【代码重构】AI：spring ai 依赖，升级到 1.0.0-M6

YunaiV
1 parent 3b7b8182
Showing 18 changed files with 197 additions and 712 deletions
yudao-module-ai/yudao-module-ai-biz/src/main/java/cn/iocoder/yudao/module/ai/framework/web/package-info.java
yudao-module-ai/yudao-module-ai-biz/src/main/java/cn/iocoder/yudao/module/ai/service/image/AiImageServiceImpl.java
yudao-module-ai/yudao-spring-boot-starter-ai/pom.xml
yudao-module-ai/yudao-spring-boot-starter-ai/src/main/java/cn/iocoder/yudao/framework/ai/config/YudaoAiAutoConfiguration.java
yudao-module-ai/yudao-spring-boot-starter-ai/src/main/java/cn/iocoder/yudao/framework/ai/config/YudaoAiProperties.java
yudao-module-ai/yudao-spring-boot-starter-ai/src/main/java/cn/iocoder/yudao/framework/ai/core/factory/AiModelFactoryImpl.java
yudao-module-ai/yudao-spring-boot-starter-ai/src/main/java/cn/iocoder/yudao/framework/ai/core/model/midjourney/api/MidjourneyApi.java
yudao-module-ai/yudao-spring-boot-starter-ai/src/main/java/cn/iocoder/yudao/framework/ai/core/util/AiUtils.java
yudao-module-ai/yudao-spring-boot-starter-ai/src/main/java/org/springframework/ai/autoconfigure/vectorstore/redis/RedisVectorStoreAutoConfiguration.java
yudao-module-ai/yudao-spring-boot-starter-ai/src/main/java/org/springframework/ai/vectorstore/RedisVectorStore.java
yudao-module-ai/yudao-spring-boot-starter-ai/src/test/java/cn/iocoder/yudao/framework/ai/chat/AzureOpenAIChatModelTests.java
yudao-module-ai/yudao-spring-boot-starter-ai/src/test/java/cn/iocoder/yudao/framework/ai/chat/LlamaChatModelTests.java
yudao-module-ai/yudao-spring-boot-starter-ai/src/test/java/cn/iocoder/yudao/framework/ai/chat/OpenAIChatModelTests.java
yudao-module-ai/yudao-spring-boot-starter-ai/src/test/java/cn/iocoder/yudao/framework/ai/chat/YiYanChatModelTests.java
yudao-module-ai/yudao-spring-boot-starter-ai/src/test/java/cn/iocoder/yudao/framework/ai/chat/ZhiPuAiChatModelTests.java
yudao-module-ai/yudao-spring-boot-starter-ai/src/test/java/cn/iocoder/yudao/framework/ai/image/QianFanImageTests.java
yudao-module-ai/yudao-spring-boot-starter-ai/src/test/java/cn/iocoder/yudao/framework/ai/image/TongYiImagesModelTest.java
yudao-module-ai/yudao-spring-boot-starter-ai/src/test/java/cn/iocoder/yudao/framework/ai/image/ZhiPuAiImageModelTests.java
 /**
- * crm 模块的 web 拓展封装
+ * ai 模块的 web 拓展封装
  */
-package cn.iocoder.yudao.module.crm.framework.web;
+package cn.iocoder.yudao.module.ai.framework.web;
@@ -20,7 +20,6 @@ import cn.iocoder.yudao.module.ai.dal.mysql.image.AiImageMapper;
 import cn.iocoder.yudao.module.ai.enums.image.AiImageStatusEnum;
 import cn.iocoder.yudao.module.ai.service.model.AiApiKeyService;
 import cn.iocoder.yudao.module.infra.api.file.FileApi;
-import com.alibaba.cloud.ai.tongyi.image.TongYiImagesOptions;
 import jakarta.annotation.Resource;
 import lombok.extern.slf4j.Slf4j;
 import org.springframework.ai.image.ImageModel;
@@ -144,7 +143,7 @@ public class AiImageServiceImpl implements AiImageService {
                     .withClipGuidancePreset(String.valueOf(draw.getOptions().get("clipGuidancePreset")))
                     .build();
         } else if (ObjUtil.equal(draw.getPlatform(), AiPlatformEnum.TONG_YI.getPlatform())) {
-            return TongYiImagesOptions.builder()
+            return DashScopeImageOptions.builder()
                     .withModel(draw.getModel()).withN(1)
                     .withHeight(draw.getHeight()).withWidth(draw.getWidth())
                     .build();
@@ -14,8 +14,8 @@
     <name>${project.artifactId}</name>
     <description>AI 大模型拓展，接入国内外大模型</description>
     <properties>
-        <spring-ai.groupId>group.springframework.ai</spring-ai.groupId>
-        <spring-ai.version>1.1.0</spring-ai.version>
+        <spring-ai.groupId>org.springframework.ai</spring-ai.groupId>
+        <spring-ai.version>1.0.0-M6</spring-ai.version>
     </properties>
     <dependencies>
@@ -90,6 +90,11 @@
             <artifactId>spring-ai-qianfan-spring-boot-starter</artifactId>
             <version>${spring-ai.version}</version>
         </dependency>
+        <dependency>
+            <groupId>com.alibaba.cloud.ai</groupId>
+            <artifactId>spring-ai-alibaba-starter</artifactId>
+            <version>1.0.0-M5.1</version>
+        </dependency>
         <!-- 阿里云 通义千问 -->
         <!-- TODO 芋艿：等 spring cloud alibaba ai 发布最新的时候，可以替换掉这个依赖，并且删除我们直接 cv 的代码 -->
 package cn.iocoder.yudao.framework.ai.config;
+import cn.hutool.core.util.StrUtil;
 import cn.iocoder.yudao.framework.ai.core.factory.AiModelFactory;
 import cn.iocoder.yudao.framework.ai.core.factory.AiModelFactoryImpl;
 import cn.iocoder.yudao.framework.ai.core.model.deepseek.DeepSeekChatModel;
-import cn.iocoder.yudao.framework.ai.core.model.deepseek.DeepSeekChatOptions;
 import cn.iocoder.yudao.framework.ai.core.model.midjourney.api.MidjourneyApi;
 import cn.iocoder.yudao.framework.ai.core.model.suno.api.SunoApi;
 import cn.iocoder.yudao.framework.ai.core.model.xinghuo.XingHuoChatModel;
-import cn.iocoder.yudao.framework.ai.core.model.xinghuo.XingHuoChatOptions;
-import com.alibaba.cloud.ai.tongyi.TongYiAutoConfiguration;
 import lombok.extern.slf4j.Slf4j;
+import org.springframework.ai.openai.OpenAiChatModel;
+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.transformer.splitter.TokenTextSplitter;
@@ -17,7 +18,6 @@ import org.springframework.boot.autoconfigure.AutoConfiguration;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnProperty;
 import org.springframework.boot.context.properties.EnableConfigurationProperties;
 import org.springframework.context.annotation.Bean;
-import org.springframework.context.annotation.Import;
 import org.springframework.context.annotation.Lazy;
 /**
@@ -28,7 +28,6 @@ import org.springframework.context.annotation.Lazy;
 @AutoConfiguration
 @EnableConfigurationProperties(YudaoAiProperties.class)
 @Slf4j
-@Import(TongYiAutoConfiguration.class)
 public class YudaoAiAutoConfiguration {
     @Bean
@@ -43,26 +42,52 @@ public class YudaoAiAutoConfiguration {
     @ConditionalOnProperty(value = "yudao.ai.deepseek.enable", havingValue = "true")
     public DeepSeekChatModel deepSeekChatModel(YudaoAiProperties yudaoAiProperties) {
         YudaoAiProperties.DeepSeekProperties properties = yudaoAiProperties.getDeepSeek();
-        DeepSeekChatOptions options = DeepSeekChatOptions.builder()
-                .model(properties.getModel())
-                .temperature(properties.getTemperature())
-                .maxTokens(properties.getMaxTokens())
-                .topP(properties.getTopP())
+        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())
                 .build();
-        return new DeepSeekChatModel(properties.getApiKey(), options);
+        return new DeepSeekChatModel(openAiChatModel);
     }
     @Bean
     @ConditionalOnProperty(value = "yudao.ai.xinghuo.enable", havingValue = "true")
     public XingHuoChatModel xingHuoChatClient(YudaoAiProperties yudaoAiProperties) {
         YudaoAiProperties.XingHuoProperties properties = yudaoAiProperties.getXinghuo();
-        XingHuoChatOptions options = XingHuoChatOptions.builder()
-                .model(properties.getModel())
-                .temperature(properties.getTemperature())
-                .maxTokens(properties.getMaxTokens())
-                .topK(properties.getTopK())
+        return buildXingHuoChatClient(properties);
+    }
+
+    public XingHuoChatModel buildXingHuoChatClient(YudaoAiProperties.XingHuoProperties properties) {
+        if (StrUtil.isEmpty(properties.getModel())) {
+            properties.setModel(XingHuoChatModel.MODEL_DEFAULT);
+        }
+        OpenAiChatModel openAiChatModel = OpenAiChatModel.builder()
+                .openAiApi(OpenAiApi.builder()
+                        .baseUrl(XingHuoChatModel.BASE_URL)
+                        .apiKey(properties.getAppKey() + ":" + properties.getSecretKey())
+                        .build())
+                .defaultOptions(OpenAiChatOptions.builder()
+                        .model(properties.getModel())
+                        .temperature(properties.getTemperature())
+                        .maxTokens(properties.getMaxTokens())
+                        .topP(properties.getTopP())
+                        .build())
                 .build();
-        return new XingHuoChatModel(properties.getAppKey(), properties.getSecretKey(), options);
+        return new XingHuoChatModel(openAiChatModel);
     }
     @Bean
@@ -42,9 +42,9 @@ public class YudaoAiProperties {
         private String secretKey;
         private String model;
-        private Float temperature;
+        private Double temperature;
         private Integer maxTokens;
-        private Integer topK;
+        private Double topP;
     }
@@ -55,9 +55,9 @@ public class YudaoAiProperties {
         private String apiKey;
         private String model;
-        private Float temperature;
+        private Double temperature;
         private Integer maxTokens;
-        private Float topP;
+        private Double topP;
     }
@@ -13,60 +13,45 @@ import cn.iocoder.yudao.framework.ai.core.model.deepseek.DeepSeekChatModel;
 import cn.iocoder.yudao.framework.ai.core.model.midjourney.api.MidjourneyApi;
 import cn.iocoder.yudao.framework.ai.core.model.suno.api.SunoApi;
 import cn.iocoder.yudao.framework.ai.core.model.xinghuo.XingHuoChatModel;
-import cn.iocoder.yudao.framework.common.util.spring.SpringUtils;
-import com.alibaba.cloud.ai.tongyi.TongYiAutoConfiguration;
-import com.alibaba.cloud.ai.tongyi.TongYiConnectionProperties;
-import com.alibaba.cloud.ai.tongyi.chat.TongYiChatModel;
-import com.alibaba.cloud.ai.tongyi.chat.TongYiChatProperties;
-import com.alibaba.cloud.ai.tongyi.image.TongYiImagesModel;
-import com.alibaba.cloud.ai.tongyi.image.TongYiImagesProperties;
-import com.alibaba.dashscope.aigc.generation.Generation;
-import com.alibaba.dashscope.aigc.imagesynthesis.ImageSynthesis;
-import com.alibaba.dashscope.embeddings.TextEmbedding;
-import com.azure.ai.openai.OpenAIClient;
+import com.alibaba.cloud.ai.autoconfigure.dashscope.DashScopeAutoConfiguration;
+import com.alibaba.cloud.ai.dashscope.api.DashScopeApi;
+import com.alibaba.cloud.ai.dashscope.api.DashScopeImageApi;
+import com.alibaba.cloud.ai.dashscope.chat.DashScopeChatModel;
+import com.alibaba.cloud.ai.dashscope.embedding.DashScopeEmbeddingModel;
+import com.alibaba.cloud.ai.dashscope.image.DashScopeImageModel;
+import com.azure.ai.openai.OpenAIClientBuilder;
 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.ollama.OllamaAutoConfiguration;
 import org.springframework.ai.autoconfigure.openai.OpenAiAutoConfiguration;
 import org.springframework.ai.autoconfigure.qianfan.QianFanAutoConfiguration;
-import org.springframework.ai.autoconfigure.qianfan.QianFanChatProperties;
-import org.springframework.ai.autoconfigure.qianfan.QianFanConnectionProperties;
-import org.springframework.ai.autoconfigure.qianfan.QianFanImageProperties;
 import org.springframework.ai.autoconfigure.zhipuai.ZhiPuAiAutoConfiguration;
-import org.springframework.ai.autoconfigure.zhipuai.ZhiPuAiChatProperties;
 import org.springframework.ai.autoconfigure.zhipuai.ZhiPuAiConnectionProperties;
-import org.springframework.ai.autoconfigure.zhipuai.ZhiPuAiImageProperties;
 import org.springframework.ai.azure.openai.AzureOpenAiChatModel;
 import org.springframework.ai.chat.model.ChatModel;
 import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.image.ImageModel;
-import org.springframework.ai.model.function.FunctionCallbackContext;
 import org.springframework.ai.ollama.OllamaChatModel;
 import org.springframework.ai.ollama.api.OllamaApi;
 import org.springframework.ai.openai.OpenAiChatModel;
 import org.springframework.ai.openai.OpenAiImageModel;
-import org.springframework.ai.openai.api.ApiUtils;
 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.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.RedisVectorStore;
+import org.springframework.ai.vectorstore.SimpleVectorStore;
 import org.springframework.ai.vectorstore.VectorStore;
 import org.springframework.ai.zhipuai.ZhiPuAiChatModel;
 import org.springframework.ai.zhipuai.ZhiPuAiImageModel;
 import org.springframework.ai.zhipuai.api.ZhiPuAiApi;
 import org.springframework.ai.zhipuai.api.ZhiPuAiImageApi;
-import org.springframework.boot.autoconfigure.data.redis.RedisProperties;
-import org.springframework.retry.support.RetryTemplate;
-import org.springframework.web.client.ResponseErrorHandler;
 import org.springframework.web.client.RestClient;
-import redis.clients.jedis.JedisPooled;
-import redis.clients.jedis.search.Schema;
 import java.util.List;
@@ -110,7 +95,7 @@ public class AiModelFactoryImpl implements AiModelFactory {
         //noinspection EnhancedSwitchMigration
         switch (platform) {
             case TONG_YI:
-                return SpringUtil.getBean(TongYiChatModel.class);
+                return SpringUtil.getBean(DashScopeChatModel.class);
             case YI_YAN:
                 return SpringUtil.getBean(QianFanChatModel.class);
             case DEEP_SEEK:
@@ -135,7 +120,7 @@ public class AiModelFactoryImpl implements AiModelFactory {
         //noinspection EnhancedSwitchMigration
         switch (platform) {
             case TONG_YI:
-                return SpringUtil.getBean(TongYiImagesModel.class);
+                return SpringUtil.getBean(DashScopeImageModel.class);
             case YI_YAN:
                 return SpringUtil.getBean(QianFanImageModel.class);
             case ZHI_PU:
@@ -202,17 +187,20 @@ public class AiModelFactoryImpl implements AiModelFactory {
         String cacheKey = buildClientCacheKey(VectorStore.class, platform, apiKey, url);
         return Singleton.get(cacheKey, (Func0<VectorStore>) () -> {
             String prefix = StrUtil.format("{}#{}:", platform.getPlatform(), apiKey);
-            var config = RedisVectorStore.RedisVectorStoreConfig.builder()
-                    .withIndexName(cacheKey)
-                    .withPrefix(prefix)
-                    .withMetadataFields(new RedisVectorStore.MetadataField("knowledgeId", Schema.FieldType.NUMERIC))
-                    .build();
-            RedisProperties redisProperties = SpringUtils.getBean(RedisProperties.class);
-            RedisVectorStore redisVectorStore = new RedisVectorStore(config, embeddingModel,
-                    new JedisPooled(redisProperties.getHost(), redisProperties.getPort()),
-                    true);
-            redisVectorStore.afterPropertiesSet();
-            return redisVectorStore;
+            // TODO @芋艿：先临时使用 store
+            return SimpleVectorStore.builder(embeddingModel).build();
+            // TODO @芋艿：@xin：后续看看，是不是切到阿里云之类的
+//            var config = RedisVectorStore.RedisVectorStoreConfig.builder()
+//                    .withIndexName(cacheKey)
+//                    .withPrefix(prefix)
+//                    .withMetadataFields(new RedisVectorStore.MetadataField("knowledgeId", Schema.FieldType.NUMERIC))
+//                    .build();
+//            RedisProperties redisProperties = SpringUtils.getBean(RedisProperties.class);
+//            RedisVectorStore redisVectorStore = new RedisVectorStore(config, embeddingModel,
+//                    new JedisPooled(redisProperties.getHost(), redisProperties.getPort()),
+//                    true);
+//            redisVectorStore.afterPropertiesSet();
+//            return redisVectorStore;
         });
     }
@@ -226,29 +214,23 @@ public class AiModelFactoryImpl implements AiModelFactory {
     // ========== 各种创建 spring-ai 客户端的方法 ==========
     /**
-     * 可参考 {@link TongYiAutoConfiguration#tongYiChatClient(Generation, TongYiChatProperties, TongYiConnectionProperties)}
+     * 可参考 {@link DashScopeAutoConfiguration} 的 dashscopeChatModel 方法
      */
-    private static TongYiChatModel buildTongYiChatModel(String key) {
-        com.alibaba.dashscope.aigc.generation.Generation generation = SpringUtil.getBean(Generation.class);
-        TongYiChatProperties chatOptions = SpringUtil.getBean(TongYiChatProperties.class);
-        // TODO @芋艿：貌似 apiKey 是全局唯一的？？？得测试下
-        // TODO @芋艿：貌似阿里云不是增量返回的
-        // 该 issue 进行跟进中 https://github.com/alibaba/spring-cloud-alibaba/issues/3790
-        TongYiConnectionProperties connectionProperties = new TongYiConnectionProperties();
-        connectionProperties.setApiKey(key);
-        return new TongYiAutoConfiguration().tongYiChatClient(generation, chatOptions, connectionProperties);
+    private static DashScopeChatModel buildTongYiChatModel(String key) {
+        DashScopeApi dashScopeApi = new DashScopeApi(key);
+        return new DashScopeChatModel(dashScopeApi);
     }
-    private static TongYiImagesModel buildTongYiImagesModel(String key) {
-        ImageSynthesis imageSynthesis = SpringUtil.getBean(ImageSynthesis.class);
-        TongYiImagesProperties imagesOptions = SpringUtil.getBean(TongYiImagesProperties.class);
-        TongYiConnectionProperties connectionProperties = new TongYiConnectionProperties();
-        connectionProperties.setApiKey(key);
-        return new TongYiAutoConfiguration().tongYiImagesClient(imageSynthesis, imagesOptions, connectionProperties);
+    /**
+     * 可参考 {@link DashScopeAutoConfiguration} 的 dashScopeImageModel 方法
+     */
+    private static DashScopeImageModel buildTongYiImagesModel(String key) {
+        DashScopeImageApi dashScopeImageApi = new DashScopeImageApi(key);
+        return new DashScopeImageModel(dashScopeImageApi);
     }
     /**
-     * 可参考 {@link QianFanAutoConfiguration#qianFanChatModel(QianFanConnectionProperties, QianFanChatProperties, RestClient.Builder, RetryTemplate, ResponseErrorHandler)}
+     * 可参考 {@link QianFanAutoConfiguration} 的 qianFanChatModel 方法
      */
     private static QianFanChatModel buildYiYanChatModel(String key) {
         List<String> keys = StrUtil.split(key, '|');
@@ -260,7 +242,7 @@ public class AiModelFactoryImpl implements AiModelFactory {
     }
     /**
-     * 可参考 {@link QianFanAutoConfiguration#qianFanImageModel(QianFanConnectionProperties, QianFanImageProperties, RestClient.Builder, RetryTemplate, ResponseErrorHandler)}
+     * 可参考 {@link QianFanAutoConfiguration} 的 qianFanImageModel 方法
      */
     private QianFanImageModel buildQianFanImageModel(String key) {
         List<String> keys = StrUtil.split(key, '|');
@@ -275,11 +257,13 @@ public class AiModelFactoryImpl implements AiModelFactory {
      * 可参考 {@link YudaoAiAutoConfiguration#deepSeekChatModel(YudaoAiProperties)}
      */
     private static DeepSeekChatModel buildDeepSeekChatModel(String apiKey) {
-        return new DeepSeekChatModel(apiKey);
+        YudaoAiProperties.DeepSeekProperties properties = new YudaoAiProperties.DeepSeekProperties()
+                .setApiKey(apiKey);
+        return new YudaoAiAutoConfiguration().buildDeepSeekChatModel(properties);
     }
     /**
-     * 可参考 {@link ZhiPuAiAutoConfiguration#zhiPuAiChatModel(ZhiPuAiConnectionProperties, ZhiPuAiChatProperties, RestClient.Builder, List, FunctionCallbackContext, RetryTemplate, ResponseErrorHandler)}
+     * 可参考 {@link ZhiPuAiAutoConfiguration} 的 zhiPuAiChatModel 方法
      */
     private ZhiPuAiChatModel buildZhiPuChatModel(String apiKey, String url) {
         url = StrUtil.blankToDefault(url, ZhiPuAiConnectionProperties.DEFAULT_BASE_URL);
@@ -288,7 +272,7 @@ public class AiModelFactoryImpl implements AiModelFactory {
     }
     /**
-     * 可参考 {@link ZhiPuAiAutoConfiguration#zhiPuAiImageModel(ZhiPuAiConnectionProperties, ZhiPuAiImageProperties, RestClient.Builder, RetryTemplate, ResponseErrorHandler)}
+     * 可参考 {@link ZhiPuAiAutoConfiguration} 的 zhiPuAiImageModel 方法
      */
     private ZhiPuAiImageModel buildZhiPuAiImageModel(String apiKey, String url) {
         url = StrUtil.blankToDefault(url, ZhiPuAiConnectionProperties.DEFAULT_BASE_URL);
@@ -301,21 +285,22 @@ public class AiModelFactoryImpl implements AiModelFactory {
      */
     private static XingHuoChatModel buildXingHuoChatModel(String key) {
         List<String> keys = StrUtil.split(key, '|');
-        Assert.equals(keys.size(), 3, "XingHuoChatClient 的密钥需要 (appid|appKey|secretKey) 格式");
-        String appKey = keys.get(1);
-        String secretKey = keys.get(2);
-        return new XingHuoChatModel(appKey, secretKey);
+        Assert.equals(keys.size(), 2, "XingHuoChatClient 的密钥需要 (appKey|secretKey) 格式");
+        YudaoAiProperties.XingHuoProperties properties = new YudaoAiProperties.XingHuoProperties()
+                .setAppKey(keys.get(0)).setSecretKey(keys.get(1));
+        return new YudaoAiAutoConfiguration().buildXingHuoChatClient(properties);
     }
     /**
-     * 可参考 {@link OpenAiAutoConfiguration}
+     * 可参考 {@link OpenAiAutoConfiguration} 的 openAiChatModel 方法
      */
     private static OpenAiChatModel buildOpenAiChatModel(String openAiToken, String url) {
-        url = StrUtil.blankToDefault(url, ApiUtils.DEFAULT_BASE_URL);
-        OpenAiApi openAiApi = new OpenAiApi(url, openAiToken);
-        return new OpenAiChatModel(openAiApi);
+        url = StrUtil.blankToDefault(url, OpenAiApiConstants.DEFAULT_BASE_URL);
+        OpenAiApi openAiApi = OpenAiApi.builder().baseUrl(url).apiKey(openAiToken).build();
+        return OpenAiChatModel.builder().openAiApi(openAiApi).build();
     }
+    // TODO @芋艿：手头暂时没密钥，使用建议再测试下
     /**
      * 可参考 {@link AzureOpenAiAutoConfiguration}
      */
@@ -325,27 +310,28 @@ public class AiModelFactoryImpl implements AiModelFactory {
         AzureOpenAiConnectionProperties connectionProperties = new AzureOpenAiConnectionProperties();
         connectionProperties.setApiKey(apiKey);
         connectionProperties.setEndpoint(url);
-        OpenAIClient openAIClient = azureOpenAiAutoConfiguration.openAIClient(connectionProperties);
+        OpenAIClientBuilder openAIClient = azureOpenAiAutoConfiguration.openAIClientBuilder(connectionProperties, null);
         // 获取 AzureOpenAiChatProperties 对象
         AzureOpenAiChatProperties chatProperties = SpringUtil.getBean(AzureOpenAiChatProperties.class);
-        return azureOpenAiAutoConfiguration.azureOpenAiChatModel(openAIClient, chatProperties, null, null);
+        return azureOpenAiAutoConfiguration.azureOpenAiChatModel(openAIClient, chatProperties,
+                null, null, null);
     }
     /**
-     * 可参考 {@link OpenAiAutoConfiguration}
+     * 可参考 {@link OpenAiAutoConfiguration} 的 openAiImageModel 方法
      */
     private OpenAiImageModel buildOpenAiImageModel(String openAiToken, String url) {
-        url = StrUtil.blankToDefault(url, ApiUtils.DEFAULT_BASE_URL);
-        OpenAiImageApi openAiApi = new OpenAiImageApi(url, openAiToken, RestClient.builder());
+        url = StrUtil.blankToDefault(url, OpenAiApiConstants.DEFAULT_BASE_URL);
+        OpenAiImageApi openAiApi = OpenAiImageApi.builder().baseUrl(url).apiKey(openAiToken).build();
         return new OpenAiImageModel(openAiApi);
     }
     /**
-     * 可参考 {@link OllamaAutoConfiguration}
+     * 可参考 {@link OllamaAutoConfiguration} 的 ollamaApi 方法
      */
     private static OllamaChatModel buildOllamaChatModel(String url) {
         OllamaApi ollamaApi = new OllamaApi(url);
-        return new OllamaChatModel(ollamaApi);
+        return OllamaChatModel.builder().ollamaApi(ollamaApi).build();
     }
     private StabilityAiImageModel buildStabilityAiImageModel(String apiKey, String url) {
@@ -356,13 +342,13 @@ public class AiModelFactoryImpl implements AiModelFactory {
     // ========== 各种创建 EmbeddingModel 的方法 ==========
+    // TODO @芋艿：需要测试下
     /**
-     * 可参考 {@link TongYiAutoConfiguration#tongYiTextEmbeddingClient(TextEmbedding, TongYiConnectionProperties)}
+     * 可参考 {@link DashScopeAutoConfiguration} 的 dashscopeEmbeddingModel 方法
      */
     private EmbeddingModel buildTongYiEmbeddingModel(String apiKey) {
-        TongYiConnectionProperties connectionProperties = new TongYiConnectionProperties();
-        connectionProperties.setApiKey(apiKey);
-        return new TongYiAutoConfiguration().tongYiTextEmbeddingClient(SpringUtil.getBean(TextEmbedding.class), connectionProperties);
+        DashScopeApi dashScopeApi = new DashScopeApi(apiKey);
+        return new DashScopeEmbeddingModel(dashScopeApi);
     }
 }
@@ -8,9 +8,10 @@ import lombok.AllArgsConstructor;
 import lombok.Data;
 import lombok.Getter;
 import lombok.extern.slf4j.Slf4j;
-import org.springframework.ai.openai.api.ApiUtils;
+import org.springframework.http.HttpHeaders;
 import org.springframework.http.HttpRequest;
 import org.springframework.http.HttpStatusCode;
+import org.springframework.http.MediaType;
 import org.springframework.web.reactive.function.client.ClientResponse;
 import org.springframework.web.reactive.function.client.WebClient;
 import reactor.core.publisher.Mono;
@@ -18,6 +19,7 @@ import reactor.core.publisher.Mono;
 import java.util.Collection;
 import java.util.List;
 import java.util.Map;
+import java.util.function.Consumer;
 import java.util.function.Function;
 import java.util.function.Predicate;
@@ -50,11 +52,19 @@ public class MidjourneyApi {
     public MidjourneyApi(String baseUrl, String apiKey, String notifyUrl) {
         this.webClient = WebClient.builder()
                 .baseUrl(baseUrl)
-                .defaultHeaders(ApiUtils.getJsonContentHeaders(apiKey))
+                .defaultHeaders(getJsonContentHeaders(apiKey))
                 .build();
         this.notifyUrl = notifyUrl;
     }
+    // TODO @芋艿：这里，看看怎么调整下？？？https://github.com/spring-projects/spring-ai/issues/741
+    public static Consumer<HttpHeaders> getJsonContentHeaders(String apiKey) {
+        return (headers) -> {
+            headers.setBearerAuth(apiKey);
+            headers.setContentType(MediaType.APPLICATION_JSON);
+        };
+    };
+
     /**
      * imagine - 根据提示词提交绘画任务
      *
@@ -2,9 +2,7 @@ package cn.iocoder.yudao.framework.ai.core.util;
 import cn.hutool.core.util.StrUtil;
 import cn.iocoder.yudao.framework.ai.core.enums.AiPlatformEnum;
-import cn.iocoder.yudao.framework.ai.core.model.deepseek.DeepSeekChatOptions;
-import cn.iocoder.yudao.framework.ai.core.model.xinghuo.XingHuoChatOptions;
-import com.alibaba.cloud.ai.tongyi.chat.TongYiChatOptions;
+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;
@@ -21,26 +19,24 @@ import org.springframework.ai.zhipuai.ZhiPuAiChatOptions;
 public class AiUtils {
     public static ChatOptions buildChatOptions(AiPlatformEnum platform, String model, Double temperature, Integer maxTokens) {
