【功能新增】AI：接入 minimax 和 moonshot 月之暗灭（kimi）

YunaiV
1 parent 99d5e7c5
Showing 7 changed files with 207 additions and 17 deletions
yudao-module-ai/yudao-spring-boot-starter-ai/pom.xml
yudao-module-ai/yudao-spring-boot-starter-ai/src/main/java/cn/iocoder/yudao/framework/ai/core/enums/AiPlatformEnum.java
yudao-module-ai/yudao-spring-boot-starter-ai/src/main/java/cn/iocoder/yudao/framework/ai/core/factory/AiModelFactoryImpl.java
yudao-module-ai/yudao-spring-boot-starter-ai/src/main/java/cn/iocoder/yudao/framework/ai/core/util/AiUtils.java
yudao-module-ai/yudao-spring-boot-starter-ai/src/test/java/cn/iocoder/yudao/framework/ai/chat/MiniMaxChatModelTests.java
yudao-module-ai/yudao-spring-boot-starter-ai/src/test/java/cn/iocoder/yudao/framework/ai/chat/MoonshotChatModelTests.java
yudao-server/src/main/resources/application.yaml
@@ -14,7 +14,6 @@
     <name>${project.artifactId}</name>
     <description>AI 大模型拓展，接入国内外大模型</description>
     <properties>
-        <spring-ai.groupId>org.springframework.ai</spring-ai.groupId>
         <spring-ai.version>1.0.0-M6</spring-ai.version>
     </properties>
@@ -26,22 +25,22 @@
         <!-- Spring AI Model 模型接入 -->
         <dependency>
-            <groupId>${spring-ai.groupId}</groupId>
+            <groupId>org.springframework.ai</groupId>
             <artifactId>spring-ai-openai-spring-boot-starter</artifactId>
             <version>${spring-ai.version}</version>
         </dependency>
         <dependency>
-            <groupId>${spring-ai.groupId}</groupId>
+            <groupId>org.springframework.ai</groupId>
             <artifactId>spring-ai-azure-openai-spring-boot-starter</artifactId>
             <version>${spring-ai.version}</version>
         </dependency>
         <dependency>
-            <groupId>${spring-ai.groupId}</groupId>
+            <groupId>org.springframework.ai</groupId>
             <artifactId>spring-ai-ollama-spring-boot-starter</artifactId>
             <version>${spring-ai.version}</version>
         </dependency>
         <dependency>
-            <groupId>${spring-ai.groupId}</groupId>
+            <groupId>org.springframework.ai</groupId>
             <artifactId>spring-ai-stability-ai-spring-boot-starter</artifactId>
             <version>${spring-ai.version}</version>
         </dependency>
@@ -53,28 +52,38 @@
         </dependency>
         <dependency>
             <!-- 文心一言 -->
-            <groupId>${spring-ai.groupId}</groupId>
+            <groupId>org.springframework.ai</groupId>
             <artifactId>spring-ai-qianfan-spring-boot-starter</artifactId>
             <version>${spring-ai.version}</version>
         </dependency>
         <dependency>
             <!-- 智谱 GLM -->
-            <groupId>${spring-ai.groupId}</groupId>
+            <groupId>org.springframework.ai</groupId>
             <artifactId>spring-ai-zhipuai-spring-boot-starter</artifactId>
             <version>${spring-ai.version}</version>
         </dependency>
+        <dependency>
+            <groupId>org.springframework.ai</groupId>
+            <artifactId>spring-ai-minimax-spring-boot-starter</artifactId>
+            <version>${spring-ai.version}</version>
+        </dependency>
+        <dependency>
+            <groupId>org.springframework.ai</groupId>
+            <artifactId>spring-ai-moonshot-spring-boot-starter</artifactId>
+            <version>${spring-ai.version}</version>
+        </dependency>
         <!-- 向量存储：https://db-engines.com/en/ranking/vector+dbms -->
         <dependency>
             <!-- Qdrant：https://qdrant.tech/ -->
-            <groupId>${spring-ai.groupId}</groupId>
+            <groupId>org.springframework.ai</groupId>
             <artifactId>spring-ai-qdrant-store</artifactId>
