feat：【AI 大模型】依赖 spring ai 升级到 1.0.0

yudao-module-ai/yudao-module-ai-server/pom.xml

@@ -14,11 +14,12 @@
     <description>
         ai 模块下，接入 LLM 大模型，支持聊天、绘图、音乐、写作、思维导图等功能。
         目前已接入各种模型，不限于：
-        国内：通义千问、文心一言、讯飞星火、智谱 GLM、DeepSeek
-        国外：OpenAI、Ollama、Midjourney、StableDiffusion、Suno
+          国内：通义千问、文心一言、讯飞星火、智谱 GLM、DeepSeek
+          国外：OpenAI、Ollama、Midjourney、StableDiffusion、Suno
     </description>
     <properties>
-        <spring-ai.version>1.0.0-M6</spring-ai.version>
+        <spring-ai.version>1.0.0</spring-ai.version>
+        <alibaba-ai.version>1.0.0.2</alibaba-ai.version>
         <tinyflow.version>1.0.2</tinyflow.version>
     </properties>
 
@@ -110,65 +111,73 @@
         <!-- Spring AI Model 模型接入 -->
         <dependency>
             <groupId>org.springframework.ai</groupId>
-            <artifactId>spring-ai-openai-spring-boot-starter</artifactId>
+            <artifactId>spring-ai-starter-model-openai</artifactId>
             <version>${spring-ai.version}</version>
         </dependency>
         <dependency>
             <groupId>org.springframework.ai</groupId>
-            <artifactId>spring-ai-azure-openai-spring-boot-starter</artifactId>
+            <artifactId>spring-ai-starter-model-azure-openai</artifactId>
             <version>${spring-ai.version}</version>
         </dependency>
         <dependency>
             <groupId>org.springframework.ai</groupId>
-            <artifactId>spring-ai-ollama-spring-boot-starter</artifactId>
+            <artifactId>spring-ai-starter-model-deepseek</artifactId>
             <version>${spring-ai.version}</version>
         </dependency>
         <dependency>
             <groupId>org.springframework.ai</groupId>
-            <artifactId>spring-ai-stability-ai-spring-boot-starter</artifactId>
+            <artifactId>spring-ai-starter-model-ollama</artifactId>
             <version>${spring-ai.version}</version>
         </dependency>
         <dependency>
-            <!-- 通义千问 -->
-            <groupId>com.alibaba.cloud.ai</groupId>
-            <artifactId>spring-ai-alibaba-starter</artifactId>
-            <version>${spring-ai.version}.1</version>
-        </dependency>
-        <dependency>
-            <!-- 文心一言 -->
             <groupId>org.springframework.ai</groupId>
-            <artifactId>spring-ai-qianfan-spring-boot-starter</artifactId>
+            <artifactId>spring-ai-starter-model-stability-ai</artifactId>
             <version>${spring-ai.version}</version>
         </dependency>
         <dependency>
             <!-- 智谱 GLM -->
             <groupId>org.springframework.ai</groupId>
-            <artifactId>spring-ai-zhipuai-spring-boot-starter</artifactId>
+            <artifactId>spring-ai-starter-model-zhipuai</artifactId>
             <version>${spring-ai.version}</version>
         </dependency>
         <dependency>
             <groupId>org.springframework.ai</groupId>
-            <artifactId>spring-ai-minimax-spring-boot-starter</artifactId>
+            <artifactId>spring-ai-starter-model-minimax</artifactId>
             <version>${spring-ai.version}</version>
         </dependency>
+
         <dependency>
-            <groupId>org.springframework.ai</groupId>
-            <artifactId>spring-ai-moonshot-spring-boot-starter</artifactId>
-            <version>${spring-ai.version}</version>
+            <!-- 通义千问 -->
+            <groupId>com.alibaba.cloud.ai</groupId>
+            <artifactId>spring-ai-alibaba-starter-dashscope</artifactId>
+            <version>${alibaba-ai.version}</version>
+        </dependency>
+
+        <dependency>
+            <!-- 文心一言 -->
+            <groupId>org.springaicommunity</groupId>
+            <artifactId>qianfan-spring-boot-starter</artifactId>
+            <version>1.0.0</version>
+        </dependency>
+        <dependency>
+            <!-- 月之暗灭 -->
+            <groupId>org.springaicommunity</groupId>
+            <artifactId>moonshot-spring-boot-starter</artifactId>
+            <version>1.0.0</version>
         </dependency>
 
         <!-- 向量存储：https://db-engines.com/en/ranking/vector+dbms -->
         <dependency>
             <!-- Qdrant：https://qdrant.tech/ -->
             <groupId>org.springframework.ai</groupId>
-            <artifactId>spring-ai-qdrant-store</artifactId>
+            <artifactId>spring-ai-starter-vector-store-qdrant</artifactId>
             <version>${spring-ai.version}</version>
         </dependency>
 
         <dependency>
             <!-- Redis：https://redis.io/docs/latest/develop/get-started/vector-database/ -->
             <groupId>org.springframework.ai</groupId>
-            <artifactId>spring-ai-redis-store</artifactId>
+            <artifactId>spring-ai-starter-vector-store-redis</artifactId>
             <version>${spring-ai.version}</version>
         </dependency>
         <dependency>
@@ -179,7 +188,7 @@
         <dependency>
             <!-- Milvus：https://milvus.io/ -->
             <groupId>org.springframework.ai</groupId>
-            <artifactId>spring-ai-milvus-store</artifactId>
+            <artifactId>spring-ai-starter-vector-store-milvus</artifactId>
             <version>${spring-ai.version}</version>
             <exclusions>
                 <!-- 解决和 logback 的日志冲突 -->

yudao-module-ai/yudao-module-ai-server/src/main/java/cn/iocoder/yudao/module/ai/AiServerApplication.java

@@ -13,8 +13,8 @@ import org.springframework.boot.autoconfigure.SpringBootApplication;
  * @author 芋道源码
  */
 @SpringBootApplication(exclude = {
-        org.springframework.ai.autoconfigure.vectorstore.qdrant.QdrantVectorStoreAutoConfiguration.class,
-        org.springframework.ai.autoconfigure.vectorstore.milvus.MilvusVectorStoreAutoConfiguration.class,
+        org.springframework.ai.vectorstore.qdrant.autoconfigure.QdrantVectorStoreAutoConfiguration.class,
+        org.springframework.ai.vectorstore.milvus.autoconfigure.MilvusVectorStoreAutoConfiguration.class,
 }) // 解决 application-${profile}.yaml 配置文件下，通过 spring.autoconfigure.exclude 无法排除的问题
 public class AiServerApplication {
 

yudao-module-ai/yudao-module-ai-server/src/main/java/cn/iocoder/yudao/module/ai/framework/ai/config/AiAutoConfiguration.java

@@ -5,7 +5,6 @@ import cn.hutool.extra.spring.SpringUtil;
 import cn.iocoder.yudao.module.ai.framework.ai.core.AiModelFactory;
 import cn.iocoder.yudao.module.ai.framework.ai.core.AiModelFactoryImpl;
 import cn.iocoder.yudao.module.ai.framework.ai.core.model.baichuan.BaiChuanChatModel;
-import cn.iocoder.yudao.module.ai.framework.ai.core.model.deepseek.DeepSeekChatModel;
 import cn.iocoder.yudao.module.ai.framework.ai.core.model.doubao.DouBaoChatModel;
 import cn.iocoder.yudao.module.ai.framework.ai.core.model.hunyuan.HunYuanChatModel;
 import cn.iocoder.yudao.module.ai.framework.ai.core.model.midjourney.api.MidjourneyApi;
@@ -14,10 +13,6 @@ import cn.iocoder.yudao.module.ai.framework.ai.core.model.siliconflow.SiliconFlo
 import cn.iocoder.yudao.module.ai.framework.ai.core.model.suno.api.SunoApi;
 import cn.iocoder.yudao.module.ai.framework.ai.core.model.xinghuo.XingHuoChatModel;
 import lombok.extern.slf4j.Slf4j;
-import org.springframework.ai.autoconfigure.vectorstore.milvus.MilvusServiceClientProperties;
-import org.springframework.ai.autoconfigure.vectorstore.milvus.MilvusVectorStoreProperties;
-import org.springframework.ai.autoconfigure.vectorstore.qdrant.QdrantVectorStoreProperties;
-import org.springframework.ai.autoconfigure.vectorstore.redis.RedisVectorStoreProperties;
 import org.springframework.ai.embedding.BatchingStrategy;
 import org.springframework.ai.embedding.TokenCountBatchingStrategy;
 import org.springframework.ai.model.tool.ToolCallingManager;
@@ -26,6 +21,10 @@ import org.springframework.ai.openai.OpenAiChatOptions;
 import org.springframework.ai.openai.api.OpenAiApi;
 import org.springframework.ai.tokenizer.JTokkitTokenCountEstimator;
 import org.springframework.ai.tokenizer.TokenCountEstimator;
+import org.springframework.ai.vectorstore.milvus.autoconfigure.MilvusServiceClientProperties;
+import org.springframework.ai.vectorstore.milvus.autoconfigure.MilvusVectorStoreProperties;
+import org.springframework.ai.vectorstore.qdrant.autoconfigure.QdrantVectorStoreProperties;
+import org.springframework.ai.vectorstore.redis.autoconfigure.RedisVectorStoreProperties;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnProperty;
 import org.springframework.boot.context.properties.EnableConfigurationProperties;
 import org.springframework.context.annotation.Bean;
@@ -52,33 +51,6 @@ public class AiAutoConfiguration {
 
     // ========== 各种 AI Client 创建 ==========
 
-    @Bean
-    @ConditionalOnProperty(value = "yudao.ai.deepseek.enable", havingValue = "true")
-    public DeepSeekChatModel deepSeekChatModel(YudaoAiProperties yudaoAiProperties) {
-        YudaoAiProperties.DeepSeekProperties properties = yudaoAiProperties.getDeepseek();
-        return buildDeepSeekChatModel(properties);
-    }
-
-    public DeepSeekChatModel buildDeepSeekChatModel(YudaoAiProperties.DeepSeekProperties properties) {
-        if (StrUtil.isEmpty(properties.getModel())) {
-            properties.setModel(DeepSeekChatModel.MODEL_DEFAULT);
-        }
-        OpenAiChatModel openAiChatModel = OpenAiChatModel.builder()
-                .openAiApi(OpenAiApi.builder()
-                        .baseUrl(DeepSeekChatModel.BASE_URL)
-                        .apiKey(properties.getApiKey())
-                        .build())
-                .defaultOptions(OpenAiChatOptions.builder()
-                        .model(properties.getModel())
-                        .temperature(properties.getTemperature())
-                        .maxTokens(properties.getMaxTokens())
-                        .topP(properties.getTopP())
-                        .build())
-                .toolCallingManager(getToolCallingManager())
-                .build();
-        return new DeepSeekChatModel(openAiChatModel);
-    }
-
     @Bean
     @ConditionalOnProperty(value = "yudao.ai.doubao.enable", havingValue = "true")
     public DouBaoChatModel douBaoChatClient(YudaoAiProperties yudaoAiProperties) {

yudao-module-ai/yudao-module-ai-server/src/main/java/cn/iocoder/yudao/module/ai/framework/ai/config/YudaoAiProperties.java

