个模型
+          temperature: 0.7 # 温度值
+    openai:
+      base-url: https://api.master-jsx.top # OpenAI 服务的访问地址，这里使用的第三方代理商：智增增
+      api-key: ENC(D6ETp0VBeDYXvM612dcoGkyHaGUcPuwOVuSLtL92TOCxydyMKXL7/VBndWjFkxAQP/AS7TeQeegla+Ny6TrLStwdJtd28mVhoyf2YsKuXIdRnKF/mv8/uZ0MpzMdv9YR)  # 填写智增增的 API Key, 该成你自己的
+      chat:
+        options:
+          model: gpt-4o # 模型名称
+          temperature: 0.7 # 温度值
+
 jasypt:
   encryptor:
     password: ${jasypt.encryptor.password}