             <version>${spring-ai.version}</version>
         </dependency>
         <dependency>
             <!-- Redis：https://redis.io/docs/latest/develop/get-started/vector-database/ -->
-            <groupId>${spring-ai.groupId}</groupId>
+            <groupId>org.springframework.ai</groupId>
             <artifactId>spring-ai-redis-store</artifactId>
             <version>${spring-ai.version}</version>
         </dependency>
@@ -92,7 +101,7 @@
         <dependency>
             <!-- Tika：负责内容的解析 -->
-            <groupId>${spring-ai.groupId}</groupId>
+            <groupId>org.springframework.ai</groupId>
             <artifactId>spring-ai-tika-document-reader</artifactId>
             <version>${spring-ai.version}</version>
             <!-- TODO 芋艿：boot 项目里，不引入 cloud 依赖！！！另外，这样也是为了解决启动报错的问题！ -->
@@ -25,6 +25,8 @@ public enum AiPlatformEnum implements ArrayValuable&lt;String&gt; {
     DOU_BAO("DouBao", "豆包"), // 字节
     HUN_YUAN("HunYuan", "混元"), // 腾讯
     SILICON_FLOW("SiliconFlow", "硅基流动"), // 硅基流动
+    MINI_MAX("MiniMax", "MiniMax"), // 稀宇科技
+    MOONSHOT("Moonshot", "月之暗灭"), // KIMI
     // ========== 国外平台 ==========
@@ -36,6 +36,8 @@ import org.springframework.ai.autoconfigure.azure.openai.AzureOpenAiAutoConfigur
 import org.springframework.ai.autoconfigure.azure.openai.AzureOpenAiChatProperties;
 import org.springframework.ai.autoconfigure.azure.openai.AzureOpenAiConnectionProperties;
 import org.springframework.ai.autoconfigure.azure.openai.AzureOpenAiEmbeddingProperties;
+import org.springframework.ai.autoconfigure.minimax.MiniMaxAutoConfiguration;
+import org.springframework.ai.autoconfigure.moonshot.MoonshotAutoConfiguration;
 import org.springframework.ai.autoconfigure.ollama.OllamaAutoConfiguration;
 import org.springframework.ai.autoconfigure.openai.OpenAiAutoConfiguration;
 import org.springframework.ai.autoconfigure.qianfan.QianFanAutoConfiguration;
@@ -48,7 +50,6 @@ import org.springframework.ai.autoconfigure.vectorstore.qdrant.QdrantVectorStore
 import org.springframework.ai.autoconfigure.vectorstore.redis.RedisVectorStoreAutoConfiguration;
 import org.springframework.ai.autoconfigure.vectorstore.redis.RedisVectorStoreProperties;
 import org.springframework.ai.autoconfigure.zhipuai.ZhiPuAiAutoConfiguration;
-import org.springframework.ai.autoconfigure.zhipuai.ZhiPuAiConnectionProperties;
 import org.springframework.ai.azure.openai.AzureOpenAiChatModel;
 import org.springframework.ai.azure.openai.AzureOpenAiEmbeddingModel;
 import org.springframework.ai.chat.model.ChatModel;
@@ -56,6 +57,12 @@ import org.springframework.ai.document.MetadataMode;
 import org.springframework.ai.embedding.BatchingStrategy;
 import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.image.ImageModel;
+import org.springframework.ai.minimax.MiniMaxChatModel;
+import org.springframework.ai.minimax.MiniMaxEmbeddingModel;
+import org.springframework.ai.minimax.MiniMaxEmbeddingOptions;
+import org.springframework.ai.minimax.api.MiniMaxApi;
+import org.springframework.ai.moonshot.MoonshotChatModel;
+import org.springframework.ai.moonshot.api.MoonshotApi;
 import org.springframework.ai.ollama.OllamaChatModel;
 import org.springframework.ai.ollama.OllamaEmbeddingModel;
 import org.springframework.ai.ollama.api.OllamaApi;
@@ -130,6 +137,10 @@ public class AiModelFactoryImpl implements AiModelFactory {
                     return buildSiliconFlowChatModel(apiKey);
                 case ZHI_PU:
                     return buildZhiPuChatModel(apiKey, url);
+                case MINI_MAX:
+                    return buildMiniMaxChatModel(apiKey, url);
+                case MOONSHOT:
+                    return buildMoonshotChatModel(apiKey, url);
                 case XING_HUO:
