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feat：【AI 大模型】依赖 spring ai 升级到 1.0.0

pull/198/head
YunaiV 2025-07-14 23:35:56 +08:00
parent 7a8e089a42
commit ef874191a6
30 changed files with 387 additions and 415 deletions
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51
yudao-module-ai/yudao-module-ai-server/pom.xml
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@ -18,7 +18,8 @@
国外：OpenAI、Ollama、Midjourney、StableDiffusion、Suno 国外：OpenAI、Ollama、Midjourney、StableDiffusion、Suno
</description> </description>
<properties> <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> <tinyflow.version>1.0.2</tinyflow.version>
</properties> </properties>
@ -110,65 +111,73 @@
<!-- Spring AI Model 模型接入 --> <!-- Spring AI Model 模型接入 -->
<dependency> <dependency>
<groupId>org.springframework.ai</groupId> <groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-openai-spring-boot-starter</artifactId> <artifactId>spring-ai-starter-model-openai</artifactId>
<version>${spring-ai.version}</version> <version>${spring-ai.version}</version>
</dependency> </dependency>
<dependency> <dependency>
<groupId>org.springframework.ai</groupId> <groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-azure-openai-spring-boot-starter</artifactId> <artifactId>spring-ai-starter-model-azure-openai</artifactId>
<version>${spring-ai.version}</version> <version>${spring-ai.version}</version>
</dependency> </dependency>
<dependency> <dependency>
<groupId>org.springframework.ai</groupId> <groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-ollama-spring-boot-starter</artifactId> <artifactId>spring-ai-starter-model-deepseek</artifactId>
<version>${spring-ai.version}</version> <version>${spring-ai.version}</version>
</dependency> </dependency>
<dependency> <dependency>
<groupId>org.springframework.ai</groupId> <groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-stability-ai-spring-boot-starter</artifactId> <artifactId>spring-ai-starter-model-ollama</artifactId>
<version>${spring-ai.version}</version> <version>${spring-ai.version}</version>
</dependency> </dependency>
<dependency> <dependency>
<!-- 通义千问 -->
<groupId>com.alibaba.cloud.ai</groupId>
<artifactId>spring-ai-alibaba-starter</artifactId>
<version>${spring-ai.version}.1</version>
</dependency>
<dependency>
<!-- 文心一言 -->
<groupId>org.springframework.ai</groupId> <groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-qianfan-spring-boot-starter</artifactId> <artifactId>spring-ai-starter-model-stability-ai</artifactId>
<version>${spring-ai.version}</version> <version>${spring-ai.version}</version>
</dependency> </dependency>
<dependency> <dependency>
<!-- 智谱 GLM --> <!-- 智谱 GLM -->
<groupId>org.springframework.ai</groupId> <groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-zhipuai-spring-boot-starter</artifactId> <artifactId>spring-ai-starter-model-zhipuai</artifactId>
<version>${spring-ai.version}</version> <version>${spring-ai.version}</version>
</dependency> </dependency>
<dependency> <dependency>
<groupId>org.springframework.ai</groupId> <groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-minimax-spring-boot-starter</artifactId> <artifactId>spring-ai-starter-model-minimax</artifactId>
<version>${spring-ai.version}</version> <version>${spring-ai.version}</version>
</dependency> </dependency>
<dependency> <dependency>
<groupId>org.springframework.ai</groupId> <!-- 通义千问 -->
<artifactId>spring-ai-moonshot-spring-boot-starter</artifactId> <groupId>com.alibaba.cloud.ai</groupId>
<version>${spring-ai.version}</version> <artifactId>spring-ai-alibaba-starter-dashscope</artifactId>
<version>${alibaba-ai.version}</version>
</dependency>
<dependency>
<!-- 文心一言 -->
<groupId>org.springaicommunity</groupId>
<artifactId>qianfan-spring-boot-starter</artifactId>
<version>1.0.0</version>
</dependency>
<dependency>
<!-- 月之暗灭 -->
<groupId>org.springaicommunity</groupId>
<artifactId>moonshot-spring-boot-starter</artifactId>
<version>1.0.0</version>
</dependency> </dependency>
<!-- 向量存储：https://db-engines.com/en/ranking/vector+dbms --> <!-- 向量存储：https://db-engines.com/en/ranking/vector+dbms -->
<dependency> <dependency>
<!-- Qdrant：https://qdrant.tech/ --> <!-- Qdrant：https://qdrant.tech/ -->
<groupId>org.springframework.ai</groupId> <groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-qdrant-store</artifactId> <artifactId>spring-ai-starter-vector-store-qdrant</artifactId>
<version>${spring-ai.version}</version> <version>${spring-ai.version}</version>
</dependency> </dependency>
<dependency> <dependency>
<!-- Redis：https://redis.io/docs/latest/develop/get-started/vector-database/ --> <!-- Redis：https://redis.io/docs/latest/develop/get-started/vector-database/ -->
<groupId>org.springframework.ai</groupId> <groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-redis-store</artifactId> <artifactId>spring-ai-starter-vector-store-redis</artifactId>
<version>${spring-ai.version}</version> <version>${spring-ai.version}</version>
</dependency> </dependency>
<dependency> <dependency>
@ -179,7 +188,7 @@
<dependency> <dependency>
<!-- Milvus：https://milvus.io/ --> <!-- Milvus：https://milvus.io/ -->
<groupId>org.springframework.ai</groupId> <groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-milvus-store</artifactId> <artifactId>spring-ai-starter-vector-store-milvus</artifactId>
<version>${spring-ai.version}</version> <version>${spring-ai.version}</version>
<exclusions> <exclusions>
<!-- 解决和 logback 的日志冲突 --> <!-- 解决和 logback 的日志冲突 -->