@@ -13,12 +13,6 @@ import org.springframework.boot.context.properties.ConfigurationProperties;
 @Data
 public class YudaoAiProperties {
 
-    /**
-     * DeepSeek
-     */
-    @SuppressWarnings("SpellCheckingInspection")
-    private DeepSeekProperties deepseek;
-
     /**
      * 字节豆包
      */
@@ -60,19 +54,6 @@ public class YudaoAiProperties {
     @SuppressWarnings("SpellCheckingInspection")
     private SunoProperties suno;
 
-    @Data
-    public static class DeepSeekProperties {
-
-        private String enable;
-        private String apiKey;
-
-        private String model;
-        private Double temperature;
-        private Integer maxTokens;
-        private Double topP;
-
-    }
-
     @Data
     public static class DouBaoProperties {
 

yudao-module-ai/yudao-module-ai-server/src/main/java/cn/iocoder/yudao/module/ai/framework/ai/core/AiModelFactoryImpl.java

@@ -8,11 +8,11 @@ import cn.hutool.core.util.ArrayUtil;
 import cn.hutool.core.util.RuntimeUtil;
 import cn.hutool.core.util.StrUtil;
 import cn.hutool.extra.spring.SpringUtil;
+import cn.iocoder.yudao.framework.common.util.spring.SpringUtils;
+import cn.iocoder.yudao.module.ai.enums.model.AiPlatformEnum;
 import cn.iocoder.yudao.module.ai.framework.ai.config.AiAutoConfiguration;
 import cn.iocoder.yudao.module.ai.framework.ai.config.YudaoAiProperties;
-import cn.iocoder.yudao.module.ai.enums.model.AiPlatformEnum;
 import cn.iocoder.yudao.module.ai.framework.ai.core.model.baichuan.BaiChuanChatModel;
-import cn.iocoder.yudao.module.ai.framework.ai.core.model.deepseek.DeepSeekChatModel;
 import cn.iocoder.yudao.module.ai.framework.ai.core.model.doubao.DouBaoChatModel;
 import cn.iocoder.yudao.module.ai.framework.ai.core.model.hunyuan.HunYuanChatModel;
 import cn.iocoder.yudao.module.ai.framework.ai.core.model.midjourney.api.MidjourneyApi;
@@ -22,8 +22,9 @@ import cn.iocoder.yudao.module.ai.framework.ai.core.model.siliconflow.SiliconFlo
 import cn.iocoder.yudao.module.ai.framework.ai.core.model.siliconflow.SiliconFlowImageModel;
 import cn.iocoder.yudao.module.ai.framework.ai.core.model.suno.api.SunoApi;
 import cn.iocoder.yudao.module.ai.framework.ai.core.model.xinghuo.XingHuoChatModel;
-import cn.iocoder.yudao.framework.common.util.spring.SpringUtils;
-import com.alibaba.cloud.ai.autoconfigure.dashscope.DashScopeAutoConfiguration;
+import com.alibaba.cloud.ai.autoconfigure.dashscope.DashScopeChatAutoConfiguration;
+import com.alibaba.cloud.ai.autoconfigure.dashscope.DashScopeEmbeddingAutoConfiguration;
+import com.alibaba.cloud.ai.autoconfigure.dashscope.DashScopeImageAutoConfiguration;
 import com.alibaba.cloud.ai.dashscope.api.DashScopeApi;
 import com.alibaba.cloud.ai.dashscope.api.DashScopeImageApi;
 import com.alibaba.cloud.ai.dashscope.chat.DashScopeChatModel;
@@ -32,47 +33,55 @@ import com.alibaba.cloud.ai.dashscope.embedding.DashScopeEmbeddingModel;
 import com.alibaba.cloud.ai.dashscope.embedding.DashScopeEmbeddingOptions;
 import com.alibaba.cloud.ai.dashscope.image.DashScopeImageModel;
 import com.azure.ai.openai.OpenAIClientBuilder;
+import com.azure.core.credential.KeyCredential;
 import io.micrometer.observation.ObservationRegistry;
 import io.milvus.client.MilvusServiceClient;
 import io.qdrant.client.QdrantClient;
 import io.qdrant.client.QdrantGrpcClient;
 import lombok.SneakyThrows;
-import org.springframework.ai.autoconfigure.azure.openai.AzureOpenAiAutoConfiguration;
-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;
-import org.springframework.ai.autoconfigure.stabilityai.StabilityAiImageAutoConfiguration;
-import org.springframework.ai.autoconfigure.vectorstore.milvus.MilvusServiceClientConnectionDetails;
-import org.springframework.ai.autoconfigure.vectorstore.milvus.MilvusServiceClientProperties;
-import org.springframework.ai.autoconfigure.vectorstore.milvus.MilvusVectorStoreAutoConfiguration;
-import org.springframework.ai.autoconfigure.vectorstore.milvus.MilvusVectorStoreProperties;
-import org.springframework.ai.autoconfigure.vectorstore.qdrant.QdrantVectorStoreAutoConfiguration;
-import org.springframework.ai.autoconfigure.vectorstore.qdrant.QdrantVectorStoreProperties;
-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.springaicommunity.moonshot.MoonshotChatModel;
+import org.springaicommunity.moonshot.MoonshotChatOptions;
+import org.springaicommunity.moonshot.api.MoonshotApi;
+import org.springaicommunity.moonshot.autoconfigure.MoonshotChatAutoConfiguration;
+import org.springaicommunity.qianfan.QianFanChatModel;
+import org.springaicommunity.qianfan.QianFanEmbeddingModel;
+import org.springaicommunity.qianfan.QianFanEmbeddingOptions;
+import org.springaicommunity.qianfan.QianFanImageModel;
+import org.springaicommunity.qianfan.api.QianFanApi;
+import org.springaicommunity.qianfan.api.QianFanImageApi;
+import org.springaicommunity.qianfan.autoconfigure.QianFanChatAutoConfiguration;
+import org.springaicommunity.qianfan.autoconfigure.QianFanEmbeddingAutoConfiguration;
 import org.springframework.ai.azure.openai.AzureOpenAiChatModel;
 import org.springframework.ai.azure.openai.AzureOpenAiEmbeddingModel;
 import org.springframework.ai.chat.model.ChatModel;
+import org.springframework.ai.deepseek.DeepSeekChatModel;
+import org.springframework.ai.deepseek.DeepSeekChatOptions;
+import org.springframework.ai.deepseek.api.DeepSeekApi;
 import org.springframework.ai.document.MetadataMode;
 import org.springframework.ai.embedding.BatchingStrategy;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.observation.EmbeddingModelObservationConvention;
 import org.springframework.ai.image.ImageModel;
 import org.springframework.ai.minimax.MiniMaxChatModel;
 import org.springframework.ai.minimax.MiniMaxChatOptions;
 import org.springframework.ai.minimax.MiniMaxEmbeddingModel;
 import org.springframework.ai.minimax.MiniMaxEmbeddingOptions;
 import org.springframework.ai.minimax.api.MiniMaxApi;
-import org.springframework.ai.model.function.FunctionCallbackResolver;
+import org.springframework.ai.model.azure.openai.autoconfigure.AzureOpenAiChatAutoConfiguration;
+import org.springframework.ai.model.azure.openai.autoconfigure.AzureOpenAiEmbeddingAutoConfiguration;
+import org.springframework.ai.model.azure.openai.autoconfigure.AzureOpenAiEmbeddingProperties;
+import org.springframework.ai.model.deepseek.autoconfigure.DeepSeekChatAutoConfiguration;
+import org.springframework.ai.model.minimax.autoconfigure.MiniMaxChatAutoConfiguration;
+import org.springframework.ai.model.minimax.autoconfigure.MiniMaxEmbeddingAutoConfiguration;
+import org.springframework.ai.model.ollama.autoconfigure.OllamaChatAutoConfiguration;
+import org.springframework.ai.model.openai.autoconfigure.OpenAiChatAutoConfiguration;
+import org.springframework.ai.model.openai.autoconfigure.OpenAiEmbeddingAutoConfiguration;
+import org.springframework.ai.model.openai.autoconfigure.OpenAiImageAutoConfiguration;
+import org.springframework.ai.model.stabilityai.autoconfigure.StabilityAiImageAutoConfiguration;
 import org.springframework.ai.model.tool.ToolCallingManager;
-import org.springframework.ai.moonshot.MoonshotChatModel;
-import org.springframework.ai.moonshot.MoonshotChatOptions;
-import org.springframework.ai.moonshot.api.MoonshotApi;
+import org.springframework.ai.model.zhipuai.autoconfigure.ZhiPuAiChatAutoConfiguration;
+import org.springframework.ai.model.zhipuai.autoconfigure.ZhiPuAiEmbeddingAutoConfiguration;
+import org.springframework.ai.model.zhipuai.autoconfigure.ZhiPuAiImageAutoConfiguration;
 import org.springframework.ai.ollama.OllamaChatModel;
 import org.springframework.ai.ollama.OllamaEmbeddingModel;
 import org.springframework.ai.ollama.api.OllamaApi;
@@ -84,21 +93,23 @@ import org.springframework.ai.openai.OpenAiImageModel;
 import org.springframework.ai.openai.api.OpenAiApi;
 import org.springframework.ai.openai.api.OpenAiImageApi;
 import org.springframework.ai.openai.api.common.OpenAiApiConstants;
-import org.springframework.ai.qianfan.QianFanChatModel;
-import org.springframework.ai.qianfan.QianFanEmbeddingModel;
-import org.springframework.ai.qianfan.QianFanEmbeddingOptions;
-import org.springframework.ai.qianfan.QianFanImageModel;
-import org.springframework.ai.qianfan.api.QianFanApi;
-import org.springframework.ai.qianfan.api.QianFanImageApi;
 import org.springframework.ai.stabilityai.StabilityAiImageModel;
 import org.springframework.ai.stabilityai.api.StabilityAiApi;
 import org.springframework.ai.vectorstore.SimpleVectorStore;
 import org.springframework.ai.vectorstore.VectorStore;
 import org.springframework.ai.vectorstore.milvus.MilvusVectorStore;
+import org.springframework.ai.vectorstore.milvus.autoconfigure.MilvusServiceClientConnectionDetails;
+import org.springframework.ai.vectorstore.milvus.autoconfigure.MilvusServiceClientProperties;
+import org.springframework.ai.vectorstore.milvus.autoconfigure.MilvusVectorStoreAutoConfiguration;
+import org.springframework.ai.vectorstore.milvus.autoconfigure.MilvusVectorStoreProperties;
 import org.springframework.ai.vectorstore.observation.DefaultVectorStoreObservationConvention;
 import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
 import org.springframework.ai.vectorstore.qdrant.QdrantVectorStore;
+import org.springframework.ai.vectorstore.qdrant.autoconfigure.QdrantVectorStoreAutoConfiguration;
+import org.springframework.ai.vectorstore.qdrant.autoconfigure.QdrantVectorStoreProperties;
 import org.springframework.ai.vectorstore.redis.RedisVectorStore;
+import org.springframework.ai.vectorstore.redis.autoconfigure.RedisVectorStoreAutoConfiguration;
+import org.springframework.ai.vectorstore.redis.autoconfigure.RedisVectorStoreProperties;
 import org.springframework.ai.zhipuai.*;
 import org.springframework.ai.zhipuai.api.ZhiPuAiApi;
 import org.springframework.ai.zhipuai.api.ZhiPuAiImageApi;
@@ -190,7 +201,7 @@ public class AiModelFactoryImpl implements AiModelFactory {
             case XING_HUO:
                 return SpringUtil.getBean(XingHuoChatModel.class);
             case BAI_CHUAN:
-                return SpringUtil.getBean(AzureOpenAiChatModel.class);
+                return SpringUtil.getBean(BaiChuanChatModel.class);
             case OPENAI:
                 return SpringUtil.getBean(OpenAiChatModel.class);
             case AZURE_OPENAI:
@@ -319,27 +330,34 @@ public class AiModelFactoryImpl implements AiModelFactory {
     // ========== 各种创建 spring-ai 客户端的方法 ==========
 