                     return buildXingHuoChatModel(apiKey);
                 case OPENAI:
@@ -162,6 +173,10 @@ public class AiModelFactoryImpl implements AiModelFactory {
                 return SpringUtil.getBean(SiliconFlowChatModel.class);
             case ZHI_PU:
                 return SpringUtil.getBean(ZhiPuAiChatModel.class);
+            case MINI_MAX:
+                return SpringUtil.getBean(MiniMaxChatModel.class);
+            case MOONSHOT:
+                return SpringUtil.getBean(MoonshotChatModel.class);
             case XING_HUO:
                 return SpringUtil.getBean(XingHuoChatModel.class);
             case OPENAI:
@@ -242,6 +257,8 @@ public class AiModelFactoryImpl implements AiModelFactory {
                     return buildYiYanEmbeddingModel(apiKey, model);
                 case ZHI_PU:
                     return buildZhiPuEmbeddingModel(apiKey, url, model);
+                case MINI_MAX:
+                    return buildMiniMaxEmbeddingModel(apiKey, url, model);
                 case OPENAI:
                     return buildOpenAiEmbeddingModel(apiKey, url, model);
                 case AZURE_OPENAI:
@@ -365,8 +382,8 @@ public class AiModelFactoryImpl implements AiModelFactory {
      * 可参考 {@link ZhiPuAiAutoConfiguration} 的 zhiPuAiChatModel 方法
      */
     private ZhiPuAiChatModel buildZhiPuChatModel(String apiKey, String url) {
-        url = StrUtil.blankToDefault(url, ZhiPuAiConnectionProperties.DEFAULT_BASE_URL);
-        ZhiPuAiApi zhiPuAiApi = new ZhiPuAiApi(url, apiKey);
+        ZhiPuAiApi zhiPuAiApi = StrUtil.isEmpty(url) ? new ZhiPuAiApi(apiKey)
+                : new ZhiPuAiApi(url, apiKey);
         return new ZhiPuAiChatModel(zhiPuAiApi);
     }
@@ -374,12 +391,30 @@ public class AiModelFactoryImpl implements AiModelFactory {
      * 可参考 {@link ZhiPuAiAutoConfiguration} 的 zhiPuAiImageModel 方法
      */
     private ZhiPuAiImageModel buildZhiPuAiImageModel(String apiKey, String url) {
-        url = StrUtil.blankToDefault(url, ZhiPuAiConnectionProperties.DEFAULT_BASE_URL);
-        ZhiPuAiImageApi zhiPuAiApi = new ZhiPuAiImageApi(url, apiKey, RestClient.builder());
+        ZhiPuAiImageApi zhiPuAiApi = StrUtil.isEmpty(url) ? new ZhiPuAiImageApi(apiKey)
+                : new ZhiPuAiImageApi(url, apiKey, RestClient.builder());
         return new ZhiPuAiImageModel(zhiPuAiApi);
     }
     /**
+     * 可参考 {@link MiniMaxAutoConfiguration} 的 miniMaxChatModel 方法
+     */
+    private MiniMaxChatModel buildMiniMaxChatModel(String apiKey, String url) {
+        MiniMaxApi miniMaxApi = StrUtil.isEmpty(url) ? new MiniMaxApi(apiKey)
+                : new MiniMaxApi(url, apiKey);
+        return new MiniMaxChatModel(miniMaxApi);
+    }
+
+    /**
+     * 可参考 {@link MoonshotAutoConfiguration} 的 moonshotChatModel 方法
+     */
+    private MoonshotChatModel buildMoonshotChatModel(String apiKey, String url) {
+        MoonshotApi moonshotApi = StrUtil.isEmpty(url)? new MoonshotApi(apiKey)
+                : new MoonshotApi(url, apiKey);
+        return new MoonshotChatModel(moonshotApi);
+    }
+
+    /**
      * 可参考 {@link YudaoAiAutoConfiguration#xingHuoChatClient(YudaoAiProperties)}
      */
     private static XingHuoChatModel buildXingHuoChatModel(String key) {
@@ -454,13 +489,23 @@ public class AiModelFactoryImpl implements AiModelFactory {
      * 可参考 {@link ZhiPuAiAutoConfiguration} 的 zhiPuAiEmbeddingModel 方法
      */
     private ZhiPuAiEmbeddingModel buildZhiPuEmbeddingModel(String apiKey, String url, String model) {
-        url = StrUtil.blankToDefault(url, ZhiPuAiConnectionProperties.DEFAULT_BASE_URL);
-        ZhiPuAiApi zhiPuAiApi = new ZhiPuAiApi(url, apiKey);
+        ZhiPuAiApi zhiPuAiApi = StrUtil.isEmpty(url) ? new ZhiPuAiApi(apiKey)
