LangChain4J Java 集成指南：从入门到高级应用

LangChain4J Java 集成指南：从入门到高级应用 | 极客日志

<?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">
    <modelVersion>4.0.0</modelVersion>
    <groupId>com.hk</groupId>
    <artifactId>langcChain4J-study</artifactId>
    <version>1.0-SNAPSHOT</version>
    <packaging>pom</packaging>
    <name>langchain4j-study 父工程</name>
    <properties>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
        <project.reporting.outputEncoding>UTF-8</project.reporting.outputEncoding>
        <java.version>17</java.version>
        <maven.compiler.source>21</maven.compiler.source>
        <maven.compiler.target>21</maven.compiler.target>
        <!-- Spring Boot -->
        <spring-boot.version>3.5.0</spring-boot.version>
        <!-- Spring AI -->
        <spring-ai.version>1.0.0</spring-ai.version>
        <!-- Spring AI Alibaba -->
        <spring-ai-alibaba.version>1.0.0-M6.1</spring-ai-alibaba.version>
        <!-- langchain4j -->
        <langchain4j.version>1.0.1</langchain4j.version>
        <!--langchain4j-community 引入阿里云百炼平台依赖管理清单-->
        <langchain4j-community.version>1.0.1-beta6</langchain4j-community.version>
        <!-- maven plugin -->
        <maven-deploy-plugin.version>3.1.1</maven-deploy-plugin.version>
        <flatten-maven-plugin.version>1.3.0</flatten-maven-plugin.version>
        <maven-compiler-plugin.version>3.8.1</maven-compiler-plugin.version>
    </properties>
    <dependencyManagement>
        <dependencies>
            <!-- Spring Boot -->
            <dependency>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-dependencies</artifactId>
                <version>${spring-boot.version}</version>
                <type>pom</type>
                <scope>import</scope>
            </dependency>
            <!-- Spring AI -->
            <dependency>
                <groupId>org.springframework.ai</groupId>
                <artifactId>spring-ai-bom</artifactId>
                <version>${spring-ai.version}</version>
                <type>pom</type>
                <scope>import</scope>
            </dependency>
            <!-- Spring AI Alibaba -->
            <dependency>
                <groupId>com.alibaba.cloud.ai</groupId>
                <artifactId>spring-ai-alibaba-starter</artifactId>
                <version>${spring-ai-alibaba.version}</version>
            </dependency>
            <!--langchain4j 的依赖清单，加载 BOM 后所有 langchain4j 版本号可以被统一管理起来 https://docs.langchain4j.dev/get-started -->
            <dependency>
                <groupId>dev.langchain4j</groupId>
                <artifactId>langchain4j-bom</artifactId>
                <version>${langchain4j.version}</version>
                <type>pom</type>
                <scope>import</scope>
            </dependency>
            <!--引入阿里云百炼平台依赖管理清单 https://docs.langchain4j.dev/integrations/language-models/dashscope -->
            <dependency>
                <groupId>dev.langchain4j</groupId>
                <artifactId>langchain4j-community-bom</artifactId>
                <version>${langchain4j-community.version}</version>
                <type>pom</type>
                <scope>import</scope>
            </dependency>
        </dependencies>
    </dependencyManagement>
    <build>
        <plugins>
            <plugin>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-maven-plugin</artifactId>
                <version>${spring-boot.version}</version>
            </plugin>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-deploy-plugin</artifactId>
                <version>${maven-deploy-plugin.version}</version>
                <configuration>
                    <skip>true</skip>
                </configuration>
            </plugin>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-compiler-plugin</artifactId>
                <version>${maven-compiler-plugin.version}</version>
                <configuration>
                    <release>${java.version}</release>
                    <compilerArgs>
                        <compilerArg>-parameters</compilerArg>
                    </compilerArgs>
                </configuration>
            </plugin>
            <plugin>
                <groupId>org.codehaus.mojo</groupId>
                <artifactId>flatten-maven-plugin</artifactId>
                <version>${flatten-maven-plugin.version}</version>
                <inherited>true</inherited>
                <executions>
                    <execution>
                        <id>flatten</id>
                        <phase>process-resources</phase>
                        <goals>
                            <goal>flatten</goal>
                        </goals>
                        <configuration>
                            <updatePomFile>true</updatePomFile>
                            <flattenMode>ossrh</flattenMode>
                            <pomElements>
                                <distributionManagement>remove</distributionManagement>
                                <dependencyManagement>remove</dependencyManagement>
                                <repositories>remove</repositories>
                                <scm>keep</scm>
                                <url>keep</url>
                                <organization>resolve</organization>
                            </pomElements>
                        </configuration>
                    </execution>
                    <execution>
                        <id>flatten.clean</id>
                        <phase>clean</phase>
                        <goals>
                            <goal>clean</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>
        </plugins>
    </build>
    <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>
        <repository>
            <id>aliyunmaven</id>
            <name>aliyun</name>
            <url>https://maven.aliyun.com/repository/public</url>
        </repository>
    </repositories>
    <pluginRepositories>
        <pluginRepository>
            <id>public</id>
            <name>aliyun nexus</name>
            <url>https://maven.aliyun.com/repository/public</url>
            <releases>
                <enabled>true</enabled>
            </releases>
            <snapshots>
                <enabled>false</enabled>
            </snapshots>
        </pluginRepository>
    </pluginRepositories>
</project>