4
yudao-module-ai/yudao-module-ai-server/src/main/java/cn/iocoder/yudao/module/ai/AiServerApplication.java
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@ -13,8 +13,8 @@ import org.springframework.boot.autoconfigure.SpringBootApplication;
* @author 芋道源码 * @author 芋道源码
*/ */
@SpringBootApplication(exclude = { @SpringBootApplication(exclude = {
org.springframework.ai.autoconfigure.vectorstore.qdrant.QdrantVectorStoreAutoConfiguration.class, org.springframework.ai.vectorstore.qdrant.autoconfigure.QdrantVectorStoreAutoConfiguration.class,
org.springframework.ai.autoconfigure.vectorstore.milvus.MilvusVectorStoreAutoConfiguration.class, org.springframework.ai.vectorstore.milvus.autoconfigure.MilvusVectorStoreAutoConfiguration.class,
}) // 解决 application-${profile}.yaml 配置文件下，通过 spring.autoconfigure.exclude 无法排除的问题 }) // 解决 application-${profile}.yaml 配置文件下，通过 spring.autoconfigure.exclude 无法排除的问题
public class AiServerApplication { public class AiServerApplication {

36
yudao-module-ai/yudao-module-ai-server/src/main/java/cn/iocoder/yudao/module/ai/framework/ai/config/AiAutoConfiguration.java
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@ -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.AiModelFactory;
import cn.iocoder.yudao.module.ai.framework.ai.core.AiModelFactoryImpl; 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.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.doubao.DouBaoChatModel;
import cn.iocoder.yudao.module.ai.framework.ai.core.model.hunyuan.HunYuanChatModel; 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; 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.suno.api.SunoApi;
import cn.iocoder.yudao.module.ai.framework.ai.core.model.xinghuo.XingHuoChatModel; import cn.iocoder.yudao.module.ai.framework.ai.core.model.xinghuo.XingHuoChatModel;
import lombok.extern.slf4j.Slf4j; 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.BatchingStrategy;
import org.springframework.ai.embedding.TokenCountBatchingStrategy; import org.springframework.ai.embedding.TokenCountBatchingStrategy;
import org.springframework.ai.model.tool.ToolCallingManager; 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.openai.api.OpenAiApi;
import org.springframework.ai.tokenizer.JTokkitTokenCountEstimator; import org.springframework.ai.tokenizer.JTokkitTokenCountEstimator;
import org.springframework.ai.tokenizer.TokenCountEstimator; 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.autoconfigure.condition.ConditionalOnProperty;
import org.springframework.boot.context.properties.EnableConfigurationProperties; import org.springframework.boot.context.properties.EnableConfigurationProperties;
import org.springframework.context.annotation.Bean; import org.springframework.context.annotation.Bean;
@ -52,33 +51,6 @@ public class AiAutoConfiguration {
// ========== 各种 AI Client 创建 ========== // ========== 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 @Bean
@ConditionalOnProperty(value = "yudao.ai.doubao.enable", havingValue = "true") @ConditionalOnProperty(value = "yudao.ai.doubao.enable", havingValue = "true")
public DouBaoChatModel douBaoChatClient(YudaoAiProperties yudaoAiProperties) { public DouBaoChatModel douBaoChatClient(YudaoAiProperties yudaoAiProperties) {

19
yudao-module-ai/yudao-module-ai-server/src/main/java/cn/iocoder/yudao/module/ai/framework/ai/config/YudaoAiProperties.java
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@ -13,12 +13,6 @@ import org.springframework.boot.context.properties.ConfigurationProperties;
@Data @Data
public class YudaoAiProperties { public class YudaoAiProperties {
/**
* DeepSeek
*/
@SuppressWarnings("SpellCheckingInspection")
private DeepSeekProperties deepseek;
/** /**
* 字节豆包 * 字节豆包
*/ */
@ -60,19 +54,6 @@ public class YudaoAiProperties {
@SuppressWarnings("SpellCheckingInspection") @SuppressWarnings("SpellCheckingInspection")
private SunoProperties suno; 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 @Data
public static class DouBaoProperties { public static class DouBaoProperties {

234
yudao-module-ai/yudao-module-ai-server/src/main/java/cn/iocoder/yudao/module/ai/framework/ai/core/AiModelFactoryImpl.java
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@ -8,11 +8,11 @@ import cn.hutool.core.util.ArrayUtil;
import cn.hutool.core.util.RuntimeUtil; import cn.hutool.core.util.RuntimeUtil;
import cn.hutool.core.util.StrUtil; import cn.hutool.core.util.StrUtil;
import cn.hutool.extra.spring.SpringUtil; 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.AiAutoConfiguration;
import cn.iocoder.yudao.module.ai.framework.ai.config.YudaoAiProperties; 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.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.doubao.DouBaoChatModel;
import cn.iocoder.yudao.module.ai.framework.ai.core.model.hunyuan.HunYuanChatModel; 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; 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.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.suno.api.SunoApi;
import cn.iocoder.yudao.module.ai.framework.ai.core.model.xinghuo.XingHuoChatModel; 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.DashScopeChatAutoConfiguration;
import com.alibaba.cloud.ai.autoconfigure.dashscope.DashScopeAutoConfiguration; 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.DashScopeApi;
import com.alibaba.cloud.ai.dashscope.api.DashScopeImageApi; import com.alibaba.cloud.ai.dashscope.api.DashScopeImageApi;
import com.alibaba.cloud.ai.dashscope.chat.DashScopeChatModel; 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.embedding.DashScopeEmbeddingOptions;
import com.alibaba.cloud.ai.dashscope.image.DashScopeImageModel; import com.alibaba.cloud.ai.dashscope.image.DashScopeImageModel;
import com.azure.ai.openai.OpenAIClientBuilder; import com.azure.ai.openai.OpenAIClientBuilder;
import com.azure.core.credential.KeyCredential;
import io.micrometer.observation.ObservationRegistry; import io.micrometer.observation.ObservationRegistry;
import io.milvus.client.MilvusServiceClient; import io.milvus.client.MilvusServiceClient;
import io.qdrant.client.QdrantClient; import io.qdrant.client.QdrantClient;
import io.qdrant.client.QdrantGrpcClient; import io.qdrant.client.QdrantGrpcClient;
import lombok.SneakyThrows; import lombok.SneakyThrows;
import org.springframework.ai.autoconfigure.azure.openai.AzureOpenAiAutoConfiguration; import org.springaicommunity.moonshot.MoonshotChatModel;
import org.springframework.ai.autoconfigure.azure.openai.AzureOpenAiChatProperties; import org.springaicommunity.moonshot.MoonshotChatOptions;
import org.springframework.ai.autoconfigure.azure.openai.AzureOpenAiConnectionProperties; import org.springaicommunity.moonshot.api.MoonshotApi;
import org.springframework.ai.autoconfigure.azure.openai.AzureOpenAiEmbeddingProperties; import org.springaicommunity.moonshot.autoconfigure.MoonshotChatAutoConfiguration;
import org.springframework.ai.autoconfigure.minimax.MiniMaxAutoConfiguration; import org.springaicommunity.qianfan.QianFanChatModel;
import org.springframework.ai.autoconfigure.moonshot.MoonshotAutoConfiguration; import org.springaicommunity.qianfan.QianFanEmbeddingModel;
import org.springframework.ai.autoconfigure.ollama.OllamaAutoConfiguration; import org.springaicommunity.qianfan.QianFanEmbeddingOptions;
import org.springframework.ai.autoconfigure.openai.OpenAiAutoConfiguration; import org.springaicommunity.qianfan.QianFanImageModel;
import org.springframework.ai.autoconfigure.qianfan.QianFanAutoConfiguration; import org.springaicommunity.qianfan.api.QianFanApi;
import org.springframework.ai.autoconfigure.stabilityai.StabilityAiImageAutoConfiguration; import org.springaicommunity.qianfan.api.QianFanImageApi;
import org.springframework.ai.autoconfigure.vectorstore.milvus.MilvusServiceClientConnectionDetails; import org.springaicommunity.qianfan.autoconfigure.QianFanChatAutoConfiguration;
import org.springframework.ai.autoconfigure.vectorstore.milvus.MilvusServiceClientProperties; import org.springaicommunity.qianfan.autoconfigure.QianFanEmbeddingAutoConfiguration;
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.springframework.ai.azure.openai.AzureOpenAiChatModel; import org.springframework.ai.azure.openai.AzureOpenAiChatModel;
import org.springframework.ai.azure.openai.AzureOpenAiEmbeddingModel; import org.springframework.ai.azure.openai.AzureOpenAiEmbeddingModel;
import org.springframework.ai.chat.model.ChatModel; 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.document.MetadataMode;
import org.springframework.ai.embedding.BatchingStrategy; import org.springframework.ai.embedding.BatchingStrategy;
import org.springframework.ai.embedding.EmbeddingModel; import org.springframework.ai.embedding.EmbeddingModel;
import org.springframework.ai.embedding.observation.EmbeddingModelObservationConvention;
import org.springframework.ai.image.ImageModel; import org.springframework.ai.image.ImageModel;
import org.springframework.ai.minimax.MiniMaxChatModel; import org.springframework.ai.minimax.MiniMaxChatModel;
import org.springframework.ai.minimax.MiniMaxChatOptions; import org.springframework.ai.minimax.MiniMaxChatOptions;
import org.springframework.ai.minimax.MiniMaxEmbeddingModel; import org.springframework.ai.minimax.MiniMaxEmbeddingModel;
import org.springframework.ai.minimax.MiniMaxEmbeddingOptions; import org.springframework.ai.minimax.MiniMaxEmbeddingOptions;
import org.springframework.ai.minimax.api.MiniMaxApi; 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.model.tool.ToolCallingManager;
import org.springframework.ai.moonshot.MoonshotChatModel; import org.springframework.ai.model.zhipuai.autoconfigure.ZhiPuAiChatAutoConfiguration;
import org.springframework.ai.moonshot.MoonshotChatOptions; import org.springframework.ai.model.zhipuai.autoconfigure.ZhiPuAiEmbeddingAutoConfiguration;
import org.springframework.ai.moonshot.api.MoonshotApi; import org.springframework.ai.model.zhipuai.autoconfigure.ZhiPuAiImageAutoConfiguration;
import org.springframework.ai.ollama.OllamaChatModel; import org.springframework.ai.ollama.OllamaChatModel;
import org.springframework.ai.ollama.OllamaEmbeddingModel; import org.springframework.ai.ollama.OllamaEmbeddingModel;
import org.springframework.ai.ollama.api.OllamaApi; 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.OpenAiApi;
import org.springframework.ai.openai.api.OpenAiImageApi; import org.springframework.ai.openai.api.OpenAiImageApi;