+                : new ZhiPuAiApi(url, apiKey);
         ZhiPuAiEmbeddingOptions zhiPuAiEmbeddingOptions = ZhiPuAiEmbeddingOptions.builder().model(model).build();
         return new ZhiPuAiEmbeddingModel(zhiPuAiApi, MetadataMode.EMBED, zhiPuAiEmbeddingOptions);
     }
     /**
+     * 可参考 {@link MiniMaxAutoConfiguration} 的 miniMaxEmbeddingModel 方法
+     */
+    private EmbeddingModel buildMiniMaxEmbeddingModel(String apiKey, String url, String model) {
+        MiniMaxApi miniMaxApi = StrUtil.isEmpty(url)? new MiniMaxApi(apiKey)
+                : new MiniMaxApi(url, apiKey);
+        MiniMaxEmbeddingOptions miniMaxEmbeddingOptions = MiniMaxEmbeddingOptions.builder().model(model).build();
+        return new MiniMaxEmbeddingModel(miniMaxApi, MetadataMode.EMBED, miniMaxEmbeddingOptions);
+    }
+
+    /**
      * 可参考 {@link QianFanAutoConfiguration} 的 qianFanEmbeddingModel 方法
      */
     private QianFanEmbeddingModel buildYiYanEmbeddingModel(String key, String model) {
@@ -6,6 +6,8 @@ import com.alibaba.cloud.ai.dashscope.chat.DashScopeChatOptions;
 import org.springframework.ai.azure.openai.AzureOpenAiChatOptions;
 import org.springframework.ai.chat.messages.*;
 import org.springframework.ai.chat.prompt.ChatOptions;
+import org.springframework.ai.minimax.MiniMaxChatOptions;
+import org.springframework.ai.moonshot.MoonshotChatOptions;
 import org.springframework.ai.ollama.api.OllamaOptions;
 import org.springframework.ai.openai.OpenAiChatOptions;
 import org.springframework.ai.qianfan.QianFanChatOptions;
@@ -27,6 +29,10 @@ public class AiUtils {
                 return QianFanChatOptions.builder().model(model).temperature(temperature).maxTokens(maxTokens).build();
             case ZHI_PU:
                 return ZhiPuAiChatOptions.builder().model(model).temperature(temperature).maxTokens(maxTokens).build();
+            case MINI_MAX:
+                return MiniMaxChatOptions.builder().model(model).temperature(temperature).maxTokens(maxTokens).build();
+            case MOONSHOT:
+                return MoonshotChatOptions.builder().model(model).temperature(temperature).maxTokens(maxTokens).build();
             case OPENAI:
             case DEEP_SEEK: // 复用 OpenAI 客户端
             case DOU_BAO: // 复用 OpenAI 客户端
+package cn.iocoder.yudao.framework.ai.chat;
+
+import org.junit.jupiter.api.Disabled;
+import org.junit.jupiter.api.Test;
+import org.springframework.ai.chat.messages.Message;
+import org.springframework.ai.chat.messages.SystemMessage;
+import org.springframework.ai.chat.messages.UserMessage;
+import org.springframework.ai.chat.model.ChatResponse;
+import org.springframework.ai.chat.prompt.Prompt;
+import org.springframework.ai.minimax.MiniMaxChatModel;
+import org.springframework.ai.minimax.MiniMaxChatOptions;
+import org.springframework.ai.minimax.api.MiniMaxApi;
+import reactor.core.publisher.Flux;
+
+import java.util.ArrayList;
+import java.util.List;
+
+/**
+ * {@link MiniMaxChatModel} 的集成测试
+ *
+ * @author 芋道源码
+ */
+public class MiniMaxChatModelTests {
+
+    private final MiniMaxChatModel chatModel = new MiniMaxChatModel(
+            new MiniMaxApi("eyJhbGciOiJSUzI1NiIsInR5cCI6IkpXVCJ9.eyJHcm91cE5hbWUiOiLnjovmlofmlowiLCJVc2VyTmFtZSI6IueOi-aWh-aWjCIsIkFjY291bnQiOiIiLCJTdWJqZWN0SUQiOiIxODk3Mjg3MjQ5NDU2ODA4MzQ2IiwiUGhvbmUiOiIxNTYwMTY5MTM5OSIsIkdyb3VwSUQiOiIxODk3Mjg3MjQ5NDQ4NDE5NzM4IiwiUGFnZU5hbWUiOiIiLCJNYWlsIjoiIiwiQ3JlYXRlVGltZSI6IjIwMjUtMDMtMTEgMTI6NTI6MDIiLCJUb2tlblR5cGUiOjEsImlzcyI6Im1pbmltYXgifQ.aAuB7gWW_oA4IYhh-CF7c9MfWWxKN49B_HK-DYjXaDwwffhiG-H1571z1WQhp9QytWG-DqgLejneeSxkiq1wQIe3FsEP2wz4BmGBct31LehbJu8ehLxg_vg75Uod1nFAHbm5mZz6JSVLNIlSo87Xr3UtSzJhAXlapEkcqlA4YOzOpKrZ8l5_OJPTORTCmHWZYgJcRS-faNiH62ZnUEHUozesTFhubJHo5GfJCw_edlnmfSUocERV1BjWvenhZ9My-aYXNktcW9WaSj9l6gayV7A0Ium_PL55T9ln1PcI8gayiVUKJGJDoqNyF1AF9_aF9NOKtTnQzwNqnZdlTYH6hw"), // 密钥