<?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">
    <modelVersion>4.0.0</modelVersion>
    <parent>
        <groupId>com.hk</groupId>
        <artifactId>langcChain4J-study</artifactId>
        <version>1.0-SNAPSHOT</version>
    </parent>
    <artifactId>langcChain4J-01study</artifactId>
    <properties>
        <maven.compiler.source>21</maven.compiler.source>
        <maven.compiler.target>21</maven.compiler.target>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    </properties>
    <dependencies>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-web</artifactId>
        </dependency>
        <!--所有调用均基于 OpenAI 协议标准，实现一致的接口设计与规范 LangChain4j 提供与许多 LLM 提供商的集成 从最简单的开始方式是从 OpenAI 集成开始 https://docs.langchain4j.dev/get-started -->
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j-open-ai</artifactId>
        </dependency>
        <!--langchain4j 高阶-->
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j</artifactId>
        </dependency>
        <!--lombok-->
        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
            <optional>true</optional>
        </dependency>
        <!--test-->
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-test</artifactId>
            <scope>test</scope>
        </dependency>
    </dependencies>
    <build>
        <plugins>
            <plugin>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-maven-plugin</artifactId>
            </plugin>
        </plugins>
    </build>
</project>

server.port=8001
spring.application.name=langchain4j-01study

@Configuration
public class LLMConfig {
    @Bean
    public ChatModel chatModel() {
        return OpenAiChatModel.builder()
                .apiKey(System.getenv("aliQwen-api"))
                .baseUrl("https://dashscope.aliyuncs.com/compatible-mode/v1")
                .modelName("qwen-plus")
                .build();
    }
}

@RestController
public class Study01Controller {
    @Resource
    private ChatModel chatModel;

    @GetMapping("/chat")
    public String chat(@RequestParam(name = "msg", defaultValue = "你是谁") String msg) {
        return chatModel.chat(msg);
    }
}

@Configuration
public class LLMConfig {
    @Bean("qwen")
    public ChatModel qwenChatModel() {
        return OpenAiChatModel.builder()
                .apiKey(System.getenv("aliQwen-api"))
                .baseUrl("https://dashscope.aliyuncs.com/compatible-mode/v1")
                .modelName("qwen-plus")
                .build();
    }

    @Bean("deepseek")
    public ChatModel deepseekChatModel() {
        return OpenAiChatModel.builder()
                .apiKey("sk-4af********")
                .baseUrl("https://api.deepseek.com/v1")
                .modelName("deepseek-chat")
                .build();
    }
}

@RestController
public class Study01Controller {
    @Resource(name = "qwen")
    private ChatModel qwenChatModel;

    @Resource(name = "deepseek")
    private ChatModel deepseekChatModel;

    @GetMapping("/chat/v1")
    public String chatV1(@RequestParam(name = "msg", defaultValue = "你是谁") String msg) {
        return qwenChatModel.chat(msg);
    }

