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README
Apache-2.0

Spring AI Alibaba

Spring AI Alibaba 是一款 Java 语言实现的 AI 应用开发框架,旨在简化 Java AI 应用程序开发,让 Java 开发者像使用 Spring 开发普通应用一样开发 AI 应用。Spring AI Alibaba 基于 Spring AI 开源项目构建,默认提供阿里云基础模型服务、开源及商业生态组件的集成与最佳实践。

快速开始

请参考快速开始 了解如何使用 Spring AI Alibaba 快速开发生成式 AI 应用。

总的来说,使用 Spring AI Alibaba 开发应用与使用普通 Spring Boot 没有什么区别,只需要增加 spring-ai-alibaba-starter 依赖,将 ChatClient Bean 注入就可以实现与模型聊天了。

因为 Spring AI Alibaba 基于 Spring Boot 3.x 开发,因此对 JDK 要求 17 及以上版本。

  1. 在项目中加入 spring-ai-alibaba-starter 依赖。

    <dependency>
    	<groupId>com.alibaba.cloud.ai</groupId>
    	<artifactId>spring-ai-alibaba-starter</artifactId>
    	<version>1.0.0-M3.2</version>
    </dependency>
    

    注意:由于 spring-ai 相关依赖包还没有发布到中央仓库,如出现 spring-ai-core 等相关依赖解析问题,请在您项目的 pom.xml 依赖中加入如下仓库配置。

    <repositories>
    	<repository>
    		<id>spring-milestones</id>
    		<name>Spring Milestones</name>
    		<url>https://repo.spring.io/milestone</url>
    		<snapshots>
    			<enabled>false</enabled>
    		</snapshots>
    	</repository>
    </repositories>
    

    补充:如果您的本地 maven settings.xml 中的 mirrorOf 标签配置了通配符 * ,请根据以下示例修改。

    <mirror>
      <id>xxxx</id>
      <mirrorOf>*,!spring-milestones</mirrorOf>
      <name>xxxx</name>
      <url>xxxx</url>
    </mirror>
    
  2. 注入 ChatClient

    @RestController
    public class ChatController {
    
    	private final ChatClient chatClient;
    
    	public ChatController(ChatClient.Builder builder) {
    		this.chatClient = builder.build();
    	}
    
    	@GetMapping("/chat")
    	public String chat(String input) {
    		return this.chatClient.prompt()
    				.user(input)
    				.call()
    				.content();
    	}
    }
    

示例

请在 spring-ai-alibaba-examples 查看更多 Example 示例。

  • Hello World
  • Chat Model
  • Multi Model
  • Function Calling
  • Structured Output
  • Prompt
  • RAG
  • Flight Booking Playground,一个贴近实际使用场景,综合运用了 prompt template、function calling、chat memory 和 rag 等的智能机票助手应用。

特性

以下是 Spring AI Alibaba 支持的核心能力,未来更多高级功能将以这些核心能力为基础。请参考官网文档 Spring AI Alibaba 核心概念以及 AI 应用开发最佳实践

  • 开发复杂 AI 应用的高阶抽象 Fluent API -- ChatClient
  • 提供多种大模型服务对接能力,包括主流开源与阿里云通义大模型服务(百炼)等
  • 支持的模型类型包括聊天、文生图、音频转录、文生语音等
  • 支持同步和流式 API,在保持应用层 API 不变的情况下支持灵活切换底层模型服务,支持特定模型的定制化能力(参数传递)
  • 支持 Structured Output,即将 AI 模型输出映射到 POJOs
  • 支持矢量数据库存储与检索
  • 支持函数调用 Function Calling
  • 支持构建 AI Agent 所需要的工具调用和对话内存记忆能力
  • 支持 RAG 开发模式,包括离线文档处理如 DocumentReader、Splitter、Embedding、VectorStore 等,支持 Retrieve 检索

Roadmap

Spring AI Alibaba 提供 AI 开源框架以及与阿里巴巴整体开源生态的深度适配,以帮助 Java 开发者快速构建原生 AI 应用架构。

  • Prompt Template 管理
  • 事件驱动的 AI 应用程序
  • 更多 Vector Database 支持
  • 函数计算等部署模式
  • 可观测性建设
  • AI 代理节点开发能力,如绿网、限流、多模型切换等
  • 开发者工具集

ai-native-architecture

参考资料

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