     /**
-     * 可参考 {@link DashScopeAutoConfiguration} 的 dashscopeChatModel 方法
+     * 可参考 {@link DashScopeChatAutoConfiguration} 的 dashscopeChatModel 方法
      */
     private static DashScopeChatModel buildTongYiChatModel(String key) {
-        DashScopeApi dashScopeApi = new DashScopeApi(key);
+        DashScopeApi dashScopeApi = DashScopeApi.builder().apiKey(key).build();
         DashScopeChatOptions options = DashScopeChatOptions.builder().withModel(DashScopeApi.DEFAULT_CHAT_MODEL)
                 .withTemperature(0.7).build();
-        return new DashScopeChatModel(dashScopeApi, options, getFunctionCallbackResolver(), DEFAULT_RETRY_TEMPLATE);
+        return DashScopeChatModel.builder()
+                .dashScopeApi(dashScopeApi)
+                .defaultOptions(options)
+                .toolCallingManager(getToolCallingManager())
+                .build();
     }
 
     /**
-     * 可参考 {@link DashScopeAutoConfiguration} 的 dashScopeImageModel 方法
+     * 可参考 {@link DashScopeImageAutoConfiguration} 的 dashScopeImageModel 方法
      */
     private static DashScopeImageModel buildTongYiImagesModel(String key) {
         DashScopeImageApi dashScopeImageApi = new DashScopeImageApi(key);
-        return new DashScopeImageModel(dashScopeImageApi);
+        return DashScopeImageModel.builder()
+                .dashScopeApi(dashScopeImageApi)
+                .build();
     }
 
     /**
-     * 可参考 {@link QianFanAutoConfiguration} 的 qianFanChatModel 方法
+     * 可参考 {@link QianFanChatAutoConfiguration} 的 qianFanChatModel 方法
      */
     private static QianFanChatModel buildYiYanChatModel(String key) {
+        // TODO spring ai qianfan 有 bug，无法使用 https://github.com/spring-ai-community/qianfan/issues/6
         List<String> keys = StrUtil.split(key, '|');
         Assert.equals(keys.size(), 2, "YiYanChatClient 的密钥需要 (appKey|secretKey) 格式");
         String appKey = keys.get(0);
@@ -349,9 +367,10 @@ public class AiModelFactoryImpl implements AiModelFactory {
     }
 
     /**
-     * 可参考 {@link QianFanAutoConfiguration} 的 qianFanImageModel 方法
+     * 可参考 {@link QianFanEmbeddingAutoConfiguration} 的 qianFanImageModel 方法
      */
     private QianFanImageModel buildQianFanImageModel(String key) {
+        // TODO spring ai qianfan 有 bug，无法使用 https://github.com/spring-ai-community/qianfan/issues/6
         List<String> keys = StrUtil.split(key, '|');
         Assert.equals(keys.size(), 2, "YiYanChatClient 的密钥需要 (appKey|secretKey) 格式");
         String appKey = keys.get(0);
@@ -361,12 +380,17 @@ public class AiModelFactoryImpl implements AiModelFactory {
     }
 
     /**
-     * 可参考 {@link AiAutoConfiguration#deepSeekChatModel(YudaoAiProperties)}
+     * 可参考 {@link DeepSeekChatAutoConfiguration} 的 deepSeekChatModel 方法
      */
     private static DeepSeekChatModel buildDeepSeekChatModel(String apiKey) {
-        YudaoAiProperties.DeepSeekProperties properties = new YudaoAiProperties.DeepSeekProperties()
-                .setApiKey(apiKey);
-        return new AiAutoConfiguration().buildDeepSeekChatModel(properties);
+        DeepSeekApi deepSeekApi = DeepSeekApi.builder().apiKey(apiKey).build();
+        DeepSeekChatOptions options = DeepSeekChatOptions.builder().model(DeepSeekApi.DEFAULT_CHAT_MODEL)
+                .temperature(0.7).build();
+        return DeepSeekChatModel.builder()
+                .deepSeekApi(deepSeekApi)
+                .defaultOptions(options)
+                .toolCallingManager(getToolCallingManager())
+                .build();
     }
 
     /**
@@ -397,17 +421,18 @@ public class AiModelFactoryImpl implements AiModelFactory {
     }
 
     /**
-     * 可参考 {@link ZhiPuAiAutoConfiguration} 的 zhiPuAiChatModel 方法
+     * 可参考 {@link ZhiPuAiChatAutoConfiguration} 的 zhiPuAiChatModel 方法
      */
     private ZhiPuAiChatModel buildZhiPuChatModel(String apiKey, String url) {
         ZhiPuAiApi zhiPuAiApi = StrUtil.isEmpty(url) ? new ZhiPuAiApi(apiKey)
                 : new ZhiPuAiApi(url, apiKey);
         ZhiPuAiChatOptions options = ZhiPuAiChatOptions.builder().model(ZhiPuAiApi.DEFAULT_CHAT_MODEL).temperature(0.7).build();
-        return new ZhiPuAiChatModel(zhiPuAiApi, options, getFunctionCallbackResolver(), DEFAULT_RETRY_TEMPLATE);
+        return new ZhiPuAiChatModel(zhiPuAiApi, options, getToolCallingManager(), DEFAULT_RETRY_TEMPLATE,
+                getObservationRegistry().getIfAvailable());
     }
 
     /**
-     * 可参考 {@link ZhiPuAiAutoConfiguration} 的 zhiPuAiImageModel 方法
+     * 可参考 {@link ZhiPuAiImageAutoConfiguration} 的 zhiPuAiImageModel 方法
      */
     private ZhiPuAiImageModel buildZhiPuAiImageModel(String apiKey, String url) {
         ZhiPuAiImageApi zhiPuAiApi = StrUtil.isEmpty(url) ? new ZhiPuAiImageApi(apiKey)
@@ -416,23 +441,30 @@ public class AiModelFactoryImpl implements AiModelFactory {
     }
 
     /**
-     * 可参考 {@link MiniMaxAutoConfiguration} 的 miniMaxChatModel 方法
+     * 可参考 {@link MiniMaxChatAutoConfiguration} 的 miniMaxChatModel 方法
      */
     private MiniMaxChatModel buildMiniMaxChatModel(String apiKey, String url) {
         MiniMaxApi miniMaxApi = StrUtil.isEmpty(url) ? new MiniMaxApi(apiKey)
                 : new MiniMaxApi(url, apiKey);
         MiniMaxChatOptions options = MiniMaxChatOptions.builder().model(MiniMaxApi.DEFAULT_CHAT_MODEL).temperature(0.7).build();
-        return new MiniMaxChatModel(miniMaxApi, options, getFunctionCallbackResolver(), DEFAULT_RETRY_TEMPLATE);
+        return new MiniMaxChatModel(miniMaxApi, options, getToolCallingManager(), DEFAULT_RETRY_TEMPLATE);
     }
 
     /**
-     * 可参考 {@link MoonshotAutoConfiguration} 的 moonshotChatModel 方法
+     * 可参考 {@link MoonshotChatAutoConfiguration} 的 moonshotChatModel 方法
      */
     private MoonshotChatModel buildMoonshotChatModel(String apiKey, String url) {
-        MoonshotApi moonshotApi = StrUtil.isEmpty(url)? new MoonshotApi(apiKey)
-                : new MoonshotApi(url, apiKey);
+        MoonshotApi.Builder moonshotApiBuilder = MoonshotApi.builder()
+                .apiKey(apiKey);
+        if (StrUtil.isNotEmpty(url)) {
+            moonshotApiBuilder.baseUrl(url);
+        }
         MoonshotChatOptions options = MoonshotChatOptions.builder().model(MoonshotApi.DEFAULT_CHAT_MODEL).build();
-        return new MoonshotChatModel(moonshotApi, options, getFunctionCallbackResolver(), DEFAULT_RETRY_TEMPLATE);
+        return MoonshotChatModel.builder()
+                .moonshotApi(moonshotApiBuilder.build())
+                .defaultOptions(options)
+                .toolCallingManager(getToolCallingManager())
+                .build();
     }
 
     /**
@@ -456,33 +488,32 @@ public class AiModelFactoryImpl implements AiModelFactory {
     }
 
     /**
-     * 可参考 {@link OpenAiAutoConfiguration} 的 openAiChatModel 方法
+     * 可参考 {@link OpenAiChatAutoConfiguration} 的 openAiChatModel 方法
      */
     private static OpenAiChatModel buildOpenAiChatModel(String openAiToken, String url) {
         url = StrUtil.blankToDefault(url, OpenAiApiConstants.DEFAULT_BASE_URL);
         OpenAiApi openAiApi = OpenAiApi.builder().baseUrl(url).apiKey(openAiToken).build();
-        return OpenAiChatModel.builder().openAiApi(openAiApi).toolCallingManager(getToolCallingManager()).build();
+        return OpenAiChatModel.builder()
+                .openAiApi(openAiApi)
+                .toolCallingManager(getToolCallingManager())
+                .build();
     }
 
-    // TODO @芋艿：手头暂时没密钥，使用建议再测试下
     /**
-     * 可参考 {@link AzureOpenAiAutoConfiguration}
+     * 可参考 {@link AzureOpenAiChatAutoConfiguration}
      */
     private static AzureOpenAiChatModel buildAzureOpenAiChatModel(String apiKey, String url) {
-        AzureOpenAiAutoConfiguration azureOpenAiAutoConfiguration = new AzureOpenAiAutoConfiguration();
-        // 创建 OpenAIClient 对象
-        AzureOpenAiConnectionProperties connectionProperties = new AzureOpenAiConnectionProperties();
-        connectionProperties.setApiKey(apiKey);
-        connectionProperties.setEndpoint(url);
-        OpenAIClientBuilder openAIClient = azureOpenAiAutoConfiguration.openAIClientBuilder(connectionProperties, null);
-        // 获取 AzureOpenAiChatProperties 对象
-        AzureOpenAiChatProperties chatProperties = SpringUtil.getBean(AzureOpenAiChatProperties.class);
-        return azureOpenAiAutoConfiguration.azureOpenAiChatModel(openAIClient, chatProperties,
-                getToolCallingManager(), null, null);
+        // TODO @芋艿：使用前，请测试，暂时没密钥！！！
+        OpenAIClientBuilder openAIClientBuilder = new OpenAIClientBuilder()
+                .endpoint(url).credential(new KeyCredential(apiKey));
+        return AzureOpenAiChatModel.builder()
+                .openAIClientBuilder(openAIClientBuilder)
+                .toolCallingManager(getToolCallingManager())
+                .build();
     }
 
     /**
-     * 可参考 {@link OpenAiAutoConfiguration} 的 openAiImageModel 方法
+     * 可参考 {@link OpenAiImageAutoConfiguration} 的 openAiImageModel 方法
      */
     private OpenAiImageModel buildOpenAiImageModel(String openAiToken, String url) {
         url = StrUtil.blankToDefault(url, OpenAiApiConstants.DEFAULT_BASE_URL);
@@ -500,11 +531,14 @@ public class AiModelFactoryImpl implements AiModelFactory {
     }
 
     /**
-     * 可参考 {@link OllamaAutoConfiguration} 的 ollamaApi 方法
+     * 可参考 {@link OllamaChatAutoConfiguration} 的 ollamaChatModel 方法
      */
     private static OllamaChatModel buildOllamaChatModel(String url) {
-        OllamaApi ollamaApi = new OllamaApi(url);
-        return OllamaChatModel.builder().ollamaApi(ollamaApi).toolCallingManager(getToolCallingManager()).build();
+        OllamaApi ollamaApi = OllamaApi.builder().baseUrl(url).build();
+        return OllamaChatModel.builder()
+                .ollamaApi(ollamaApi)
+                .toolCallingManager(getToolCallingManager())
+                .build();
     }
 
     /**
@@ -519,16 +553,16 @@ public class AiModelFactoryImpl implements AiModelFactory {
     // ========== 各种创建 EmbeddingModel 的方法 ==========
 
     /**
-     * 可参考 {@link DashScopeAutoConfiguration} 的 dashscopeEmbeddingModel 方法
+     * 可参考 {@link DashScopeEmbeddingAutoConfiguration} 的 dashscopeEmbeddingModel 方法
      */
     private DashScopeEmbeddingModel buildTongYiEmbeddingModel(String apiKey, String model) {
-        DashScopeApi dashScopeApi = new DashScopeApi(apiKey);
+        DashScopeApi dashScopeApi = DashScopeApi.builder().apiKey(apiKey).build();
         DashScopeEmbeddingOptions dashScopeEmbeddingOptions = DashScopeEmbeddingOptions.builder().withModel(model).build();
         return new DashScopeEmbeddingModel(dashScopeApi, MetadataMode.EMBED, dashScopeEmbeddingOptions);
     }
 
     /**
-     * 可参考 {@link ZhiPuAiAutoConfiguration} 的 zhiPuAiEmbeddingModel 方法
+     * 可参考 {@link ZhiPuAiEmbeddingAutoConfiguration} 的 zhiPuAiEmbeddingModel 方法
      */
     private ZhiPuAiEmbeddingModel buildZhiPuEmbeddingModel(String apiKey, String url, String model) {
         ZhiPuAiApi zhiPuAiApi = StrUtil.isEmpty(url) ? new ZhiPuAiApi(apiKey)
@@ -538,7 +572,7 @@ public class AiModelFactoryImpl implements AiModelFactory {
     }
 
     /**
-     * 可参考 {@link MiniMaxAutoConfiguration} 的 miniMaxEmbeddingModel 方法
+     * 可参考 {@link MiniMaxEmbeddingAutoConfiguration} 的 miniMaxEmbeddingModel 方法
      */
     private EmbeddingModel buildMiniMaxEmbeddingModel(String apiKey, String url, String model) {
         MiniMaxApi miniMaxApi = StrUtil.isEmpty(url)? new MiniMaxApi(apiKey)
@@ -548,7 +582,7 @@ public class AiModelFactoryImpl implements AiModelFactory {
     }
 
     /**
-     * 可参考 {@link QianFanAutoConfiguration} 的 qianFanEmbeddingModel 方法
+     * 可参考 {@link QianFanEmbeddingAutoConfiguration} 的 qianFanEmbeddingModel 方法
      */
     private QianFanEmbeddingModel buildYiYanEmbeddingModel(String key, String model) {
         List<String> keys = StrUtil.split(key, '|');
@@ -561,13 +595,16 @@ public class AiModelFactoryImpl implements AiModelFactory {
     }
 
     private OllamaEmbeddingModel buildOllamaEmbeddingModel(String url, String model) {
-        OllamaApi ollamaApi = new OllamaApi(url);
+        OllamaApi ollamaApi = OllamaApi.builder().baseUrl(url).build();
         OllamaOptions ollamaOptions = OllamaOptions.builder().model(model).build();
-        return OllamaEmbeddingModel.builder().ollamaApi(ollamaApi).defaultOptions(ollamaOptions).build();
+        return OllamaEmbeddingModel.builder()
+                .ollamaApi(ollamaApi)
+                .defaultOptions(ollamaOptions)
+                .build();
     }
 
     /**
-     * 可参考 {@link OpenAiAutoConfiguration} 的 openAiEmbeddingModel 方法
+     * 可参考 {@link OpenAiEmbeddingAutoConfiguration} 的 openAiEmbeddingModel 方法
      */
     private OpenAiEmbeddingModel buildOpenAiEmbeddingModel(String openAiToken, String url, String model) {
         url = StrUtil.blankToDefault(url, OpenAiApiConstants.DEFAULT_BASE_URL);
@@ -576,21 +613,19 @@ public class AiModelFactoryImpl implements AiModelFactory {
         return new OpenAiEmbeddingModel(openAiApi, MetadataMode.EMBED, openAiEmbeddingProperties);
     }
 
-    // TODO @芋艿：手头暂时没密钥，使用建议再测试下
     /**
-     * 可参考 {@link AzureOpenAiAutoConfiguration} 的 azureOpenAiEmbeddingModel 方法
+     * 可参考 {@link AzureOpenAiEmbeddingAutoConfiguration} 的 azureOpenAiEmbeddingModel 方法
      */
     private AzureOpenAiEmbeddingModel buildAzureOpenAiEmbeddingModel(String apiKey, String url, String model) {
-        AzureOpenAiAutoConfiguration azureOpenAiAutoConfiguration = new AzureOpenAiAutoConfiguration();
-        // 创建 OpenAIClient 对象
-        AzureOpenAiConnectionProperties connectionProperties = new AzureOpenAiConnectionProperties();
-        connectionProperties.setApiKey(apiKey);
-        connectionProperties.setEndpoint(url);
-        OpenAIClientBuilder openAIClient = azureOpenAiAutoConfiguration.openAIClientBuilder(connectionProperties, null);
+        // TODO @芋艿：手头暂时没密钥，使用建议再测试下
+        AzureOpenAiEmbeddingAutoConfiguration azureOpenAiAutoConfiguration = new AzureOpenAiEmbeddingAutoConfiguration();
+        // 创建 OpenAIClientBuilder 对象
+        OpenAIClientBuilder openAIClientBuilder = new OpenAIClientBuilder()
+                .endpoint(url).credential(new KeyCredential(apiKey));
         // 获取 AzureOpenAiChatProperties 对象
         AzureOpenAiEmbeddingProperties embeddingProperties = SpringUtil.getBean(AzureOpenAiEmbeddingProperties.class);
-        return azureOpenAiAutoConfiguration.azureOpenAiEmbeddingModel(openAIClient, embeddingProperties,
-                null, null);
+        return azureOpenAiAutoConfiguration.azureOpenAiEmbeddingModel(openAIClientBuilder, embeddingProperties,
+                getObservationRegistry(), getEmbeddingModelObservationConvention());
     }
 
     // ========== 各种创建 VectorStore 的方法 ==========
@@ -655,12 +690,12 @@ public class AiModelFactoryImpl implements AiModelFactory {
                                                    Map<String, Class<?>> metadataFields) {
         // 创建 JedisPooled 对象
         RedisProperties redisProperties = SpringUtils.getBean(RedisProperties.class);
-        JedisPooled jedisPooled = new JedisPooled(redisProperties.getHost(), redisProperties.getPort());
+        JedisPooled jedisPooled = new JedisPooled(redisProperties.getHost(), redisProperties.getPort(),
+                redisProperties.getUsername(), redisProperties.getPassword());
         // 创建 RedisVectorStoreProperties 对象
-        RedisVectorStoreAutoConfiguration configuration = new RedisVectorStoreAutoConfiguration();
         RedisVectorStoreProperties properties = SpringUtil.getBean(RedisVectorStoreProperties.class);
         RedisVectorStore redisVectorStore = RedisVectorStore.builder(jedisPooled, embeddingModel)
-                .indexName(properties.getIndex()).prefix(properties.getPrefix())
+                .indexName(properties.getIndexName()).prefix(properties.getPrefix())
                 .initializeSchema(properties.isInitializeSchema())
                 .metadataFields(convertList(metadataFields.entrySet(), entry -> {
                     String fieldName = entry.getKey();
@@ -730,10 +765,12 @@ public class AiModelFactoryImpl implements AiModelFactory {
 
     private static ObjectProvider<VectorStoreObservationConvention> getCustomObservationConvention() {
         return new ObjectProvider<>() {
+
             @Override
             public VectorStoreObservationConvention getObject() throws BeansException {
                 return new DefaultVectorStoreObservationConvention();
             }
+
         };
     }
 
@@ -745,8 +782,15 @@ public class AiModelFactoryImpl implements AiModelFactory {
         return SpringUtil.getBean(ToolCallingManager.class);
     }
 
-    private static FunctionCallbackResolver getFunctionCallbackResolver() {
-        return SpringUtil.getBean(FunctionCallbackResolver.class);
+    private static ObjectProvider<EmbeddingModelObservationConvention> getEmbeddingModelObservationConvention() {
+        return new ObjectProvider<>() {
+
+            @Override
+            public EmbeddingModelObservationConvention getObject() throws BeansException {
+                return SpringUtil.getBean(EmbeddingModelObservationConvention.class);
+            }
+
+        };
     }
 
 }

yudao-module-ai/yudao-module-ai-server/src/main/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/deepseek/DeepSeekChatModel.java

@@ -1,45 +0,0 @@
-package cn.iocoder.yudao.module.ai.framework.ai.core.model.deepseek;
-
-import lombok.RequiredArgsConstructor;
-import lombok.extern.slf4j.Slf4j;
-import org.springframework.ai.chat.model.ChatModel;
-import org.springframework.ai.chat.model.ChatResponse;
-import org.springframework.ai.chat.prompt.ChatOptions;
-import org.springframework.ai.chat.prompt.Prompt;
-import org.springframework.ai.openai.OpenAiChatModel;
-import reactor.core.publisher.Flux;
-
-/**
- * DeepSeek {@link ChatModel} 实现类
- *
- * @author fansili
- */
-@Slf4j
-@RequiredArgsConstructor
-public class DeepSeekChatModel implements ChatModel {
-
-    public static final String BASE_URL = "https://api.deepseek.com";
-
-    public static final String MODEL_DEFAULT = "deepseek-chat";
-
-    /**
-     * 兼容 OpenAI 接口，进行复用
-     */
-    private final OpenAiChatModel openAiChatModel;
-
-    @Override
-    public ChatResponse call(Prompt prompt) {
-        return openAiChatModel.call(prompt);
-    }
-
-    @Override
-    public Flux<ChatResponse> stream(Prompt prompt) {
-        return openAiChatModel.stream(prompt);
-    }
-
-    @Override
-    public ChatOptions getDefaultOptions() {
-        return openAiChatModel.getDefaultOptions();
-    }
-
-}

yudao-module-ai/yudao-module-ai-server/src/main/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/siliconflow/SiliconFlowImageModel.java

@@ -46,94 +46,94 @@ import java.util.List;
  */
 public class SiliconFlowImageModel implements ImageModel {
 
-	private static final Logger logger = LoggerFactory.getLogger(SiliconFlowImageModel.class);
+    private static final Logger logger = LoggerFactory.getLogger(SiliconFlowImageModel.class);
 
-	private static final ImageModelObservationConvention DEFAULT_OBSERVATION_CONVENTION = new DefaultImageModelObservationConvention();
+    private static final ImageModelObservationConvention DEFAULT_OBSERVATION_CONVENTION = new DefaultImageModelObservationConvention();
 
-	private final SiliconFlowImageOptions defaultOptions;
+    private final SiliconFlowImageOptions defaultOptions;
 
-	private final RetryTemplate retryTemplate;
+    private final RetryTemplate retryTemplate;
 
-	private final SiliconFlowImageApi siliconFlowImageApi;
+    private final SiliconFlowImageApi siliconFlowImageApi;
 
-	private final ObservationRegistry observationRegistry;
+    private final ObservationRegistry observationRegistry;
 
     @Setter
-	private ImageModelObservationConvention observationConvention = DEFAULT_OBSERVATION_CONVENTION;
+    private ImageModelObservationConvention observationConvention = DEFAULT_OBSERVATION_CONVENTION;
 
-	public SiliconFlowImageModel(SiliconFlowImageApi siliconFlowImageApi) {
-		this(siliconFlowImageApi, SiliconFlowImageOptions.builder().build(), RetryUtils.DEFAULT_RETRY_TEMPLATE);
-	}
+    public SiliconFlowImageModel(SiliconFlowImageApi siliconFlowImageApi) {
+        this(siliconFlowImageApi, SiliconFlowImageOptions.builder().build(), RetryUtils.DEFAULT_RETRY_TEMPLATE);
+    }
 
-	public SiliconFlowImageModel(SiliconFlowImageApi siliconFlowImageApi, SiliconFlowImageOptions options, RetryTemplate retryTemplate) {
-		this(siliconFlowImageApi, options, retryTemplate, ObservationRegistry.NOOP);
-	}
+    public SiliconFlowImageModel(SiliconFlowImageApi siliconFlowImageApi, SiliconFlowImageOptions options, RetryTemplate retryTemplate) {
+        this(siliconFlowImageApi, options, retryTemplate, ObservationRegistry.NOOP);
+    }
 
-	public SiliconFlowImageModel(SiliconFlowImageApi siliconFlowImageApi, SiliconFlowImageOptions options, RetryTemplate retryTemplate,
+    public SiliconFlowImageModel(SiliconFlowImageApi siliconFlowImageApi, SiliconFlowImageOptions options, RetryTemplate retryTemplate,
                                  ObservationRegistry observationRegistry) {
-		Assert.notNull(siliconFlowImageApi, "OpenAiImageApi must not be null");
-		Assert.notNull(options, "options must not be null");
-		Assert.notNull(retryTemplate, "retryTemplate must not be null");
-		Assert.notNull(observationRegistry, "observationRegistry must not be null");
-		this.siliconFlowImageApi = siliconFlowImageApi;
-		this.defaultOptions = options;
-		this.retryTemplate = retryTemplate;
-		this.observationRegistry = observationRegistry;
-	}
+        Assert.notNull(siliconFlowImageApi, "OpenAiImageApi must not be null");
+        Assert.notNull(options, "options must not be null");
+        Assert.notNull(retryTemplate, "retryTemplate must not be null");
+        Assert.notNull(observationRegistry, "observationRegistry must not be null");
+        this.siliconFlowImageApi = siliconFlowImageApi;
+        this.defaultOptions = options;
+        this.retryTemplate = retryTemplate;
+        this.observationRegistry = observationRegistry;
+    }
 
-	@Override
-	public ImageResponse call(ImagePrompt imagePrompt) {
+    @Override
+    public ImageResponse call(ImagePrompt imagePrompt) {
         SiliconFlowImageOptions requestImageOptions = mergeOptions(imagePrompt.getOptions(), this.defaultOptions);
         SiliconFlowImageApi.SiliconflowImageRequest imageRequest = createRequest(imagePrompt, requestImageOptions);
 
-		var observationContext = ImageModelObservationContext.builder()
-			.imagePrompt(imagePrompt)
-			.provider(SiliconFlowApiConstants.PROVIDER_NAME)
-			.requestOptions(imagePrompt.getOptions())
-			.build();
+        var observationContext = ImageModelObservationContext.builder()
+                .imagePrompt(imagePrompt)
+                .provider(SiliconFlowApiConstants.PROVIDER_NAME)
+                .imagePrompt(imagePrompt)
+                .build();
 
-		return ImageModelObservationDocumentation.IMAGE_MODEL_OPERATION
-			.observation(this.observationConvention, DEFAULT_OBSERVATION_CONVENTION, () -> observationContext,
-					this.observationRegistry)
-			.observe(() -> {
-				ResponseEntity<OpenAiImageApi.OpenAiImageResponse> imageResponseEntity = this.retryTemplate
-					.execute(ctx -> this.siliconFlowImageApi.createImage(imageRequest));
+        return ImageModelObservationDocumentation.IMAGE_MODEL_OPERATION
+                .observation(this.observationConvention, DEFAULT_OBSERVATION_CONVENTION, () -> observationContext,
+                        this.observationRegistry)
+                .observe(() -> {
+                    ResponseEntity<OpenAiImageApi.OpenAiImageResponse> imageResponseEntity = this.retryTemplate
+                            .execute(ctx -> this.siliconFlowImageApi.createImage(imageRequest));
 
-				ImageResponse imageResponse = convertResponse(imageResponseEntity, imageRequest);
+                    ImageResponse imageResponse = convertResponse(imageResponseEntity, imageRequest);
 
-				observationContext.setResponse(imageResponse);
+                    observationContext.setResponse(imageResponse);
 
-				return imageResponse;
-			});
-	}
+                    return imageResponse;
+                });
+    }
 
-	private SiliconFlowImageApi.SiliconflowImageRequest createRequest(ImagePrompt imagePrompt,
+    private SiliconFlowImageApi.SiliconflowImageRequest createRequest(ImagePrompt imagePrompt,
                                                                       SiliconFlowImageOptions requestImageOptions) {
-		String instructions = imagePrompt.getInstructions().get(0).getText();
+        String instructions = imagePrompt.getInstructions().get(0).getText();
 
-		SiliconFlowImageApi.SiliconflowImageRequest imageRequest = new SiliconFlowImageApi.SiliconflowImageRequest(instructions,
+        SiliconFlowImageApi.SiliconflowImageRequest imageRequest = new SiliconFlowImageApi.SiliconflowImageRequest(instructions,
                 SiliconFlowApiConstants.DEFAULT_IMAGE_MODEL);
 
-		return ModelOptionsUtils.merge(requestImageOptions, imageRequest, SiliconFlowImageApi.SiliconflowImageRequest.class);
-	}
+        return ModelOptionsUtils.merge(requestImageOptions, imageRequest, SiliconFlowImageApi.SiliconflowImageRequest.class);
+    }
 
-	private ImageResponse convertResponse(ResponseEntity<OpenAiImageApi.OpenAiImageResponse> imageResponseEntity,
-										  SiliconFlowImageApi.SiliconflowImageRequest siliconflowImageRequest) {
-		OpenAiImageApi.OpenAiImageResponse imageApiResponse = imageResponseEntity.getBody();
-		if (imageApiResponse == null) {
-			logger.warn("No image response returned for request: {}", siliconflowImageRequest);
-			return new ImageResponse(List.of());
-		}
+    private ImageResponse convertResponse(ResponseEntity<OpenAiImageApi.OpenAiImageResponse> imageResponseEntity,
+                                          SiliconFlowImageApi.SiliconflowImageRequest siliconflowImageRequest) {
+        OpenAiImageApi.OpenAiImageResponse imageApiResponse = imageResponseEntity.getBody();
+        if (imageApiResponse == null) {
+            logger.warn("No image response returned for request: {}", siliconflowImageRequest);
+            return new ImageResponse(List.of());
+        }
 
-		List<ImageGeneration> imageGenerationList = imageApiResponse.data()
-			.stream()
-			.map(entry -> new ImageGeneration(new Image(entry.url(), entry.b64Json()),
-					new OpenAiImageGenerationMetadata(entry.revisedPrompt())))
-			.toList();
+        List<ImageGeneration> imageGenerationList = imageApiResponse.data()
+                .stream()
+                .map(entry -> new ImageGeneration(new Image(entry.url(), entry.b64Json()),
+                        new OpenAiImageGenerationMetadata(entry.revisedPrompt())))
+                .toList();
 
-		ImageResponseMetadata openAiImageResponseMetadata = new ImageResponseMetadata(imageApiResponse.created());
-		return new ImageResponse(imageGenerationList, openAiImageResponseMetadata);
-	}
+        ImageResponseMetadata openAiImageResponseMetadata = new ImageResponseMetadata(imageApiResponse.created());
+        return new ImageResponse(imageGenerationList, openAiImageResponseMetadata);
+    }
 
     private SiliconFlowImageOptions mergeOptions(@Nullable ImageOptions runtimeOptions, SiliconFlowImageOptions defaultOptions) {
         var runtimeOptionsForProvider = ModelOptionsUtils.copyToTarget(runtimeOptions, ImageOptions.class,

yudao-module-ai/yudao-module-ai-server/src/main/java/cn/iocoder/yudao/module/ai/service/image/AiImageServiceImpl.java

@@ -29,12 +29,12 @@ import cn.iocoder.yudao.module.infra.api.file.FileApi;
 import com.alibaba.cloud.ai.dashscope.image.DashScopeImageOptions;
 import jakarta.annotation.Resource;
 import lombok.extern.slf4j.Slf4j;
+import org.springaicommunity.qianfan.QianFanImageOptions;
 import org.springframework.ai.image.ImageModel;
 import org.springframework.ai.image.ImageOptions;
 import org.springframework.ai.image.ImagePrompt;
 import org.springframework.ai.image.ImageResponse;
 import org.springframework.ai.openai.OpenAiImageOptions;
-import org.springframework.ai.qianfan.QianFanImageOptions;
 import org.springframework.ai.stabilityai.api.StabilityAiImageOptions;
 import org.springframework.ai.zhipuai.ZhiPuAiImageOptions;
 import org.springframework.scheduling.annotation.Async;
@@ -140,10 +140,10 @@ public class AiImageServiceImpl implements AiImageService {
     private static ImageOptions buildImageOptions(AiImageDrawReqVO draw, AiModelDO model) {
         if (ObjUtil.equal(model.getPlatform(), AiPlatformEnum.OPENAI.getPlatform())) {
             // https://platform.openai.com/docs/api-reference/images/create
-            return OpenAiImageOptions.builder().withModel(model.getModel())
-                    .withHeight(draw.getHeight()).withWidth(draw.getWidth())
-                    .withStyle(MapUtil.getStr(draw.getOptions(), "style")) // 风格
-                    .withResponseFormat("b64_json")
+            return OpenAiImageOptions.builder().model(model.getModel())
+                    .height(draw.getHeight()).width(draw.getWidth())
+                    .style(MapUtil.getStr(draw.getOptions(), "style")) // 风格
+                    .responseFormat("b64_json")
                     .build();
         } else if (ObjUtil.equal(model.getPlatform(), AiPlatformEnum.SILICON_FLOW.getPlatform())) {
             // https://docs.siliconflow.cn/cn/api-reference/images/images-generations

yudao-module-ai/yudao-module-ai-server/src/main/java/cn/iocoder/yudao/module/ai/service/model/tool/UserProfileQueryToolFunction.java

@@ -7,6 +7,8 @@ import cn.iocoder.yudao.framework.tenant.core.util.TenantUtils;
 import cn.iocoder.yudao.module.system.api.user.AdminUserApi;
 import cn.iocoder.yudao.module.system.api.user.dto.AdminUserRespDTO;
 import com.fasterxml.jackson.annotation.JsonClassDescription;
+import com.fasterxml.jackson.annotation.JsonProperty;
+import com.fasterxml.jackson.annotation.JsonPropertyDescription;
 import jakarta.annotation.Resource;
 import lombok.AllArgsConstructor;
 import lombok.Data;
@@ -17,7 +19,7 @@ import org.springframework.stereotype.Component;
 import java.util.function.BiFunction;
 
 /**
- * 工具：当前用户信息查询
+ * 工具：用户信息查询
  *
  * 同时，也是展示 ToolContext 上下文的使用
  *
@@ -31,8 +33,17 @@ public class UserProfileQueryToolFunction
     private AdminUserApi adminUserApi;
 
     @Data
-    @JsonClassDescription("当前用户信息查询")
-    public static class Request { }
+    @JsonClassDescription("用户信息查询")
+    public static class Request {
+
+        /**
+         * 用户编号
+         */
+        @JsonProperty(value = "id")
+        @JsonPropertyDescription("用户编号，例如说：1。如果查询自己，则 id 为空")
+        private Long id;
+
+    }
 
     @Data
     @AllArgsConstructor
@@ -61,13 +72,19 @@ public class UserProfileQueryToolFunction
 
     @Override
     public Response apply(Request request, ToolContext toolContext) {
-        LoginUser loginUser = (LoginUser) toolContext.getContext().get(AiUtils.TOOL_CONTEXT_LOGIN_USER);
         Long tenantId = (Long) toolContext.getContext().get(AiUtils.TOOL_CONTEXT_TENANT_ID);
-        if (loginUser == null | tenantId == null) {
-            return null;
+        if (tenantId == null) {
+            return new Response();
+        }
+        if (request.getId() == null) {
+            LoginUser loginUser = (LoginUser) toolContext.getContext().get(AiUtils.TOOL_CONTEXT_LOGIN_USER);
+            if (loginUser == null) {
+                return new Response();
+            }
+            request.setId(loginUser.getId());
         }
         return TenantUtils.execute(tenantId, () -> {
-            AdminUserRespDTO user = adminUserApi.getUser(loginUser.getId()).getCheckedData();
+            AdminUserRespDTO user = adminUserApi.getUser(request.getId()).getCheckedData();
             return BeanUtils.toBean(user, Response.class);
         });
     }

yudao-module-ai/yudao-module-ai-server/src/main/java/cn/iocoder/yudao/module/ai/util/AiUtils.java

@@ -2,18 +2,18 @@ package cn.iocoder.yudao.module.ai.util;
 
 import cn.hutool.core.util.ObjUtil;
 import cn.hutool.core.util.StrUtil;
-import cn.iocoder.yudao.module.ai.enums.model.AiPlatformEnum;
 import cn.iocoder.yudao.framework.security.core.util.SecurityFrameworkUtils;
 import cn.iocoder.yudao.framework.tenant.core.context.TenantContextHolder;
+import cn.iocoder.yudao.module.ai.enums.model.AiPlatformEnum;
 import com.alibaba.cloud.ai.dashscope.chat.DashScopeChatOptions;
+import org.springaicommunity.moonshot.MoonshotChatOptions;
+import org.springaicommunity.qianfan.QianFanChatOptions;
 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;
 import org.springframework.ai.zhipuai.ZhiPuAiChatOptions;
 
 import java.util.Collections;
@@ -43,18 +43,18 @@ public class AiUtils {
         switch (platform) {
             case TONG_YI:
                 return DashScopeChatOptions.builder().withModel(model).withTemperature(temperature).withMaxToken(maxTokens)
-                        .withFunctions(toolNames).withToolContext(toolContext).build();
+                        .withToolNames(toolNames).withToolContext(toolContext).build();
             case YI_YAN:
                 return QianFanChatOptions.builder().model(model).temperature(temperature).maxTokens(maxTokens).build();
             case ZHI_PU:
                 return ZhiPuAiChatOptions.builder().model(model).temperature(temperature).maxTokens(maxTokens)
-                        .functions(toolNames).toolContext(toolContext).build();
+                        .toolNames(toolNames).toolContext(toolContext).build();
             case MINI_MAX:
                 return MiniMaxChatOptions.builder().model(model).temperature(temperature).maxTokens(maxTokens)
-                        .functions(toolNames).toolContext(toolContext).build();
+                        .toolNames(toolNames).toolContext(toolContext).build();
             case MOONSHOT:
                 return MoonshotChatOptions.builder().model(model).temperature(temperature).maxTokens(maxTokens)
-                        .functions(toolNames).toolContext(toolContext).build();
+                        .toolNames(toolNames).toolContext(toolContext).build();
             case OPENAI:
             case DEEP_SEEK: // 复用 OpenAI 客户端
             case DOU_BAO: // 复用 OpenAI 客户端

yudao-module-ai/yudao-module-ai-server/src/main/resources/application-dev.yaml

@@ -20,8 +20,8 @@ spring:
   # 数据源配置项
   autoconfigure:
     exclude:
-      - org.springframework.ai.autoconfigure.vectorstore.qdrant.QdrantVectorStoreAutoConfiguration # 禁用 AI 模块的 Qdrant，手动创建
-      - org.springframework.ai.autoconfigure.vectorstore.milvus.MilvusVectorStoreAutoConfiguration # 禁用 AI 模块的 Milvus，手动创建
+      - org.springframework.ai.vectorstore.qdrant.autoconfigure.QdrantVectorStoreAutoConfiguration # 禁用 AI 模块的 Qdrant，手动创建
+      - org.springframework.ai.vectorstore.milvus.autoconfigure.MilvusVectorStoreAutoConfiguration # 禁用 AI 模块的 Milvus，手动创建
   datasource:
     druid: # Druid 【监控】相关的全局配置
       web-stat-filter:

yudao-module-ai/yudao-module-ai-server/src/main/resources/application-local.yaml

@@ -21,8 +21,8 @@ spring:
   autoconfigure:
     exclude:
       - de.codecentric.boot.admin.client.config.SpringBootAdminClientAutoConfiguration # 禁用 Spring Boot Admin 的 Client 的自动配置
-      - org.springframework.ai.autoconfigure.vectorstore.qdrant.QdrantVectorStoreAutoConfiguration # 禁用 AI 模块的 Qdrant，手动创建
-      - org.springframework.ai.autoconfigure.vectorstore.milvus.MilvusVectorStoreAutoConfiguration # 禁用 AI 模块的 Milvus，手动创建
+      - org.springframework.ai.vectorstore.qdrant.autoconfigure.QdrantVectorStoreAutoConfiguration # 禁用 AI 模块的 Qdrant，手动创建
+      - org.springframework.ai.vectorstore.milvus.autoconfigure.MilvusVectorStoreAutoConfiguration # 禁用 AI 模块的 Milvus，手动创建
   datasource:
     druid: # Druid 【监控】相关的全局配置
       web-stat-filter:

yudao-module-ai/yudao-module-ai-server/src/main/resources/application.yaml

@@ -107,7 +107,7 @@ spring:
     vectorstore: # 向量存储
       redis:
         initialize-schema: true
-        index: knowledge_index # Redis 中向量索引的名称：用于存储和检索向量数据的索引标识符，所有相关的向量搜索操作都会基于这个索引进行
+        index-name: knowledge_index # Redis 中向量索引的名称：用于存储和检索向量数据的索引标识符，所有相关的向量搜索操作都会基于这个索引进行
         prefix: "knowledge_segment:" # Redis 中存储向量数据的键名前缀：这个前缀会添加到每个存储在 Redis 中的向量数据键名前，每个 document 都是一个 hash 结构
       qdrant:
         initialize-schema: true
@@ -145,13 +145,14 @@ spring:
       api-key: xxxx
     moonshot: # 月之暗灭（KIMI）
       api-key: sk-abc
+    deepseek: # DeepSeek
+      api-key: sk-e94db327cc7d457d99a8de8810fc6b12
+      chat:
+        options:
+          model: deepseek-chat
 
 yudao:
   ai:
-    deep-seek: # DeepSeek
-      enable: true
-      api-key: sk-e94db327cc7d457d99a8de8810fc6b12
-      model: deepseek-chat
     doubao: # 字节豆包
       enable: true
       api-key: 5c1b5747-26d2-4ebd-a4e0-dd0e8d8b4272

yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/chat/AzureOpenAIChatModelTests.java

@@ -2,7 +2,6 @@ package cn.iocoder.yudao.module.ai.framework.ai.core.model.chat;
 
 import com.azure.ai.openai.OpenAIClientBuilder;
 import com.azure.core.credential.AzureKeyCredential;
-import com.azure.core.util.ClientOptions;
 import org.junit.jupiter.api.Disabled;
 import org.junit.jupiter.api.Test;
 import org.springframework.ai.azure.openai.AzureOpenAiChatModel;
@@ -17,7 +16,7 @@ import reactor.core.publisher.Flux;
 import java.util.ArrayList;
 import java.util.List;
 
-import static org.springframework.ai.autoconfigure.azure.openai.AzureOpenAiChatProperties.DEFAULT_DEPLOYMENT_NAME;
+import static org.springframework.ai.model.azure.openai.autoconfigure.AzureOpenAiChatProperties.DEFAULT_DEPLOYMENT_NAME;
 
 /**
  * {@link AzureOpenAiChatModel} 集成测试
@@ -29,10 +28,13 @@ public class AzureOpenAIChatModelTests {
     // TODO @芋艿：晚点在调整
     private final OpenAIClientBuilder openAiApi = new OpenAIClientBuilder()
             .endpoint("https://eastusprejade.openai.azure.com")
-            .credential(new AzureKeyCredential("xxx"))
-            .clientOptions((new ClientOptions()).setApplicationId("spring-ai"));
-    private final AzureOpenAiChatModel chatModel = new AzureOpenAiChatModel(openAiApi,
-            AzureOpenAiChatOptions.builder().deploymentName(DEFAULT_DEPLOYMENT_NAME).build());
+            .credential(new AzureKeyCredential("xxx"));
+    private final AzureOpenAiChatModel chatModel = AzureOpenAiChatModel.builder()
+            .openAIClientBuilder(openAiApi)
+            .defaultOptions(AzureOpenAiChatOptions.builder()
+                    .deploymentName(DEFAULT_DEPLOYMENT_NAME)
+                    .build())
+            .build();
 
     @Test
     @Disabled

yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/chat/BaiChuanChatModelTests.java

@@ -1,7 +1,6 @@
 package cn.iocoder.yudao.module.ai.framework.ai.core.model.chat;
 
 import cn.iocoder.yudao.module.ai.framework.ai.core.model.baichuan.BaiChuanChatModel;
-import cn.iocoder.yudao.module.ai.framework.ai.core.model.deepseek.DeepSeekChatModel;
 import org.junit.jupiter.api.Disabled;
 import org.junit.jupiter.api.Test;
 import org.springframework.ai.chat.messages.Message;
@@ -35,7 +34,7 @@ public class BaiChuanChatModelTests {
                     .build())
             .build();
 
-    private final DeepSeekChatModel chatModel = new DeepSeekChatModel(openAiChatModel);
+    private final BaiChuanChatModel chatModel = new BaiChuanChatModel(openAiChatModel);
 
     @Test
     @Disabled

yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/chat/DeepSeekChatModelTests.java

@@ -1,6 +1,5 @@
 package cn.iocoder.yudao.module.ai.framework.ai.core.model.chat;
 
-import cn.iocoder.yudao.module.ai.framework.ai.core.model.deepseek.DeepSeekChatModel;
 import org.junit.jupiter.api.Disabled;
 import org.junit.jupiter.api.Test;
 import org.springframework.ai.chat.messages.Message;
@@ -8,9 +7,9 @@ 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.openai.OpenAiChatModel;
-import org.springframework.ai.openai.OpenAiChatOptions;
-import org.springframework.ai.openai.api.OpenAiApi;
+import org.springframework.ai.deepseek.DeepSeekChatModel;
+import org.springframework.ai.deepseek.DeepSeekChatOptions;
+import org.springframework.ai.deepseek.api.DeepSeekApi;
 import reactor.core.publisher.Flux;
 
 import java.util.ArrayList;
@@ -23,19 +22,16 @@ import java.util.List;
  */
 public class DeepSeekChatModelTests {
 
-    private final OpenAiChatModel openAiChatModel = OpenAiChatModel.builder()
-            .openAiApi(OpenAiApi.builder()
-                    .baseUrl(DeepSeekChatModel.BASE_URL)
-                    .apiKey("sk-e52047409b144d97b791a6a46a2d") // apiKey
+    private final DeepSeekChatModel chatModel = DeepSeekChatModel.builder()
+            .deepSeekApi(DeepSeekApi.builder()
+                    .apiKey("sk-eaf4172a057344dd9bc64b1f806b6axx") // apiKey
                     .build())
-            .defaultOptions(OpenAiChatOptions.builder()
+            .defaultOptions(DeepSeekChatOptions.builder()
                     .model("deepseek-chat") // 模型
                     .temperature(0.7)
                     .build())
             .build();
 
-    private final DeepSeekChatModel chatModel = new DeepSeekChatModel(openAiChatModel);
-
     @Test
     @Disabled
     public void testCall() {

yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/chat/LlamaChatModelTests.java

@@ -1,20 +1,6 @@
 package cn.iocoder.yudao.module.ai.framework.ai.core.model.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.ollama.OllamaChatModel;
-import org.springframework.ai.ollama.api.OllamaApi;
-import org.springframework.ai.ollama.api.OllamaModel;
-import org.springframework.ai.ollama.api.OllamaOptions;
-import reactor.core.publisher.Flux;
-
-import java.util.ArrayList;
-import java.util.List;
 
 /**
  * {@link OllamaChatModel} 集成测试
@@ -23,43 +9,43 @@ import java.util.List;
  */
 public class LlamaChatModelTests {
 
-    private final OllamaChatModel chatModel = OllamaChatModel.builder()
-            .ollamaApi(new OllamaApi("http://127.0.0.1:11434")) // Ollama 服务地址
-            .defaultOptions(OllamaOptions.builder()
-                    .model(OllamaModel.LLAMA3.getName()) // 模型
-                    .build())
-            .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();
-    }
+//    private final OllamaChatModel chatModel = OllamaChatModel.builder()
+//            .ollamaApi(new OllamaApi("http://127.0.0.1:11434")) // Ollama 服务地址
+//            .defaultOptions(OllamaOptions.builder()
+//                    .model(OllamaModel.LLAMA3.getName()) // 模型
+//                    .build())
+//            .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();
+//    }
 
 }

yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/chat/MoonshotChatModelTests.java

@@ -2,14 +2,14 @@ package cn.iocoder.yudao.module.ai.framework.ai.core.model.chat;
 
 import org.junit.jupiter.api.Disabled;
 import org.junit.jupiter.api.Test;
+import org.springaicommunity.moonshot.MoonshotChatModel;
+import org.springaicommunity.moonshot.MoonshotChatOptions;
+import org.springaicommunity.moonshot.api.MoonshotApi;
 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;
@@ -22,11 +22,15 @@ import java.util.List;
  */
 public class MoonshotChatModelTests {
 
-    private final MoonshotChatModel chatModel = new MoonshotChatModel(
-            new MoonshotApi("sk-aHYYV1SARscItye5QQRRNbXij4fy65Ee7pNZlC9gsSQnUKXA"), // 密钥
-            MoonshotChatOptions.builder()
-                    .model("moonshot-v1-8k") // 模型
-                    .build());
+    private final MoonshotChatModel chatModel = MoonshotChatModel.builder()
+            .moonshotApi(MoonshotApi.builder()
+                    .apiKey("sk-aHYYV1SARscItye5QQRRNbXij4fy65Ee7pNZlC9gsSQnUKXA") // 密钥
+                    .build())
+            .defaultOptions(MoonshotChatOptions.builder()
+                    .model("kimi-k2-0711-preview") // 模型
+                    .build())
+            .build();
+
     @Test
     @Disabled
     public void testCall() {

yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/chat/OllamaChatModelTests.java

@@ -23,7 +23,9 @@ import java.util.List;
 public class OllamaChatModelTests {
 
     private final OllamaChatModel chatModel = OllamaChatModel.builder()
-            .ollamaApi(new OllamaApi("http://127.0.0.1:11434")) // Ollama 服务地址
+            .ollamaApi(OllamaApi.builder()
+                    .baseUrl("http://127.0.0.1:11434") // Ollama 服务地址
+                    .build())
             .defaultOptions(OllamaOptions.builder()
 //                    .model("qwen") // 模型（https://ollama.com/library/qwen）
                     .model("deepseek-r1") // 模型（https://ollama.com/library/deepseek-r1）

yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/chat/OpenAIChatModelTests.java