import org.springframework.ai.openai.api.common.OpenAiApiConstants; 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.StabilityAiImageModel;
import org.springframework.ai.stabilityai.api.StabilityAiApi; import org.springframework.ai.stabilityai.api.StabilityAiApi;
import org.springframework.ai.vectorstore.SimpleVectorStore; import org.springframework.ai.vectorstore.SimpleVectorStore;
import org.springframework.ai.vectorstore.VectorStore; import org.springframework.ai.vectorstore.VectorStore;
import org.springframework.ai.vectorstore.milvus.MilvusVectorStore; 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.DefaultVectorStoreObservationConvention;
import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention; import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
import org.springframework.ai.vectorstore.qdrant.QdrantVectorStore; 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.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.*;
import org.springframework.ai.zhipuai.api.ZhiPuAiApi; import org.springframework.ai.zhipuai.api.ZhiPuAiApi;
import org.springframework.ai.zhipuai.api.ZhiPuAiImageApi; import org.springframework.ai.zhipuai.api.ZhiPuAiImageApi;
@ -190,7 +201,7 @@ public class AiModelFactoryImpl implements AiModelFactory {
case XING_HUO: case XING_HUO:
return SpringUtil.getBean(XingHuoChatModel.class); return SpringUtil.getBean(XingHuoChatModel.class);
case BAI_CHUAN: case BAI_CHUAN:
return SpringUtil.getBean(AzureOpenAiChatModel.class); return SpringUtil.getBean(BaiChuanChatModel.class);
case OPENAI: case OPENAI:
return SpringUtil.getBean(OpenAiChatModel.class); return SpringUtil.getBean(OpenAiChatModel.class);
case AZURE_OPENAI: case AZURE_OPENAI:
@ -319,27 +330,34 @@ public class AiModelFactoryImpl implements AiModelFactory {
// ========== 各种创建 spring-ai 客户端的方法 ========== // ========== 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) { 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) DashScopeChatOptions options = DashScopeChatOptions.builder().withModel(DashScopeApi.DEFAULT_CHAT_MODEL)
.withTemperature(0.7).build(); .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) { private static DashScopeImageModel buildTongYiImagesModel(String key) {
DashScopeImageApi dashScopeImageApi = new DashScopeImageApi(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) { 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, '|'); List<String> keys = StrUtil.split(key, '|');
Assert.equals(keys.size(), 2, "YiYanChatClient 的密钥需要 (appKey|secretKey) 格式"); Assert.equals(keys.size(), 2, "YiYanChatClient 的密钥需要 (appKey|secretKey) 格式");
String appKey = keys.get(0); 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) { 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, '|'); List<String> keys = StrUtil.split(key, '|');
Assert.equals(keys.size(), 2, "YiYanChatClient 的密钥需要 (appKey|secretKey) 格式"); Assert.equals(keys.size(), 2, "YiYanChatClient 的密钥需要 (appKey|secretKey) 格式");
String appKey = keys.get(0); 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) { private static DeepSeekChatModel buildDeepSeekChatModel(String apiKey) {
YudaoAiProperties.DeepSeekProperties properties = new YudaoAiProperties.DeepSeekProperties() DeepSeekApi deepSeekApi = DeepSeekApi.builder().apiKey(apiKey).build();
.setApiKey(apiKey); DeepSeekChatOptions options = DeepSeekChatOptions.builder().model(DeepSeekApi.DEFAULT_CHAT_MODEL)
return new AiAutoConfiguration().buildDeepSeekChatModel(properties); .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) { private ZhiPuAiChatModel buildZhiPuChatModel(String apiKey, String url) {
ZhiPuAiApi zhiPuAiApi = StrUtil.isEmpty(url) ? new ZhiPuAiApi(apiKey) ZhiPuAiApi zhiPuAiApi = StrUtil.isEmpty(url) ? new ZhiPuAiApi(apiKey)
: new ZhiPuAiApi(url, apiKey); : new ZhiPuAiApi(url, apiKey);
ZhiPuAiChatOptions options = ZhiPuAiChatOptions.builder().model(ZhiPuAiApi.DEFAULT_CHAT_MODEL).temperature(0.7).build(); 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) { private ZhiPuAiImageModel buildZhiPuAiImageModel(String apiKey, String url) {
ZhiPuAiImageApi zhiPuAiApi = StrUtil.isEmpty(url) ? new ZhiPuAiImageApi(apiKey) 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) { private MiniMaxChatModel buildMiniMaxChatModel(String apiKey, String url) {
MiniMaxApi miniMaxApi = StrUtil.isEmpty(url) ? new MiniMaxApi(apiKey) MiniMaxApi miniMaxApi = StrUtil.isEmpty(url) ? new MiniMaxApi(apiKey)
: new MiniMaxApi(url, apiKey); : new MiniMaxApi(url, apiKey);
MiniMaxChatOptions options = MiniMaxChatOptions.builder().model(MiniMaxApi.DEFAULT_CHAT_MODEL).temperature(0.7).build(); 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) { private MoonshotChatModel buildMoonshotChatModel(String apiKey, String url) {
MoonshotApi moonshotApi = StrUtil.isEmpty(url)? new MoonshotApi(apiKey) MoonshotApi.Builder moonshotApiBuilder = MoonshotApi.builder()
: new MoonshotApi(url, apiKey); .apiKey(apiKey);
if (StrUtil.isNotEmpty(url)) {
moonshotApiBuilder.baseUrl(url);
}
MoonshotChatOptions options = MoonshotChatOptions.builder().model(MoonshotApi.DEFAULT_CHAT_MODEL).build(); 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) { private static OpenAiChatModel buildOpenAiChatModel(String openAiToken, String url) {
url = StrUtil.blankToDefault(url, OpenAiApiConstants.DEFAULT_BASE_URL); url = StrUtil.blankToDefault(url, OpenAiApiConstants.DEFAULT_BASE_URL);
OpenAiApi openAiApi = OpenAiApi.builder().baseUrl(url).apiKey(openAiToken).build(); 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) { private static AzureOpenAiChatModel buildAzureOpenAiChatModel(String apiKey, String url) {
AzureOpenAiAutoConfiguration azureOpenAiAutoConfiguration = new AzureOpenAiAutoConfiguration(); // TODO @芋艿：使用前，请测试，暂时没密钥！！！
// 创建 OpenAIClient 对象 OpenAIClientBuilder openAIClientBuilder = new OpenAIClientBuilder()
AzureOpenAiConnectionProperties connectionProperties = new AzureOpenAiConnectionProperties(); .endpoint(url).credential(new KeyCredential(apiKey));
connectionProperties.setApiKey(apiKey); return AzureOpenAiChatModel.builder()
connectionProperties.setEndpoint(url); .openAIClientBuilder(openAIClientBuilder)
OpenAIClientBuilder openAIClient = azureOpenAiAutoConfiguration.openAIClientBuilder(connectionProperties, null); .toolCallingManager(getToolCallingManager())
// 获取 AzureOpenAiChatProperties 对象 .build();
AzureOpenAiChatProperties chatProperties = SpringUtil.getBean(AzureOpenAiChatProperties.class);
return azureOpenAiAutoConfiguration.azureOpenAiChatModel(openAIClient, chatProperties,
getToolCallingManager(), null, null);
} }
/** /**
* 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) { private OpenAiImageModel buildOpenAiImageModel(String openAiToken, String url) {
url = StrUtil.blankToDefault(url, OpenAiApiConstants.DEFAULT_BASE_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) { private static OllamaChatModel buildOllamaChatModel(String url) {
OllamaApi ollamaApi = new OllamaApi(url); OllamaApi ollamaApi = OllamaApi.builder().baseUrl(url).build();
return OllamaChatModel.builder().ollamaApi(ollamaApi).toolCallingManager(getToolCallingManager()).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 ========== // ========== 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) { 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(); DashScopeEmbeddingOptions dashScopeEmbeddingOptions = DashScopeEmbeddingOptions.builder().withModel(model).build();
return new DashScopeEmbeddingModel(dashScopeApi, MetadataMode.EMBED, dashScopeEmbeddingOptions); 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) { private ZhiPuAiEmbeddingModel buildZhiPuEmbeddingModel(String apiKey, String url, String model) {
ZhiPuAiApi zhiPuAiApi = StrUtil.isEmpty(url) ? new ZhiPuAiApi(apiKey) 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) { private EmbeddingModel buildMiniMaxEmbeddingModel(String apiKey, String url, String model) {
MiniMaxApi miniMaxApi = StrUtil.isEmpty(url)? new MiniMaxApi(apiKey) 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) { private QianFanEmbeddingModel buildYiYanEmbeddingModel(String key, String model) {
List<String> keys = StrUtil.split(key, '|'); List<String> keys = StrUtil.split(key, '|');
@ -561,13 +595,16 @@ public class AiModelFactoryImpl implements AiModelFactory {
} }
private OllamaEmbeddingModel buildOllamaEmbeddingModel(String url, String model) { 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(); 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) { private OpenAiEmbeddingModel buildOpenAiEmbeddingModel(String openAiToken, String url, String model) {
url = StrUtil.blankToDefault(url, OpenAiApiConstants.DEFAULT_BASE_URL); url = StrUtil.blankToDefault(url, OpenAiApiConstants.DEFAULT_BASE_URL);
@ -576,21 +613,19 @@ public class AiModelFactoryImpl implements AiModelFactory {
return new OpenAiEmbeddingModel(openAiApi, MetadataMode.EMBED, openAiEmbeddingProperties); 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) { private AzureOpenAiEmbeddingModel buildAzureOpenAiEmbeddingModel(String apiKey, String url, String model) {
AzureOpenAiAutoConfiguration azureOpenAiAutoConfiguration = new AzureOpenAiAutoConfiguration(); // TODO @芋艿：手头暂时没密钥，使用建议再测试下
// 创建 OpenAIClient 对象 AzureOpenAiEmbeddingAutoConfiguration azureOpenAiAutoConfiguration = new AzureOpenAiEmbeddingAutoConfiguration();
AzureOpenAiConnectionProperties connectionProperties = new AzureOpenAiConnectionProperties(); // 创建 OpenAIClientBuilder 对象
connectionProperties.setApiKey(apiKey); OpenAIClientBuilder openAIClientBuilder = new OpenAIClientBuilder()
connectionProperties.setEndpoint(url); .endpoint(url).credential(new KeyCredential(apiKey));
OpenAIClientBuilder openAIClient = azureOpenAiAutoConfiguration.openAIClientBuilder(connectionProperties, null);
// 获取 AzureOpenAiChatProperties 对象 // 获取 AzureOpenAiChatProperties 对象
AzureOpenAiEmbeddingProperties embeddingProperties = SpringUtil.getBean(AzureOpenAiEmbeddingProperties.class); AzureOpenAiEmbeddingProperties embeddingProperties = SpringUtil.getBean(AzureOpenAiEmbeddingProperties.class);
return azureOpenAiAutoConfiguration.azureOpenAiEmbeddingModel(openAIClient, embeddingProperties, return azureOpenAiAutoConfiguration.azureOpenAiEmbeddingModel(openAIClientBuilder, embeddingProperties,
null, null); getObservationRegistry(), getEmbeddingModelObservationConvention());
} }
// ========== 各种创建 VectorStore 的方法 ========== // ========== 各种创建 VectorStore 的方法 ==========
@ -655,12 +690,12 @@ public class AiModelFactoryImpl implements AiModelFactory {
Map<String, Class<?>> metadataFields) { Map<String, Class<?>> metadataFields) {
// 创建 JedisPooled 对象 // 创建 JedisPooled 对象
RedisProperties redisProperties = SpringUtils.getBean(RedisProperties.class); 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 // 创建 RedisVectorStoreProperties 对象
RedisVectorStoreAutoConfiguration configuration = new RedisVectorStoreAutoConfiguration();
RedisVectorStoreProperties properties = SpringUtil.getBean(RedisVectorStoreProperties.class); RedisVectorStoreProperties properties = SpringUtil.getBean(RedisVectorStoreProperties.class);
RedisVectorStore redisVectorStore = RedisVectorStore.builder(jedisPooled, embeddingModel) RedisVectorStore redisVectorStore = RedisVectorStore.builder(jedisPooled, embeddingModel)
.indexName(properties.getIndex()).prefix(properties.getPrefix()) .indexName(properties.getIndexName()).prefix(properties.getPrefix())
.initializeSchema(properties.isInitializeSchema()) .initializeSchema(properties.isInitializeSchema())
.metadataFields(convertList(metadataFields.entrySet(), entry -> { .metadataFields(convertList(metadataFields.entrySet(), entry -> {
String fieldName = entry.getKey(); String fieldName = entry.getKey();
@ -730,10 +765,12 @@ public class AiModelFactoryImpl implements AiModelFactory {
private static ObjectProvider<VectorStoreObservationConvention> getCustomObservationConvention() { private static ObjectProvider<VectorStoreObservationConvention> getCustomObservationConvention() {
return new ObjectProvider<>() { return new ObjectProvider<>() {
@Override @Override
public VectorStoreObservationConvention getObject() throws BeansException { public VectorStoreObservationConvention getObject() throws BeansException {
return new DefaultVectorStoreObservationConvention(); return new DefaultVectorStoreObservationConvention();
} }
}; };
} }
@ -745,8 +782,15 @@ public class AiModelFactoryImpl implements AiModelFactory {
return SpringUtil.getBean(ToolCallingManager.class); return SpringUtil.getBean(ToolCallingManager.class);
} }
private static FunctionCallbackResolver getFunctionCallbackResolver() { private static ObjectProvider<EmbeddingModelObservationConvention> getEmbeddingModelObservationConvention() {
return SpringUtil.getBean(FunctionCallbackResolver.class); return new ObjectProvider<>() {
@Override
public EmbeddingModelObservationConvention getObject() throws BeansException {
return SpringUtil.getBean(EmbeddingModelObservationConvention.class);
}
};
} }
} }

