feat:【AI 大模型】依赖 spring ai 升级到 1.0.0

This commit is contained in:
YunaiV 2025-07-14 20:34:42 +08:00
parent e50250449a
commit c789418a7b
10 changed files with 56 additions and 51 deletions

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@ -19,7 +19,8 @@
国外OpenAI、Ollama、Midjourney、StableDiffusion、Suno
</description>
<properties>
<spring-ai.version>1.0.0-M6</spring-ai.version>
<spring-ai.version>1.0.0</spring-ai.version>
<alibaba-ai.version>1.0.0.2</alibaba-ai.version>
<tinyflow.version>1.0.2</tinyflow.version>
</properties>
@ -75,65 +76,66 @@
<!-- Spring AI Model 模型接入 -->
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-openai-spring-boot-starter</artifactId>
<artifactId>spring-ai-starter-model-openai</artifactId>
<version>${spring-ai.version}</version>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-azure-openai-spring-boot-starter</artifactId>
<artifactId>spring-ai-starter-model-azure-openai</artifactId>
<version>${spring-ai.version}</version>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-ollama-spring-boot-starter</artifactId>
<artifactId>spring-ai-starter-model-ollama</artifactId>
<version>${spring-ai.version}</version>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-stability-ai-spring-boot-starter</artifactId>
<artifactId>spring-ai-starter-model-stability-ai</artifactId>
<version>${spring-ai.version}</version>
</dependency>
<dependency>
<!-- 通义千问 -->
<groupId>com.alibaba.cloud.ai</groupId>
<artifactId>spring-ai-alibaba-starter</artifactId>
<version>${spring-ai.version}.1</version>
<artifactId>spring-ai-alibaba-starter-dashscope</artifactId>
<version>${alibaba-ai.version}</version>
</dependency>
<dependency>
<!-- 文心一言 -->
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-qianfan-spring-boot-starter</artifactId>
<version>${spring-ai.version}</version>
<groupId>org.springaicommunity</groupId>
<artifactId>qianfan-spring-boot-starter</artifactId>
<version>1.0.0</version>
</dependency>
<dependency>
<!-- 智谱 GLM -->
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-zhipuai-spring-boot-starter</artifactId>
<artifactId>spring-ai-starter-model-zhipuai</artifactId>
<version>${spring-ai.version}</version>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-minimax-spring-boot-starter</artifactId>
<artifactId>spring-ai-starter-model-minimax</artifactId>
<version>${spring-ai.version}</version>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-moonshot-spring-boot-starter</artifactId>
<version>${spring-ai.version}</version>
<!-- 月之暗灭 -->
<groupId>org.springaicommunity</groupId>
<artifactId>moonshot-spring-boot-starter</artifactId>
<version>1.0.0</version>
</dependency>
<!-- 向量存储https://db-engines.com/en/ranking/vector+dbms -->
<dependency>
<!-- Qdranthttps://qdrant.tech/ -->
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-qdrant-store</artifactId>
<artifactId>spring-ai-starter-vector-store-qdrant</artifactId>
<version>${spring-ai.version}</version>
</dependency>
<dependency>
<!-- Redishttps://redis.io/docs/latest/develop/get-started/vector-database/ -->
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-redis-store</artifactId>
<artifactId>spring-ai-starter-vector-store-redis</artifactId>
<version>${spring-ai.version}</version>
</dependency>
<dependency>
@ -144,7 +146,7 @@
<dependency>
<!-- Milvushttps://milvus.io/ -->
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-milvus-store</artifactId>
<artifactId>spring-ai-starter-vector-store-milvus</artifactId>
<version>${spring-ai.version}</version>
<exclusions>
<!-- 解决和 logback 的日志冲突 -->

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@ -14,10 +14,6 @@ import cn.iocoder.yudao.module.ai.framework.ai.core.model.siliconflow.SiliconFlo
import cn.iocoder.yudao.module.ai.framework.ai.core.model.suno.api.SunoApi;
import cn.iocoder.yudao.module.ai.framework.ai.core.model.xinghuo.XingHuoChatModel;
import lombok.extern.slf4j.Slf4j;
import org.springframework.ai.autoconfigure.vectorstore.milvus.MilvusServiceClientProperties;
import org.springframework.ai.autoconfigure.vectorstore.milvus.MilvusVectorStoreProperties;
import org.springframework.ai.autoconfigure.vectorstore.qdrant.QdrantVectorStoreProperties;
import org.springframework.ai.autoconfigure.vectorstore.redis.RedisVectorStoreProperties;
import org.springframework.ai.embedding.BatchingStrategy;
import org.springframework.ai.embedding.TokenCountBatchingStrategy;
import org.springframework.ai.model.tool.ToolCallingManager;
@ -26,6 +22,10 @@ import org.springframework.ai.openai.OpenAiChatOptions;
import org.springframework.ai.openai.api.OpenAiApi;
import org.springframework.ai.tokenizer.JTokkitTokenCountEstimator;
import org.springframework.ai.tokenizer.TokenCountEstimator;
import org.springframework.ai.vectorstore.milvus.autoconfigure.MilvusServiceClientProperties;
import org.springframework.ai.vectorstore.milvus.autoconfigure.MilvusVectorStoreProperties;
import org.springframework.ai.vectorstore.qdrant.autoconfigure.QdrantVectorStoreProperties;
import org.springframework.ai.vectorstore.redis.autoconfigure.RedisVectorStoreProperties;
import org.springframework.boot.autoconfigure.condition.ConditionalOnProperty;
import org.springframework.boot.context.properties.EnableConfigurationProperties;
import org.springframework.context.annotation.Bean;

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

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@ -9,9 +9,6 @@ import cn.hutool.core.util.ObjUtil;
import cn.hutool.core.util.StrUtil;
import cn.hutool.extra.spring.SpringUtil;
import cn.hutool.http.HttpUtil;
import cn.iocoder.yudao.module.ai.enums.model.AiPlatformEnum;
import cn.iocoder.yudao.module.ai.framework.ai.core.model.midjourney.api.MidjourneyApi;
import cn.iocoder.yudao.module.ai.framework.ai.core.model.siliconflow.SiliconFlowImageOptions;
import cn.iocoder.yudao.framework.common.pojo.PageResult;
import cn.iocoder.yudao.framework.common.util.object.BeanUtils;
import cn.iocoder.yudao.module.ai.controller.admin.image.vo.AiImageDrawReqVO;
@ -24,17 +21,20 @@ import cn.iocoder.yudao.module.ai.dal.dataobject.image.AiImageDO;
import cn.iocoder.yudao.module.ai.dal.dataobject.model.AiModelDO;
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.enums.model.AiPlatformEnum;
import cn.iocoder.yudao.module.ai.framework.ai.core.model.midjourney.api.MidjourneyApi;
import cn.iocoder.yudao.module.ai.framework.ai.core.model.siliconflow.SiliconFlowImageOptions;
import cn.iocoder.yudao.module.ai.service.model.AiModelService;
import cn.iocoder.yudao.module.infra.api.file.FileApi;
import com.alibaba.cloud.ai.dashscope.image.DashScopeImageOptions;
import jakarta.annotation.Resource;
import lombok.extern.slf4j.Slf4j;
import org.springaicommunity.qianfan.QianFanImageOptions;
import org.springframework.ai.image.ImageModel;
import org.springframework.ai.image.ImageOptions;
import org.springframework.ai.image.ImagePrompt;
import org.springframework.ai.image.ImageResponse;
import org.springframework.ai.openai.OpenAiImageOptions;
import org.springframework.ai.qianfan.QianFanImageOptions;
import org.springframework.ai.stabilityai.api.StabilityAiImageOptions;
import org.springframework.ai.zhipuai.ZhiPuAiImageOptions;
import org.springframework.scheduling.annotation.Async;
@ -140,10 +140,10 @@ public class AiImageServiceImpl implements AiImageService {
private static ImageOptions buildImageOptions(AiImageDrawReqVO draw, AiModelDO model) {
if (ObjUtil.equal(model.getPlatform(), AiPlatformEnum.OPENAI.getPlatform())) {
// https://platform.openai.com/docs/api-reference/images/create
return OpenAiImageOptions.builder().withModel(model.getModel())
.withHeight(draw.getHeight()).withWidth(draw.getWidth())
.withStyle(MapUtil.getStr(draw.getOptions(), "style")) // 风格
.withResponseFormat("b64_json")
return OpenAiImageOptions.builder().model(model.getModel())
.height(draw.getHeight()).width(draw.getWidth())
.style(MapUtil.getStr(draw.getOptions(), "style")) // 风格
.responseFormat("b64_json")
.build();
} else if (ObjUtil.equal(model.getPlatform(), AiPlatformEnum.SILICON_FLOW.getPlatform())) {
// https://docs.siliconflow.cn/cn/api-reference/images/images-generations

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

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

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

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

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

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