-        Float temperatureF = temperature != null ? temperature.floatValue() : null;
         //noinspection EnhancedSwitchMigration
         switch (platform) {
             case TONG_YI:
-                return TongYiChatOptions.builder().withModel(model).withTemperature(temperature).withMaxTokens(maxTokens).build();
+                // TODO @芋艿：tongyi 暂时没 maxTokens 选项
+                return DashScopeChatOptions.builder().withModel(model).withTemperature(temperature).build();
             case YI_YAN:
-                return QianFanChatOptions.builder().withModel(model).withTemperature(temperatureF).withMaxTokens(maxTokens).build();
-            case DEEP_SEEK:
-                return DeepSeekChatOptions.builder().model(model).temperature(temperatureF).maxTokens(maxTokens).build();
+                return QianFanChatOptions.builder().model(model).temperature(temperature).maxTokens(maxTokens).build();
             case ZHI_PU:
-                return ZhiPuAiChatOptions.builder().withModel(model).withTemperature(temperatureF).withMaxTokens(maxTokens).build();
-            case XING_HUO:
-                return XingHuoChatOptions.builder().model(model).temperature(temperatureF).maxTokens(maxTokens).build();
+                return ZhiPuAiChatOptions.builder().model(model).temperature(temperature).maxTokens(maxTokens).build();
             case OPENAI:
-                return OpenAiChatOptions.builder().withModel(model).withTemperature(temperatureF).withMaxTokens(maxTokens).build();
+            case DEEP_SEEK: // 复用 OpenAI 客户端
+            case XING_HUO: // 复用 OpenAI 客户端
+                return OpenAiChatOptions.builder().model(model).temperature(temperature).maxTokens(maxTokens).build();
             case AZURE_OPENAI:
                 // TODO 芋艿：貌似没 model 字段？？？！
-                return AzureOpenAiChatOptions.builder().withDeploymentName(model).withTemperature(temperatureF).withMaxTokens(maxTokens).build();
+                return AzureOpenAiChatOptions.builder().deploymentName(model).temperature(temperature).maxTokens(maxTokens).build();
             case OLLAMA:
-                return OllamaOptions.create().withModel(model).withTemperature(temperatureF).withNumPredict(maxTokens);
+                return OllamaOptions.builder().model(model).temperature(temperature).numPredict(maxTokens).build();
             default:
                 throw new IllegalArgumentException(StrUtil.format("未知平台({})", platform));
         }
@@ -56,8 +52,8 @@ public class AiUtils {
         if (MessageType.SYSTEM.getValue().equals(type)) {
             return new SystemMessage(content);
         }
-        if (MessageType.FUNCTION.getValue().equals(type)) {
-            return new FunctionMessage(content);
+        if (MessageType.TOOL.getValue().equals(type)) {
+            throw new UnsupportedOperationException("暂不支持 tool 消息：" + content);
         }
         throw new IllegalArgumentException(StrUtil.format("未知消息类型({})", type));
     }
-/*
- * Copyright 2023 - 2024 the original author or authors.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * https://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-package org.springframework.ai.autoconfigure.vectorstore.redis;
-
-import org.springframework.ai.embedding.EmbeddingModel;
-import org.springframework.ai.vectorstore.RedisVectorStore;
-import org.springframework.ai.vectorstore.RedisVectorStore.RedisVectorStoreConfig;
-import org.springframework.boot.autoconfigure.AutoConfiguration;
-import org.springframework.boot.autoconfigure.condition.ConditionalOnBean;
-import org.springframework.boot.autoconfigure.condition.ConditionalOnClass;
-import org.springframework.boot.autoconfigure.condition.ConditionalOnMissingBean;
-import org.springframework.boot.autoconfigure.data.redis.RedisAutoConfiguration;
-import org.springframework.boot.context.properties.EnableConfigurationProperties;
-import org.springframework.context.annotation.Bean;
-import org.springframework.data.redis.connection.jedis.JedisConnectionFactory;
-import redis.clients.jedis.JedisPooled;
-
-/**
- * TODO @xin 先拿 spring-ai 最新代码覆盖，1.0.0-M1 跟 redis 自动配置会冲突
- *
- * TODO 这个官方，有说啥时候 fix 哇？
- * TODO 看着是列在1.0.0-M2版本
- *
- * @author Christian Tzolov
- * @author Eddú Meléndez
- */
-@AutoConfiguration(after = RedisAutoConfiguration.class)
-@ConditionalOnClass({JedisPooled.class, JedisConnectionFactory.class, RedisVectorStore.class, EmbeddingModel.class})
-@ConditionalOnBean(JedisConnectionFactory.class)
-@EnableConfigurationProperties(RedisVectorStoreProperties.class)
-public class RedisVectorStoreAutoConfiguration {
-
-    @Bean
-    @ConditionalOnMissingBean
-    public RedisVectorStore vectorStore(EmbeddingModel embeddingModel, RedisVectorStoreProperties properties,
-                                        JedisConnectionFactory jedisConnectionFactory) {
-
-        var config = RedisVectorStoreConfig.builder()
-                .withIndexName(properties.getIndex())
-                .withPrefix(properties.getPrefix())
-                .build();
-
-        return new RedisVectorStore(config, embeddingModel,
-                new JedisPooled(jedisConnectionFactory.getHostName(), jedisConnectionFactory.getPort()),
-                properties.isInitializeSchema());
-    }
-
-}
-/*
- * Copyright 2023 - 2024 the original author or authors.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * https://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-package org.springframework.ai.vectorstore;
-
-import org.slf4j.Logger;
-import org.slf4j.LoggerFactory;
-import org.springframework.ai.document.Document;
-import org.springframework.ai.embedding.EmbeddingModel;
-import org.springframework.ai.vectorstore.filter.FilterExpressionConverter;
-import org.springframework.beans.factory.InitializingBean;
-import org.springframework.util.Assert;
-import org.springframework.util.CollectionUtils;
-import redis.clients.jedis.JedisPooled;
-import redis.clients.jedis.Pipeline;
-import redis.clients.jedis.json.Path2;
-import redis.clients.jedis.search.*;
-import redis.clients.jedis.search.Schema.FieldType;
-import redis.clients.jedis.search.schemafields.*;
-import redis.clients.jedis.search.schemafields.VectorField.VectorAlgorithm;
-
-import java.text.MessageFormat;
-import java.util.*;
-import java.util.function.Function;
-import java.util.function.Predicate;
-import java.util.stream.Collectors;
-
-/**
- * The RedisVectorStore is for managing and querying vector data in a Redis database. It
- * offers functionalities like adding, deleting, and performing similarity searches on
- * documents.
