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

This commit is contained in:
YunaiV 2025-03-11 13:20:59 +08:00
parent 99d5e7c509
commit 07fe6167e0
7 changed files with 207 additions and 17 deletions
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29
yudao-module-ai/yudao-spring-boot-starter-ai/pom.xml
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@ -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！ -->

2
yudao-module-ai/yudao-spring-boot-starter-ai/src/main/java/cn/iocoder/yudao/framework/ai/core/enums/AiPlatformEnum.java
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@ -25,6 +25,8 @@ public enum AiPlatformEnum implements ArrayValuable<String> {
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 ==========

59
yudao-module-ai/yudao-spring-boot-starter-ai/src/main/java/cn/iocoder/yudao/framework/ai/core/factory/AiModelFactoryImpl.java
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@ -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);
}
@ -374,11 +391,29 @@ 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)}
*/
@ -454,12 +489,22 @@ 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
*/

6
yudao-module-ai/yudao-spring-boot-starter-ai/src/main/java/cn/iocoder/yudao/framework/ai/core/util/AiUtils.java
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@ -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

62
yudao-module-ai/yudao-spring-boot-starter-ai/src/test/java/cn/iocoder/yudao/framework/ai/chat/MiniMaxChatModelTests.java Normal file
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@ -0,0 +1,62 @@
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();
}
}

62
yudao-module-ai/yudao-spring-boot-starter-ai/src/test/java/cn/iocoder/yudao/framework/ai/chat/MoonshotChatModelTests.java Normal file
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@ -0,0 +1,62 @@
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();
}
}

4
yudao-server/src/main/resources/application.yaml
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@ -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: