langchain4j实战：三种模型的使用（ChatLanguageModel、StreamingChatLanguageModel、ImageModel）_langchain4j 流式响应

langchain4j版本用的是0.27.1，LLM大模型使用OpenAi
本文主要介绍聊天对话、流式对话、文生图三种模式的使用，只需要两步就可以实现和LLM交互

引入pom依赖

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <parent>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-parent</artifactId>
        <version>3.2.1</version>
    </parent>
    <modelVersion>4.0.0</modelVersion>

    <groupId>org.example</groupId>
    <artifactId>langChain_demo</artifactId>
    <version>1.0-SNAPSHOT</version>

    <properties>
        <maven.compiler.source>17</maven.compiler.source>
        <maven.compiler.target>17</maven.compiler.target>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
        <langchain4j.version>0.27.1</langchain4j.version>
    </properties>
    <dependencies>
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j</artifactId>
            <version>${langchain4j.version}</version>
        </dependency>
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j-open-ai</artifactId>
            <version>${langchain4j.version}</version>
        </dependency>
    </dependencies>
</project>
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聊天对话ChatLanguageModel

apikey为demo时，将url转成代理地址http://langchain4j.dev/demo/openai/v1，非demo时，则url为https://api.openai.com/v1。
简单聊天场景可以使用demo测试，更高级的场景如文生图等需要自己申请的openAi的令牌key。
后续示例中的常量OPEN_AI_BASE_URL 为 https://api.openai.com/v1，OPEN_AI_API_KEY需要设置自己的key

    public static void main(String[] args) {
        ChatLanguageModel model = OpenAiChatModel.builder()
                .apiKey("demo")
                .build();
        String result = model.generate("你是谁");
        System.out.println(result);
    }
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流式对话StreamingChatLanguageModel

上面ChatLanguageModel模型，大模型会一下输出所有信息；如果需要像打字机一样，一个字一个字输出，则可以使用StreamingChatLanguageModel模型

    public static void main(String[] args) {
        StreamingChatLanguageModel model = OpenAiStreamingChatModel.builder()
                .baseUrl(OPEN_AI_BASE_URL)
                .apiKey(OPEN_AI_API_KEY)
                .build();
        model.generate("你好 我是小橘", new StreamingResponseHandler<AiMessage>() {
            @Override
            public void onNext(String token) {
                System.out.println(token);
                try {
                    TimeUnit.SECONDS.sleep(1);
                } catch (InterruptedException e) {
                    throw new RuntimeException(e);
                }
            }

            @Override
            public void onError(Throwable throwable) {
            }
        });
    }
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文生图ImageModel

大模型可以根据你的信息生成对应的图片，下面链接就是生成的橘猫图片url；响应除了可以拿到url外，也提供下Base64的编码的文件字符串

https://oaidalleapiprodscus.blob.core.windows.net/private/org-ZLTuOuStHhQibWNJKgkpotO2/user-TFhEhsgVpt9L4c1u6Smt9gIu/img-Qb8hXLdi3NQDnhxO1DKu7NH6.png?st=2024-05-17T06%3A58%3A23Z&se=2024-05-17T08%3A58%3A23Z&sp=r&sv=2021-08-06&sr=b&rscd=inline&rsct=image/png&skoid=6aaadede-4fb3-4698-a8f6-684d7786b067&sktid=a48cca56-e6da-484e-a814-9c849652bcb3&skt=2024-05-16T13%3A52%3A40Z&ske=2024-05-17T13%3A52%3A40Z&sks=b&skv=2021-08-06&sig=yHC60xphZw1Zu94VKPnWx0yK0Ggq/BzUsspwQKFTAC8%3D

    public static void main(String[] args) {
        ImageModel imageModel = OpenAiImageModel.builder()
                .baseUrl(OPEN_AI_BASE_URL)
                .apiKey(OPEN_AI_API_KEY)
                .build();
        Response<Image> response = imageModel.generate("橘猫");
        System.out.println(response.content().url());
    }
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