用 Spring AI 调用 OpenAI 对话接口

AlphaHinex

发布于 2024-12-03 21:16:32

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代码可运行

文章被收录于专栏：周拱壹卒

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代码可运行

环境准备

JDK

使用Spring AI[1] 需要JDK 17[2] 及以上版本。

$ java -version
openjdk version "17.0.2" 2022-01-18
OpenJDK Runtime Environment (build 17.0.2+8-86)
OpenJDK 64-Bit Server VM (build 17.0.2+8-86, mixed mode, sharing)

start.spring.io

从 https://start.spring.io/ 下载一个包含 Spring Web 依赖的 Maven 工程：

解压，并使用其中自带的 Maven Wrapper 进行构建：

$ unzip demo.zip
$ cd demo
$ ./mvnw clean package
...
[INFO] ------------------------------------------------------------------------
[INFO] BUILD SUCCESS
[INFO] ------------------------------------------------------------------------
[INFO] Total time:  5.569 s
[INFO] Finished at: 2024-11-30T13:58:27+08:00
[INFO] ------------------------------------------------------------------------

智谱 AI 开放平台

登录到智谱AI开放平台API Keys 页面[3] 获取最新版生成的用户 API Key，用于调用其提供的兼容 OpenAI 对话接口的免费模型GLM-4-Flash：

$ curl --location 'https://open.bigmodel.cn/api/paas/v4/chat/completions' \
--header 'Authorization: Bearer <你的apikey>' \
--header 'Content-Type: application/json' \
--data '{
    "model": "glm-4-flash",
    "messages": [
        {
            "role": "user",
            "content": "你好"
        }
    ]
}'
{"choices":[{"finish_reason":"stop","index":0,"message":{"content":"你好👋！很高兴见到你，有什么可以帮助你的吗？","role":"assistant"}}],"created":1732946586,"id":"202411301403051925a900b08f4e23","model":"glm-4-flash","request_id":"202411301403051925a900b08f4e23","usage":{"completion_tokens":16,"prompt_tokens":6,"total_tokens":22}}

添加依赖

在pom.xml 中添加 Spring AI 的相关配置及依赖[4]：

repositories：

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

dependencyManagement：

<dependencyManagement>
  <dependencies>
    <dependency>
      <groupId>org.springframework.ai</groupId>
      <artifactId>spring-ai-bom</artifactId>
      <version>1.0.0-SNAPSHOT</version>
      <type>pom</type>
      <scope>import</scope>
    </dependency>
  </dependencies>
</dependencyManagement>

dependency：

<dependency>
  <groupId>org.springframework.ai</groupId>
  <artifactId>spring-ai-openai-spring-boot-starter</artifactId>
</dependency>

使用 ChatClient 与 OpenAI 兼容模型接口对话

仅对接一个大模型时

可直接通过配置项注册并使用 ChatClient。

在application.properties 中添加 Spring AI OpenAI 的相关配置：

spring.ai.openai.base-url=https://open.bigmodel.cn/api/paas
spring.ai.openai.chat.completions-path=/v4/chat/completions
spring.ai.openai.api-key=<你的apikey>
spring.ai.openai.chat.options.model=glm-4-flash

创建一个配置类：

@Configuration
public class Config {

    @Bean
    ChatClient chatClient(ChatClient.Builder builder) {
        return builder.build();
    }

}

在工程中自带的DemoApplicationTests 单元测试中，验证对话效果：

@Autowired
ChatClient chatClient;

@Test
void autoConfig() {
    String userMsg = "who r u";
    System.out.println(chatClient.prompt().user(userMsg).call().content());
}

执行结果如下：

I am an AI assistant named ChatGLM, which is developed based on the language model jointly trained by Tsinghua University KEG Lab and Zhipu AI Company in 2024. My job is to provide appropriate answers and support to users' questions and requests.

需要对接多个大模型时

可定义一个工场类创建多个 ChatClient 实例：

public class ChatClientFactory {

    public static ChatClient createOpenAiChatClient(String baseUrl, String apiKey, String model, String completionsPath) {
        if (StringUtils.isBlank(completionsPath)) {
            completionsPath = "/v1/chat/completions";
        }
        OpenAiApi openAiApi = new OpenAiApi(baseUrl, apiKey, completionsPath,
            "/v1/embeddings", RestClient.builder(), WebClient.builder(), RetryUtils.DEFAULT_RESPONSE_ERROR_HANDLER);
        OpenAiChatModel openAiChatModel = new OpenAiChatModel(openAiApi, OpenAiChatOptions.builder().withModel(model).build());
        return ChatClient.create(openAiChatModel);
    }

}

@Test
void multiClients() {
    ChatClient llm1 = ChatClientFactory.createOpenAiChatClient("https://open.bigmodel.cn/api/paas", "xxxx", "glm-4-flash", "/v4/chat/completions");
    ChatClient llm2 = ChatClientFactory.createOpenAiChatClient("https://open.bigmodel.cn/api/paas", "xxxx", "glm-4-flash", "/v4/chat/completions");

    String userMsg = "你是谁？";
    System.out.println(llm1.prompt().user(userMsg).call().content());
    System.out.println(llm2.prompt().user(userMsg).call().content());
}