45
yudao-module-ai/yudao-module-ai-server/src/main/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/deepseek/DeepSeekChatModel.java
View File

@ -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();
}
}

2
yudao-module-ai/yudao-module-ai-server/src/main/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/siliconflow/SiliconFlowImageModel.java
View File

@ -89,7 +89,7 @@ public class SiliconFlowImageModel implements ImageModel {
var observationContext = ImageModelObservationContext.builder() var observationContext = ImageModelObservationContext.builder()
.imagePrompt(imagePrompt) .imagePrompt(imagePrompt)
.provider(SiliconFlowApiConstants.PROVIDER_NAME) .provider(SiliconFlowApiConstants.PROVIDER_NAME)
.requestOptions(imagePrompt.getOptions()) .imagePrompt(imagePrompt)
.build(); .build();
return ImageModelObservationDocumentation.IMAGE_MODEL_OPERATION return ImageModelObservationDocumentation.IMAGE_MODEL_OPERATION

10
yudao-module-ai/yudao-module-ai-server/src/main/java/cn/iocoder/yudao/module/ai/service/image/AiImageServiceImpl.java
View File

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

31
yudao-module-ai/yudao-module-ai-server/src/main/java/cn/iocoder/yudao/module/ai/service/model/tool/UserProfileQueryToolFunction.java
View File

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

14
yudao-module-ai/yudao-module-ai-server/src/main/java/cn/iocoder/yudao/module/ai/util/AiUtils.java
View File

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

4
yudao-module-ai/yudao-module-ai-server/src/main/resources/application-dev.yaml
View File