- *
- * The store utilizes RedisJSON and RedisSearch to handle JSON documents and to index and
- * search vector data. It supports various vector algorithms (e.g., FLAT, HSNW) for
- * efficient similarity searches. Additionally, it allows for custom metadata fields in
- * the documents to be stored alongside the vector and content data.
- *
- * This class requires a RedisVectorStoreConfig configuration object for initialization,
- * which includes settings like Redis URI, index name, field names, and vector algorithms.
- * It also requires an EmbeddingModel to convert documents into embeddings before storing
- * them.
- *
- * @author Julien Ruaux
- * @author Christian Tzolov
- * @author Eddú Meléndez
- * @see VectorStore
- * @see RedisVectorStoreConfig
- * @see EmbeddingModel
- */
-public class RedisVectorStore implements VectorStore, InitializingBean {
-
-    public enum Algorithm {
-
-        FLAT, HSNW
-
-    }
-
-    public record MetadataField(String name, FieldType fieldType) {
-
-        public static MetadataField text(String name) {
-            return new MetadataField(name, FieldType.TEXT);
-        }
-
-        public static MetadataField numeric(String name) {
-            return new MetadataField(name, FieldType.NUMERIC);
-        }
-
-        public static MetadataField tag(String name) {
-            return new MetadataField(name, FieldType.TAG);
-        }
-
-    }
-
-    /**
-     * Configuration for the Redis vector store.
-     */
-    public static final class RedisVectorStoreConfig {
-
-        private final String indexName;
-
-        private final String prefix;
-
-        private final String contentFieldName;
-
-        private final String embeddingFieldName;
-
-        private final Algorithm vectorAlgorithm;
-
-        private final List<MetadataField> metadataFields;
-
-        private RedisVectorStoreConfig() {
-            this(builder());
-        }
-
-        private RedisVectorStoreConfig(Builder builder) {
-            this.indexName = builder.indexName;
-            this.prefix = builder.prefix;
-            this.contentFieldName = builder.contentFieldName;
-            this.embeddingFieldName = builder.embeddingFieldName;
-            this.vectorAlgorithm = builder.vectorAlgorithm;
-            this.metadataFields = builder.metadataFields;
-        }
-
-        /**
-         * Start building a new configuration.
-         * @return The entry point for creating a new configuration.
-         */
-        public static Builder builder() {
-
-            return new Builder();
-        }
-
-        /**
-         * {@return the default config}
-         */
-        public static RedisVectorStoreConfig defaultConfig() {
-
-            return builder().build();
-        }
-
-        public static class Builder {
-
-            private String indexName = DEFAULT_INDEX_NAME;
-
-            private String prefix = DEFAULT_PREFIX;
-
-            private String contentFieldName = DEFAULT_CONTENT_FIELD_NAME;
-
-            private String embeddingFieldName = DEFAULT_EMBEDDING_FIELD_NAME;
-
-            private Algorithm vectorAlgorithm = DEFAULT_VECTOR_ALGORITHM;
-
-            private List<MetadataField> metadataFields = new ArrayList<>();
-
-            private Builder() {
-            }
-
-            /**
-             * Configures the Redis index name to use.
-             * @param name the index name to use
-             * @return this builder
-             */
-            public Builder withIndexName(String name) {
-                this.indexName = name;
-                return this;
-            }
-
-            /**
-             * Configures the Redis key prefix to use (default: "embedding:").
-             * @param prefix the prefix to use
-             * @return this builder
-             */
-            public Builder withPrefix(String prefix) {
-                this.prefix = prefix;
-                return this;
-            }
-
-            /**
-             * Configures the Redis content field name to use.
-             * @param name the content field name to use
-             * @return this builder
-             */
-            public Builder withContentFieldName(String name) {
-                this.contentFieldName = name;
-                return this;
-            }
-
-            /**
-             * Configures the Redis embedding field name to use.
-             * @param name the embedding field name to use
-             * @return this builder
-             */
-            public Builder withEmbeddingFieldName(String name) {
-                this.embeddingFieldName = name;
-                return this;
-            }
-
-            /**
-             * Configures the Redis vector algorithmto use.
-             * @param algorithm the vector algorithm to use
-             * @return this builder
-             */
-            public Builder withVectorAlgorithm(Algorithm algorithm) {
-                this.vectorAlgorithm = algorithm;
-                return this;
-            }
-
-            public Builder withMetadataFields(MetadataField... fields) {
-                return withMetadataFields(Arrays.asList(fields));
-            }
-
-            public Builder withMetadataFields(List<MetadataField> fields) {
-                this.metadataFields = fields;
-                return this;
-            }
-
-            /**
-             * {@return the immutable configuration}
-             */
-            public RedisVectorStoreConfig build() {
-
-                return new RedisVectorStoreConfig(this);
-            }
-
-        }
-
-    }
-
-    private final boolean initializeSchema;
-
-    public static final String DEFAULT_INDEX_NAME = "spring-ai-index";
-
-    public static final String DEFAULT_CONTENT_FIELD_NAME = "content";
-
-    public static final String DEFAULT_EMBEDDING_FIELD_NAME = "embedding";
-
-    public static final String DEFAULT_PREFIX = "embedding:";
-
-    public static final Algorithm DEFAULT_VECTOR_ALGORITHM = Algorithm.HSNW;
-
-    private static final String QUERY_FORMAT = "%s=>[KNN %s @%s $%s AS %s]";
-
-    private static final Path2 JSON_SET_PATH = Path2.of("$");
-
-    private static final String JSON_PATH_PREFIX = "$.";
-
-    private static final Logger logger = LoggerFactory.getLogger(RedisVectorStore.class);
-
-    private static final Predicate<Object> RESPONSE_OK = Predicate.isEqual("OK");
-
-    private static final Predicate<Object> RESPONSE_DEL_OK = Predicate.isEqual(1l);
-
-    private static final String VECTOR_TYPE_FLOAT32 = "FLOAT32";
-
-    private static final String EMBEDDING_PARAM_NAME = "BLOB";
-
-    public static final String DISTANCE_FIELD_NAME = "vector_score";
-
-    private static final String DEFAULT_DISTANCE_METRIC = "COSINE";
-
-    private final JedisPooled jedis;
-
-    private final EmbeddingModel embeddingModel;
-
-    private final RedisVectorStoreConfig config;
-
-    private FilterExpressionConverter filterExpressionConverter;
-
-    public RedisVectorStore(RedisVectorStoreConfig config, EmbeddingModel embeddingModel, JedisPooled jedis,
-                            boolean initializeSchema) {
-
-        Assert.notNull(config, "Config must not be null");
-        Assert.notNull(embeddingModel, "Embedding model must not be null");
-        this.initializeSchema = initializeSchema;
-
-        this.jedis = jedis;
-        this.embeddingModel = embeddingModel;
-        this.config = config;
-        this.filterExpressionConverter = new RedisFilterExpressionConverter(this.config.metadataFields);
-    }
-
-    public JedisPooled getJedis() {
-        return this.jedis;
-    }
-
-    @Override
-    public void add(List<Document> documents) {
-        try (Pipeline pipeline = this.jedis.pipelined()) {
-            for (Document document : documents) {
-                var embedding = this.embeddingModel.embed(document);
-                document.setEmbedding(embedding);
-
-                var fields = new HashMap<String, Object>();
-                fields.put(this.config.embeddingFieldName, embedding);
-                fields.put(this.config.contentFieldName, document.getContent());
-                fields.putAll(document.getMetadata());
-                pipeline.jsonSetWithEscape(key(document.getId()), JSON_SET_PATH, fields);
-            }
-            List<Object> responses = pipeline.syncAndReturnAll();
-            Optional<Object> errResponse = responses.stream().filter(Predicate.not(RESPONSE_OK)).findAny();
-            if (errResponse.isPresent()) {
-                String message = MessageFormat.format("Could not add document: {0}", errResponse.get());
-                if (logger.isErrorEnabled()) {
-                    logger.error(message);
-                }
-                throw new RuntimeException(message);
-            }
-        }
-    }
-
-    private String key(String id) {
-        return this.config.prefix + id;
-    }
-
-    @Override
-    public Optional<Boolean> delete(List<String> idList) {
-        try (Pipeline pipeline = this.jedis.pipelined()) {
-            for (String id : idList) {
-                pipeline.jsonDel(key(id));
-            }
-            List<Object> responses = pipeline.syncAndReturnAll();
-            Optional<Object> errResponse = responses.stream().filter(Predicate.not(RESPONSE_DEL_OK)).findAny();
-            if (errResponse.isPresent()) {
-                if (logger.isErrorEnabled()) {
-                    logger.error("Could not delete document: {}", errResponse.get());
-                }
-                return Optional.of(false);
-            }
-            return Optional.of(true);
-        }
-    }
-
-    @Override
-    public List<Document> similaritySearch(SearchRequest request) {
-
-        Assert.isTrue(request.getTopK() > 0, "The number of documents to returned must be greater than zero");
-        Assert.isTrue(request.getSimilarityThreshold() >= 0 && request.getSimilarityThreshold() <= 1,
-                "The similarity score is bounded between 0 and 1; least to most similar respectively.");
-
-        String filter = nativeExpressionFilter(request);
-
-        String queryString = String.format(QUERY_FORMAT, filter, request.getTopK(), this.config.embeddingFieldName,
-                EMBEDDING_PARAM_NAME, DISTANCE_FIELD_NAME);
-
-        List<String> returnFields = new ArrayList<>();
-        this.config.metadataFields.stream().map(MetadataField::name).forEach(returnFields::add);
-        returnFields.add(this.config.embeddingFieldName);
-        returnFields.add(this.config.contentFieldName);
-        returnFields.add(DISTANCE_FIELD_NAME);
-        var embedding = toFloatArray(this.embeddingModel.embed(request.getQuery()));
-        Query query = new Query(queryString).addParam(EMBEDDING_PARAM_NAME, RediSearchUtil.toByteArray(embedding))
-                .returnFields(returnFields.toArray(new String[0]))
-                .setSortBy(DISTANCE_FIELD_NAME, true)
-                .dialect(2);
-
-        SearchResult result = this.jedis.ftSearch(this.config.indexName, query);
-        return result.getDocuments()
-                .stream()
-                .filter(d -> similarityScore(d) >= request.getSimilarityThreshold())
-                .map(this::toDocument)
-                .toList();
-    }
-
-    private Document toDocument(redis.clients.jedis.search.Document doc) {
-        var id = doc.getId().substring(this.config.prefix.length());
-        var content = doc.hasProperty(this.config.contentFieldName) ? doc.getString(this.config.contentFieldName)
-                : null;
-        Map<String, Object> metadata = this.config.metadataFields.stream()
-                .map(MetadataField::name)
-                .filter(doc::hasProperty)
-                .collect(Collectors.toMap(Function.identity(), doc::getString));
-        metadata.put(DISTANCE_FIELD_NAME, 1 - similarityScore(doc));
-        return new Document(id, content, metadata);
-    }
-
-    private float similarityScore(redis.clients.jedis.search.Document doc) {
-        return (2 - Float.parseFloat(doc.getString(DISTANCE_FIELD_NAME))) / 2;
-    }
-
-    private String nativeExpressionFilter(SearchRequest request) {
-        if (request.getFilterExpression() == null) {
-            return "*";
-        }
-        return "(" + this.filterExpressionConverter.convertExpression(request.getFilterExpression()) + ")";
-    }
-
-    @Override
-    public void afterPropertiesSet() {
-
-        if (!this.initializeSchema) {
-            return;
-        }
-
-        // If index already exists don't do anything
-        if (this.jedis.ftList().contains(this.config.indexName)) {
-            return;
-        }
-
-        String response = this.jedis.ftCreate(this.config.indexName,
-                FTCreateParams.createParams().on(IndexDataType.JSON).addPrefix(this.config.prefix), schemaFields());
-        if (!RESPONSE_OK.test(response)) {
-            String message = MessageFormat.format("Could not create index: {0}", response);
-            throw new RuntimeException(message);
-        }
-    }
-
-    private Iterable<SchemaField> schemaFields() {
-        Map<String, Object> vectorAttrs = new HashMap<>();
-        vectorAttrs.put("DIM", this.embeddingModel.dimensions());
-        vectorAttrs.put("DISTANCE_METRIC", DEFAULT_DISTANCE_METRIC);
-        vectorAttrs.put("TYPE", VECTOR_TYPE_FLOAT32);
-        List<SchemaField> fields = new ArrayList<>();
-        fields.add(TextField.of(jsonPath(this.config.contentFieldName)).as(this.config.contentFieldName).weight(1.0));
-        fields.add(VectorField.builder()
-                .fieldName(jsonPath(this.config.embeddingFieldName))
-                .algorithm(vectorAlgorithm())
-                .attributes(vectorAttrs)
-                .as(this.config.embeddingFieldName)
-                .build());
-
-        if (!CollectionUtils.isEmpty(this.config.metadataFields)) {
-            for (MetadataField field : this.config.metadataFields) {
-                fields.add(schemaField(field));
-            }
-        }
-        return fields;
-    }
-