+            MiniMaxChatOptions.builder()
+                    .model(MiniMaxApi.ChatModel.ABAB_6_5_G_Chat.getValue()) // 模型
+                    .build());
+    @Test
+    @Disabled
+    public void testCall() {
+        // 准备参数
+        List<Message> messages = new ArrayList<>();
+        messages.add(new SystemMessage("你是一个优质的文言文作者，用文言文描述着各城市的人文风景。"));
+        messages.add(new UserMessage("1 + 1 = ？"));
+
+        // 调用
+        ChatResponse response = chatModel.call(new Prompt(messages));
+        // 打印结果
+        System.out.println(response);
+        System.out.println(response.getResult().getOutput());
+    }
+
+    @Test
+    @Disabled
+    public void testStream() {
+        // 准备参数
+        List<Message> messages = new ArrayList<>();
+        messages.add(new SystemMessage("你是一个优质的文言文作者，用文言文描述着各城市的人文风景。"));
+        messages.add(new UserMessage("1 + 1 = ？"));
+
+        // 调用
+        Flux<ChatResponse> flux = chatModel.stream(new Prompt(messages));
+        // 打印结果
+        flux.doOnNext(response -> {
+//            System.out.println(response);
+            System.out.println(response.getResult().getOutput());
+        }).then().block();
+    }
+
+}
+package cn.iocoder.yudao.framework.ai.chat;
+
+import org.junit.jupiter.api.Disabled;
+import org.junit.jupiter.api.Test;
+import org.springframework.ai.chat.messages.Message;
+import org.springframework.ai.chat.messages.SystemMessage;
+import org.springframework.ai.chat.messages.UserMessage;
+import org.springframework.ai.chat.model.ChatResponse;
+import org.springframework.ai.chat.prompt.Prompt;
+import org.springframework.ai.moonshot.MoonshotChatModel;
+import org.springframework.ai.moonshot.MoonshotChatOptions;
+import org.springframework.ai.moonshot.api.MoonshotApi;
+import reactor.core.publisher.Flux;
+
+import java.util.ArrayList;
+import java.util.List;
+
+/**
+ * {@link org.springframework.ai.moonshot.MoonshotChatModel} 的集成测试
+ *
+ * @author 芋道源码
+ */
+public class MoonshotChatModelTests {
+
+    private final MoonshotChatModel chatModel = new MoonshotChatModel(
+            new MoonshotApi("sk-aHYYV1SARscItye5QQRRNbXij4fy65Ee7pNZlC9gsSQnUKXA"), // 密钥
+            MoonshotChatOptions.builder()
+                    .model("moonshot-v1-8k") // 模型
+                    .build());
+    @Test
+    @Disabled
+    public void testCall() {
+        // 准备参数
+        List<Message> messages = new ArrayList<>();
+        messages.add(new SystemMessage("你是一个优质的文言文作者，用文言文描述着各城市的人文风景。"));
+        messages.add(new UserMessage("1 + 1 = ？"));
+
+        // 调用
+        ChatResponse response = chatModel.call(new Prompt(messages));
+        // 打印结果
+        System.out.println(response);
+        System.out.println(response.getResult().getOutput());
+    }
+
+    @Test
+    @Disabled
+    public void testStream() {
+        // 准备参数
+        List<Message> messages = new ArrayList<>();
+        messages.add(new SystemMessage("你是一个优质的文言文作者，用文言文描述着各城市的人文风景。"));
+        messages.add(new UserMessage("1 + 1 = ？"));
+
+        // 调用
+        Flux<ChatResponse> flux = chatModel.stream(new Prompt(messages));
+        // 打印结果
+        flux.doOnNext(response -> {
+//            System.out.println(response);
+            System.out.println(response.getResult().getOutput());
+        }).then().block();
+    }
+
+}
@@ -184,6 +184,10 @@ spring:
       api-key: sk-e53UqbboF8QJCscYvzJscJxJXoFcFg4iJjl1oqgE7baJETmx
     dashscope: # 通义千问
       api-key: sk-71800982914041848008480000000000
+    minimax: # Minimax：https://www.minimaxi.com/
+      api-key: xxxx
+    moonshot: # 月之暗灭（KIMI）
+      api-key: sk-abc
 yudao:
   ai: