springboot之langchain4j学习-01

与springboot集成

前言

记录一下学习的过程

一、与springboot集成

1. langchain4j需要集成版本说明

2. 引入依赖

  <dependencyManagement>
        <dependencies>
            <dependency>
                <groupId>dev.langchain4j</groupId>
                <artifactId>langchain4j-bom</artifactId>
                <version>1.4.0</version>
                <type>pom</type>
                <scope>import</scope>
            </dependency>
        </dependencies>
    </dependencyManagement>
        <dependencies>

        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j-spring-boot-starter</artifactId>
        </dependency>

        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j-open-ai-spring-boot-starter</artifactId>
        </dependency>

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

        <!-- for Flux<String> support -->
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j-reactor</artifactId>
        </dependency>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-webflux</artifactId>
        </dependency>

        <!-- observability -->
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-actuator</artifactId>
        </dependency>
        <dependency>
            <groupId>io.micrometer</groupId>
            <artifactId>micrometer-tracing-bridge-otel</artifactId>
        </dependency>
        <dependency>
            <groupId>io.opentelemetry</groupId>
            <artifactId>opentelemetry-exporter-zipkin</artifactId>
        </dependency>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-aop</artifactId>
        </dependency>
    </dependencies>

3. 引入LLM的配置（在application.properties）

langchain4j.open-ai.chat-model.base-url=https://dashscope.aliyuncs.com/compatible-mode/v1
langchain4j.open-ai.chat-model.api-key=xxxxxx
langchain4j.open-ai.chat-model.model-name=deepseek-v3.1

ps：现在是用的百炼，根据后面需求方式配置

4. 简单写个demo试一下

@RestController
public class ChatAgentController {
    @Autowired
    private OpenAiChatModel openAiChatModel;

    @GetMapping("/chatOpenAi")
    public String openAi(@RequestParam(value = "message", defaultValue = "Hello") String message) {
        return openAiChatModel.chat(message);
    }
 }

运行一下~~，搞定。

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