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

4
yudao-module-ai/yudao-module-ai-server/src/main/resources/application-local.yaml
View File

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

11
yudao-module-ai/yudao-module-ai-server/src/main/resources/application.yaml
View File

@ -107,7 +107,7 @@ spring:
vectorstore: # 向量存储 vectorstore: # 向量存储
redis: redis:
initialize-schema: true 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 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: qdrant:
initialize-schema: true initialize-schema: true
@ -145,13 +145,14 @@ spring:
api-key: xxxx api-key: xxxx
moonshot: # 月之暗灭（KIMI） moonshot: # 月之暗灭（KIMI）
api-key: sk-abc api-key: sk-abc
deepseek: # DeepSeek
api-key: sk-e94db327cc7d457d99a8de8810fc6b12
chat:
options:
model: deepseek-chat
yudao: yudao:
ai: ai:
deep-seek: # DeepSeek
enable: true
api-key: sk-e94db327cc7d457d99a8de8810fc6b12
model: deepseek-chat
doubao: # 字节豆包 doubao: # 字节豆包
enable: true enable: true
api-key: 5c1b5747-26d2-4ebd-a4e0-dd0e8d8b4272 api-key: 5c1b5747-26d2-4ebd-a4e0-dd0e8d8b4272

14
yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/chat/AzureOpenAIChatModelTests.java
View File

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

3
yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/chat/BaiChuanChatModelTests.java
View File

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

18
yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/chat/DeepSeekChatModelTests.java
View File

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

88
yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/chat/LlamaChatModelTests.java
View File

@ -1,20 +1,6 @@
package cn.iocoder.yudao.module.ai.framework.ai.core.model.chat; 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.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 * {@link OllamaChatModel} 集成测试
@ -23,43 +9,43 @@ import java.util.List;
*/ */
public class LlamaChatModelTests { public class LlamaChatModelTests {
private final OllamaChatModel chatModel = OllamaChatModel.builder() // private final OllamaChatModel chatModel = OllamaChatModel.builder()
.ollamaApi(new OllamaApi("http://127.0.0.1:11434")) // Ollama 服务地址 // .ollamaApi(new OllamaApi("http://127.0.0.1:11434")) // Ollama 服务地址
.defaultOptions(OllamaOptions.builder() // .defaultOptions(OllamaOptions.builder()
.model(OllamaModel.LLAMA3.getName()) // 模型 // .model(OllamaModel.LLAMA3.getName()) // 模型
.build()) // .build())
.build(); // .build();
//
@Test // @Test
@Disabled // @Disabled
public void testCall() { // public void testCall() {
// 准备参数 // // 准备参数
List<Message> messages = new ArrayList<>(); // 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 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 = ？")); // messages.add(new UserMessage("1 + 1 = ？"));
//
// 调用 // // 调用
ChatResponse response = chatModel.call(new Prompt(messages)); // ChatResponse response = chatModel.call(new Prompt(messages));
// 打印结果 // // 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);
System.out.println(response.getResult().getOutput()); // System.out.println(response.getResult().getOutput());
}).then().block(); // }
} //
// @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();
// }
} }

20
yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/chat/MoonshotChatModelTests.java
View File

@ -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.Disabled;
import org.junit.jupiter.api.Test; 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.Message;
import org.springframework.ai.chat.messages.SystemMessage; import org.springframework.ai.chat.messages.SystemMessage;
import org.springframework.ai.chat.messages.UserMessage; import org.springframework.ai.chat.messages.UserMessage;
import org.springframework.ai.chat.model.ChatResponse; import org.springframework.ai.chat.model.ChatResponse;
import org.springframework.ai.chat.prompt.Prompt; 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 reactor.core.publisher.Flux;
import java.util.ArrayList; import java.util.ArrayList;
@ -22,11 +22,15 @@ import java.util.List;
*/ */
public class MoonshotChatModelTests { public class MoonshotChatModelTests {
private final MoonshotChatModel chatModel = new MoonshotChatModel( private final MoonshotChatModel chatModel = MoonshotChatModel.builder()
new MoonshotApi("sk-aHYYV1SARscItye5QQRRNbXij4fy65Ee7pNZlC9gsSQnUKXA"), // 密钥 .moonshotApi(MoonshotApi.builder()
MoonshotChatOptions.builder() .apiKey("sk-aHYYV1SARscItye5QQRRNbXij4fy65Ee7pNZlC9gsSQnUKXA") // 密钥
.model("moonshot-v1-8k") // 模型 .build())
.build()); .defaultOptions(MoonshotChatOptions.builder()
.model("kimi-k2-0711-preview") // 模型
.build())
.build();
@Test @Test
@Disabled @Disabled
public void testCall() { public void testCall() {

4
yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/chat/OllamaChatModelTests.java
View File

@ -23,7 +23,9 @@ import java.util.List;
public class OllamaChatModelTests { public class OllamaChatModelTests {
private final OllamaChatModel chatModel = OllamaChatModel.builder() 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() .defaultOptions(OllamaOptions.builder()
// .model("qwen") // 模型（https://ollama.com/library/qwen） // .model("qwen") // 模型（https://ollama.com/library/qwen）
.model("deepseek-r1") // 模型（https://ollama.com/library/deepseek-r1） .model("deepseek-r1") // 模型（https://ollama.com/library/deepseek-r1）