@@ -25,10 +25,10 @@ public class OpenAIChatModelTests {
     private final OpenAiChatModel chatModel = OpenAiChatModel.builder()
             .openAiApi(OpenAiApi.builder()
                     .baseUrl("https://api.holdai.top")
-                    .apiKey("sk-aN6nWn3fILjrgLFT0fC4Aa60B72e4253826c77B29dC94f17") // apiKey
+                    .apiKey("sk-PytRecQlmjEteoa2RRN6cGnwslo72UUPLQVNEMS6K9yjbmpD") // apiKey
                     .build())
             .defaultOptions(OpenAiChatOptions.builder()
-                    .model(OpenAiApi.ChatModel.GPT_4_O) // 模型
+                    .model(OpenAiApi.ChatModel.GPT_4_1_NANO) // 模型
                     .temperature(0.7)
                     .build())
             .build();

yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/chat/TongYiChatModelTests.java

@@ -22,14 +22,17 @@ import java.util.List;
  */
 public class TongYiChatModelTests {
 
-    private final DashScopeChatModel chatModel = new DashScopeChatModel(
-            new DashScopeApi("sk-7d903764249848cfa912733146da12d1"),
-            DashScopeChatOptions.builder()
+    private final DashScopeChatModel chatModel = DashScopeChatModel.builder()
+            .dashScopeApi(DashScopeApi.builder()
+                    .apiKey("sk-47aa124781be4bfb95244cc62f63f7d0")
+                    .build())
+            .defaultOptions( DashScopeChatOptions.builder()
                     .withModel("qwen1.5-72b-chat") // 模型
 //                    .withModel("deepseek-r1") // 模型（deepseek-r1）
 //                    .withModel("deepseek-v3") // 模型（deepseek-v3）
 //                    .withModel("deepseek-r1-distill-qwen-1.5b") // 模型（deepseek-r1-distill-qwen-1.5b）
-                    .build());
+                    .build())
+            .build();
 
     @Test
     @Disabled

yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/chat/YiYanChatModelTests.java

@@ -2,13 +2,13 @@ package cn.iocoder.yudao.module.ai.framework.ai.core.model.chat;
 
 import org.junit.jupiter.api.Disabled;
 import org.junit.jupiter.api.Test;
+import org.springaicommunity.qianfan.QianFanChatModel;
+import org.springaicommunity.qianfan.QianFanChatOptions;
+import org.springaicommunity.qianfan.api.QianFanApi;
 import org.springframework.ai.chat.messages.Message;
 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.qianfan.QianFanChatModel;
-import org.springframework.ai.qianfan.QianFanChatOptions;
-import org.springframework.ai.qianfan.api.QianFanApi;
 import reactor.core.publisher.Flux;
 
 import java.util.ArrayList;
@@ -23,9 +23,9 @@ import java.util.List;
 public class YiYanChatModelTests {
 
     private final QianFanChatModel chatModel = new QianFanChatModel(
-            new QianFanApi("qS8k8dYr2nXunagK4SSU8Xjj", "pHGbx51ql2f0hOyabQvSZezahVC3hh3e"), // 密钥
+            new QianFanApi("DGnyzREuaY7av7c38bOM9Ji2", "9aR8myflEOPDrEeLhoXv0FdqANOAyIZW"), // 密钥
             QianFanChatOptions.builder()
-                    .model(QianFanApi.ChatModel.ERNIE_4_0_8K_Preview.getValue())
+                    .model("ERNIE-4.5-8K-Preview")
                     .build()
     );
 

yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/image/OpenAiImageModelTests.java

@@ -18,7 +18,7 @@ public class OpenAiImageModelTests {
 
     private final OpenAiImageModel imageModel = new OpenAiImageModel(OpenAiImageApi.builder()
             .baseUrl("https://api.holdai.top") // apiKey
-            .apiKey("sk-aN6nWn3fILjrgLFT0fC4Aa60B72e4253826c77B29dC94f17")
+            .apiKey("sk-PytRecQlmjEteoa2RRN6cGnwslo72UUPLQVNEMS6K9yjbmpD")
             .build());
 
     @Test
@@ -26,8 +26,8 @@ public class OpenAiImageModelTests {
     public void testCall() {
         // 准备参数
         ImageOptions options = OpenAiImageOptions.builder()
-                .withModel(OpenAiImageApi.ImageModel.DALL_E_2.getValue()) // 这个模型比较便宜
-                .withHeight(256).withWidth(256)
+                .model(OpenAiImageApi.ImageModel.DALL_E_2.getValue()) // 这个模型比较便宜
+                .height(256).width(256)
                 .build();
         ImagePrompt prompt = new ImagePrompt("中国长城!", options);
 

yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/image/QianFanImageTests.java

@@ -2,11 +2,11 @@ package cn.iocoder.yudao.module.ai.framework.ai.core.model.image;
 
 import org.junit.jupiter.api.Disabled;
 import org.junit.jupiter.api.Test;
+import org.springaicommunity.qianfan.QianFanImageModel;
+import org.springaicommunity.qianfan.QianFanImageOptions;
+import org.springaicommunity.qianfan.api.QianFanImageApi;
 import org.springframework.ai.image.ImagePrompt;
 import org.springframework.ai.image.ImageResponse;
-import org.springframework.ai.qianfan.QianFanImageModel;
-import org.springframework.ai.qianfan.QianFanImageOptions;
-import org.springframework.ai.qianfan.api.QianFanImageApi;
 
 import static cn.iocoder.yudao.module.ai.framework.ai.core.model.image.StabilityAiImageModelTests.viewImage;
 

yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/image/StabilityAiImageModelTests.java

@@ -31,8 +31,8 @@ public class StabilityAiImageModelTests {
     public void testCall() {
         // 准备参数
         ImageOptions options = OpenAiImageOptions.builder()
-                .withModel("stable-diffusion-v1-6")
-                .withHeight(320).withWidth(320)
+                .model("stable-diffusion-v1-6")
+                .height(320).width(320)
                 .build();
         ImagePrompt prompt = new ImagePrompt("great wall", options);
 

yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/ppt/wdd/WenDuoDuoPptApiTests.java

@@ -1,7 +1,7 @@
 package cn.iocoder.yudao.module.ai.framework.ai.core.model.ppt.wdd;
 
-import cn.iocoder.yudao.module.ai.framework.ai.core.model.wenduoduo.api.WenDuoDuoPptApi;
 import cn.iocoder.yudao.framework.common.util.json.JsonUtils;
+import cn.iocoder.yudao.module.ai.framework.ai.core.model.wenduoduo.api.WenDuoDuoPptApi;
 import org.junit.jupiter.api.Disabled;
 import org.junit.jupiter.api.Test;
 import reactor.core.publisher.Flux;

yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/ppt/xunfei/XunFeiPptApiTests.java

@@ -1,8 +1,8 @@
 package cn.iocoder.yudao.module.ai.framework.ai.core.model.ppt.xunfei;
 
 import cn.hutool.core.io.FileUtil;
-import cn.iocoder.yudao.module.ai.framework.ai.core.model.xinghuo.api.XunFeiPptApi;
 import cn.iocoder.yudao.framework.common.util.json.JsonUtils;
+import cn.iocoder.yudao.module.ai.framework.ai.core.model.xinghuo.api.XunFeiPptApi;
 import org.junit.jupiter.api.Disabled;
 import org.junit.jupiter.api.Test;
 import org.springframework.mock.web.MockMultipartFile;

yudao-server/src/main/resources/application-dev.yaml

@@ -6,8 +6,8 @@ server:
 spring:
   autoconfigure:
     exclude:
-      - org.springframework.ai.autoconfigure.vectorstore.qdrant.QdrantVectorStoreAutoConfiguration # 禁用 AI 模块的 Qdrant，手动创建
-      - org.springframework.ai.autoconfigure.vectorstore.milvus.MilvusVectorStoreAutoConfiguration # 禁用 AI 模块的 Milvus，手动创建
+      - org.springframework.ai.vectorstore.qdrant.autoconfigure.QdrantVectorStoreAutoConfiguration # 禁用 AI 模块的 Qdrant，手动创建
+      - org.springframework.ai.vectorstore.milvus.autoconfigure.MilvusVectorStoreAutoConfiguration # 禁用 AI 模块的 Milvus，手动创建
   # 数据源配置项
   datasource:
     druid: # Druid 【监控】相关的全局配置

yudao-server/src/main/resources/application-local.yaml

@@ -10,8 +10,8 @@ spring:
       - de.codecentric.boot.admin.server.ui.config.AdminServerUiAutoConfiguration # 禁用 Spring Boot Admin 的 Server UI 的自动配置
       - de.codecentric.boot.admin.server.cloud.config.AdminServerDiscoveryAutoConfiguration # 禁用 Spring Boot Admin 的 Server 的自动配置
       - de.codecentric.boot.admin.client.config.SpringBootAdminClientAutoConfiguration # 禁用 Spring Boot Admin 的 Client 的自动配置
-      - org.springframework.ai.autoconfigure.vectorstore.qdrant.QdrantVectorStoreAutoConfiguration # 禁用 AI 模块的 Qdrant，手动创建
-      - org.springframework.ai.autoconfigure.vectorstore.milvus.MilvusVectorStoreAutoConfiguration # 禁用 AI 模块的 Milvus，手动创建
+      - org.springframework.ai.vectorstore.qdrant.autoconfigure.QdrantVectorStoreAutoConfiguration # 禁用 AI 模块的 Qdrant，手动创建
+      - org.springframework.ai.vectorstore.milvus.autoconfigure.MilvusVectorStoreAutoConfiguration # 禁用 AI 模块的 Milvus，手动创建
   # 数据源配置项
   datasource:
     druid: # Druid 【监控】相关的全局配置

yudao-server/src/main/resources/application.yaml

@@ -174,7 +174,7 @@ spring:
     vectorstore: # 向量存储
       redis:
         initialize-schema: true
-        index: knowledge_index # Redis 中向量索引的名称：用于存储和检索向量数据的索引标识符，所有相关的向量搜索操作都会基于这个索引进行
+        index-name: knowledge_index # Redis 中向量索引的名称：用于存储和检索向量数据的索引标识符，所有相关的向量搜索操作都会基于这个索引进行
         prefix: "knowledge_segment:" # Redis 中存储向量数据的键名前缀：这个前缀会添加到每个存储在 Redis 中的向量数据键名前，每个 document 都是一个 hash 结构
       qdrant:
         initialize-schema: true
@@ -212,13 +212,14 @@ spring:
       api-key: xxxx
     moonshot: # 月之暗灭（KIMI）
       api-key: sk-abc
+    deepseek: # DeepSeek
+      api-key: sk-e94db327cc7d457d99a8de8810fc6b12
+      chat:
+        options:
+          model: deepseek-chat
 
 yudao:
   ai:
-    deep-seek: # DeepSeek
-      enable: true
-      api-key: sk-e94db327cc7d457d99a8de8810fc6b12
-      model: deepseek-chat
     doubao: # 字节豆包
       enable: true
       api-key: 5c1b5747-26d2-4ebd-a4e0-dd0e8d8b4272