-    private SchemaField schemaField(MetadataField field) {
-        String fieldName = jsonPath(field.name);
-        switch (field.fieldType) {
-            case NUMERIC:
-                return NumericField.of(fieldName).as(field.name);
-            case TAG:
-                return TagField.of(fieldName).as(field.name);
-            case TEXT:
-                return TextField.of(fieldName).as(field.name);
-            default:
-                throw new IllegalArgumentException(
-                        MessageFormat.format("Field {0} has unsupported type {1}", field.name, field.fieldType));
-        }
-    }
-
-    private VectorAlgorithm vectorAlgorithm() {
-        if (config.vectorAlgorithm == Algorithm.HSNW) {
-            return VectorAlgorithm.HNSW;
-        }
-        return VectorAlgorithm.FLAT;
-    }
-
-    private String jsonPath(String field) {
-        return JSON_PATH_PREFIX + field;
-    }
-
-    private static float[] toFloatArray(List<Double> embeddingDouble) {
-        float[] embeddingFloat = new float[embeddingDouble.size()];
-        int i = 0;
-        for (Double d : embeddingDouble) {
-            embeddingFloat[i++] = d.floatValue();
-        }
-        return embeddingFloat;
-    }
-
-}
 \ No newline at end of file
 package cn.iocoder.yudao.framework.ai.chat;
-import com.azure.ai.openai.OpenAIClient;
 import com.azure.ai.openai.OpenAIClientBuilder;
 import com.azure.core.credential.AzureKeyCredential;
 import com.azure.core.util.ClientOptions;
@@ -27,13 +26,13 @@ import static org.springframework.ai.autoconfigure.azure.openai.AzureOpenAiChatP
  */
 public class AzureOpenAIChatModelTests {
-    private final OpenAIClient openAiApi = (new OpenAIClientBuilder())
+    // 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"))
-            .buildClient();
+            .clientOptions((new ClientOptions()).setApplicationId("spring-ai"));
     private final AzureOpenAiChatModel chatModel = new AzureOpenAiChatModel(openAiApi,
-            AzureOpenAiChatOptions.builder().withDeploymentName(DEFAULT_DEPLOYMENT_NAME).build());
+            AzureOpenAiChatOptions.builder().deploymentName(DEFAULT_DEPLOYMENT_NAME).build());
     @Test
     @Disabled
 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.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
@@ -23,41 +9,41 @@ import java.util.List;
  */
 public class LlamaChatModelTests {
-    private final OllamaApi ollamaApi = new OllamaApi(
-            "http://127.0.0.1:11434");
-    private final OllamaChatModel chatModel = new OllamaChatModel(ollamaApi,
-            OllamaOptions.create().withModel(OllamaModel.LLAMA3.getModelName()));
-
-    @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 OllamaApi ollamaApi = new OllamaApi(
+//            "http://127.0.0.1:11434");
+//    private final OllamaChatModel chatModel = new OllamaChatModel(ollamaApi,
+//            OllamaOptions.create().withModel(OllamaModel.LLAMA3.getModelName()));
+//
+//    @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();
+//    }
 }
@@ -26,7 +26,7 @@ public class OpenAIChatModelTests {
             "https://api.holdai.top",
             "sk-dZEPiVaNcT3FHhef51996bAa0bC74806BeAb620dA5Da10Bf");
     private final OpenAiChatModel chatModel = new OpenAiChatModel(openAiApi,
-            OpenAiChatOptions.builder().withModel(OpenAiApi.ChatModel.GPT_4_O).build());
+            OpenAiChatOptions.builder().model(OpenAiApi.ChatModel.GPT_4_O).build());
     @Test
     @Disabled
@@ -25,7 +25,7 @@ public class YiYanChatModelTests {
             "qS8k8dYr2nXunagK4SSU8Xjj",
             "pHGbx51ql2f0hOyabQvSZezahVC3hh3e");
     private final QianFanChatModel chatModel = new QianFanChatModel(qianFanApi,
-            QianFanChatOptions.builder().withModel(QianFanApi.ChatModel.ERNIE_Tiny_8K.getValue()).build()
+            QianFanChatOptions.builder().model(QianFanApi.ChatModel.ERNIE_Tiny_8K.getValue()).build()
     );
     @Test
@@ -24,7 +24,7 @@ public class ZhiPuAiChatModelTests {
     private final ZhiPuAiApi zhiPuAiApi = new ZhiPuAiApi("32f84543e54eee31f8d56b2bd6020573.3vh9idLJZ2ZhxDEs");
     private final ZhiPuAiChatModel chatModel = new ZhiPuAiChatModel(zhiPuAiApi,
-            ZhiPuAiChatOptions.builder().withModel(ZhiPuAiApi.ChatModel.GLM_4.getModelName()).build());
+            ZhiPuAiChatOptions.builder().model(ZhiPuAiApi.ChatModel.GLM_4.getName()).build());
     @Test
     @Disabled
@@ -25,9 +25,9 @@ public class QianFanImageTests {
         // 准备参数
         // 只支持 1024x1024、768x768、768x1024、1024x768、576x1024、1024x576
         QianFanImageOptions imageOptions = QianFanImageOptions.builder()
-                .withModel(QianFanImageApi.ImageModel.Stable_Diffusion_XL.getValue())
-                .withWidth(1024).withHeight(1024)
-                .withN(1)
+                .model(QianFanImageApi.ImageModel.Stable_Diffusion_XL.getValue())
+                .width(1024).height(1024)
+                .N(1)
                 .build();
         ImagePrompt prompt = new ImagePrompt("good", imageOptions);
 package cn.iocoder.yudao.framework.ai.image;
-import com.alibaba.cloud.ai.tongyi.image.TongYiImagesModel;
+import com.alibaba.cloud.ai.dashscope.api.DashScopeImageApi;
+import com.alibaba.cloud.ai.dashscope.image.DashScopeImageModel;
+import com.alibaba.cloud.ai.dashscope.image.DashScopeImageOptions;
 import com.alibaba.dashscope.aigc.imagesynthesis.ImageSynthesis;
-import com.alibaba.dashscope.utils.Constants;
 import org.junit.jupiter.api.Disabled;
 import org.junit.jupiter.api.Test;
 import org.springframework.ai.image.ImageOptions;
 import org.springframework.ai.image.ImagePrompt;
 import org.springframework.ai.image.ImageResponse;
-import org.springframework.ai.openai.OpenAiImageOptions;
 /**
- * {@link com.alibaba.cloud.ai.tongyi.image.TongYiImagesModel} 集成测试类
+ * {@link DashScopeImageModel} 集成测试类
  *
  * @author fansili
  */
 public class TongYiImagesModelTest {
-    private final ImageSynthesis imageApi = new ImageSynthesis();
-    private final TongYiImagesModel imageModel = new TongYiImagesModel(imageApi);
-
-    static {
-        Constants.apiKey = "sk-Zsd81gZYg7";
-    }
+    private final DashScopeImageModel imageModel = new DashScopeImageModel(
+            new DashScopeImageApi("sk-7d903764249848cfa912733146da12d1"));
     @Test
     @Disabled
     public void imageCallTest() {
         // 准备参数
-        ImageOptions options = OpenAiImageOptions.builder()
+        ImageOptions options = DashScopeImageOptions.builder()
                 .withModel(ImageSynthesis.Models.WANX_V1)
                 .withHeight(256).withWidth(256)
                 .build();
@@ -22,7 +22,7 @@ public class ZhiPuAiImageModelTests {
     public void testCall() {
         // 准备参数
         ZhiPuAiImageOptions imageOptions = ZhiPuAiImageOptions.builder()
-                .withModel(ZhiPuAiImageApi.ImageModel.CogView_3.getValue())
+                .model(ZhiPuAiImageApi.ImageModel.CogView_3.getValue())
                 .build();
         ImagePrompt prompt = new ImagePrompt("万里长城", imageOptions);