4
yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/chat/OpenAIChatModelTests.java
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@ -25,10 +25,10 @@ public class OpenAIChatModelTests {
private final OpenAiChatModel chatModel = OpenAiChatModel.builder() private final OpenAiChatModel chatModel = OpenAiChatModel.builder()
.openAiApi(OpenAiApi.builder() .openAiApi(OpenAiApi.builder()
.baseUrl("https://api.holdai.top") .baseUrl("https://api.holdai.top")
.apiKey("sk-aN6nWn3fILjrgLFT0fC4Aa60B72e4253826c77B29dC94f17") // apiKey .apiKey("sk-PytRecQlmjEteoa2RRN6cGnwslo72UUPLQVNEMS6K9yjbmpD") // apiKey
.build()) .build())
.defaultOptions(OpenAiChatOptions.builder() .defaultOptions(OpenAiChatOptions.builder()
.model(OpenAiApi.ChatModel.GPT_4_O) // 模型 .model(OpenAiApi.ChatModel.GPT_4_1_NANO) // 模型
.temperature(0.7) .temperature(0.7)
.build()) .build())
.build(); .build();

11
yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/chat/TongYiChatModelTests.java
View File

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

10
yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/chat/YiYanChatModelTests.java
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@ -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.Disabled;
import org.junit.jupiter.api.Test; 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.Message;
import org.springframework.ai.chat.messages.UserMessage; import org.springframework.ai.chat.messages.UserMessage;
import org.springframework.ai.chat.model.ChatResponse; import org.springframework.ai.chat.model.ChatResponse;
import org.springframework.ai.chat.prompt.Prompt; 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 reactor.core.publisher.Flux;
import java.util.ArrayList; import java.util.ArrayList;
@ -23,9 +23,9 @@ import java.util.List;
public class YiYanChatModelTests { public class YiYanChatModelTests {
private final QianFanChatModel chatModel = new QianFanChatModel( private final QianFanChatModel chatModel = new QianFanChatModel(
new QianFanApi("qS8k8dYr2nXunagK4SSU8Xjj", "pHGbx51ql2f0hOyabQvSZezahVC3hh3e"), // 密钥 new QianFanApi("DGnyzREuaY7av7c38bOM9Ji2", "9aR8myflEOPDrEeLhoXv0FdqANOAyIZW"), // 密钥
QianFanChatOptions.builder() QianFanChatOptions.builder()
.model(QianFanApi.ChatModel.ERNIE_4_0_8K_Preview.getValue()) .model("ERNIE-4.5-8K-Preview")
.build() .build()
); );

6
yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/image/OpenAiImageModelTests.java
View File

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

6
yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/image/QianFanImageTests.java
View File

@ -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.Disabled;
import org.junit.jupiter.api.Test; 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.ImagePrompt;
import org.springframework.ai.image.ImageResponse; 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; import static cn.iocoder.yudao.module.ai.framework.ai.core.model.image.StabilityAiImageModelTests.viewImage;

4
yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/image/StabilityAiImageModelTests.java
View File

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

2
yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/ppt/wdd/WenDuoDuoPptApiTests.java
View File

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

2
yudao-module-ai/yudao-module-ai-server/src/test/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/ppt/xunfei/XunFeiPptApiTests.java
View File

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

4
yudao-server/src/main/resources/application-dev.yaml
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@ -6,8 +6,8 @@ server:
spring: spring:
autoconfigure: autoconfigure:
exclude: exclude:
- org.springframework.ai.autoconfigure.vectorstore.qdrant.QdrantVectorStoreAutoConfiguration # 禁用 AI 模块的 Qdrant，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.autoconfigure.vectorstore.milvus.MilvusVectorStoreAutoConfiguration # 禁用 AI 模块的 Milvus，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 # 数据源配置项
datasource: datasource:
druid: # Druid 【监控】相关的全局配置 druid: # Druid 【监控】相关的全局配置

4
yudao-server/src/main/resources/application-local.yaml
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@ -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.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.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 - 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.vectorstore.qdrant.autoconfigure.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.milvus.autoconfigure.MilvusVectorStoreAutoConfiguration # 禁用 AI 模块的 Milvus，手动创建
# 数据源配置项 # 数据源配置项
datasource: datasource:
druid: # Druid 【监控】相关的全局配置 druid: # Druid 【监控】相关的全局配置

11
yudao-server/src/main/resources/application.yaml
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@ -174,7 +174,7 @@ spring:
vectorstore: # 向量存储 vectorstore: # 向量存储
redis: redis:
initialize-schema: true 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 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: qdrant:
initialize-schema: true initialize-schema: true
@ -212,13 +212,14 @@ spring:
api-key: xxxx api-key: xxxx
moonshot: # 月之暗灭（KIMI） moonshot: # 月之暗灭（KIMI）
api-key: sk-abc api-key: sk-abc
deepseek: # DeepSeek
api-key: sk-e94db327cc7d457d99a8de8810fc6b12
chat:
options:
model: deepseek-chat
yudao: yudao:
ai: ai:
deep-seek: # DeepSeek
enable: true
api-key: sk-e94db327cc7d457d99a8de8810fc6b12
model: deepseek-chat
doubao: # 字节豆包 doubao: # 字节豆包
enable: true enable: true
api-key: 5c1b5747-26d2-4ebd-a4e0-dd0e8d8b4272 api-key: 5c1b5747-26d2-4ebd-a4e0-dd0e8d8b4272