    @GetMapping("/chat/v2")
    public String chatV2(@RequestParam(name = "msg", defaultValue = "你是谁") String msg) {
        return deepseekChatModel.chat(msg);
    }
}

<?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">
    <modelVersion>4.0.0</modelVersion>
    <parent>
        <groupId>com.hk</groupId>
        <artifactId>langcChain4J-study</artifactId>
        <version>1.0-SNAPSHOT</version>
    </parent>
    <artifactId>langChain4j-02boot</artifactId>
    <properties>
        <maven.compiler.source>21</maven.compiler.source>
        <maven.compiler.target>21</maven.compiler.target>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    </properties>
    <dependencies>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-web</artifactId>
        </dependency>
        <!--langchain4j 原生 基础-->
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j-open-ai</artifactId>
        </dependency>
        <!--langchain4j 原生 高阶-->
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j</artifactId>
        </dependency>
        <!--1 LangChain4j 整合 boot 底层支持-->
        <!-- https://docs.langchain4j.dev/tutorials/spring-boot-integration -->
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j-open-ai-spring-boot-starter</artifactId>
        </dependency>
        <!--2 LangChain4j 整合 boot 高阶支持-->
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j-spring-boot-starter</artifactId>
        </dependency>
        <!--lombok-->
        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
            <optional>true</optional>
        </dependency>
        <!--test-->
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-test</artifactId>
            <scope>test</scope>
        </dependency>
    </dependencies>
    <build>
        <plugins>
            <plugin>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-maven-plugin</artifactId>
            </plugin>
        </plugins>
    </build>
</project>

server.port=8002
spring.application.name=langchain4j-02boot
# https://docs.langchain4j.dev/tutorials/spring-boot-integration
langchain4j.open-ai.chat-model.api-key=${aliQwen-api}
langchain4j.open-ai.chat-model.model-name=qwen-plus
langchain4j.open-ai.chat-model.base-url=https://dashscope.aliyuncs.com/compatible-mode/v1

@RestController
public class PopularIntegrationsController {
    @Resource
    private ChatModel chatModel;

    @GetMapping("/chatv1")
    public String chat(String msg) {
        return chatModel.chat(msg);
    }
}

@AiService
public interface ChatAssistant {
    String chat(String prompt);
}

@RestController
public class DeclarativeAIServiceController {
    @Resource
    private ChatAssistant chatAssistant;

    @GetMapping("/chatv2")
    public String chat(String msg) {
        return chatAssistant.chat(msg);
    }
}

<?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">
    <modelVersion>4.0.0</modelVersion>
    <parent>
        <groupId>com.hk</groupId>
        <artifactId>langcChain4J-study</artifactId>
        <version>1.0-SNAPSHOT</version>
    </parent>
    <artifactId>langChain4j-03lowhigh</artifactId>
    <properties>
        <maven.compiler.source>21</maven.compiler.source>
        <maven.compiler.target>21</maven.compiler.target>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    </properties>
    <dependencies>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-web</artifactId>
        </dependency>
        <!--langchain4j-open-ai 基础-->
        <!--所有调用均基于 OpenAI 协议标准，实现一致的接口设计与规范 LangChain4j 提供与许多 LLM 提供商的集成 从最简单的开始方式是从 OpenAI 集成开始 https://docs.langchain4j.dev/get-started -->
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j-open-ai</artifactId>
        </dependency>
        <!--langchain4j 高阶-->
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j</artifactId>
        </dependency>
        <!--lombok-->
        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
            <optional>true</optional>
        </dependency>
        <!--test-->
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-test</artifactId>
            <scope>test</scope>
        </dependency>
    </dependencies>
    <build>
        <plugins>
            <plugin>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-maven-plugin</artifactId>
            </plugin>
        </plugins>
    </build>
</project>

server.port=8003
spring.application.name=langChain4j-03lowhigh

@Configuration
public class LLMConfig {
    @Bean
    public ChatModel chatModel() {
        return OpenAiChatModel.builder()
                .apiKey(System.getenv("aliQwen-api"))
                .modelName("qwen-plus")
                .baseUrl("https://dashscope.aliyuncs.com/compatible-mode/v1")
                .build();
    }
}

@RestController
public class LowApiController {
    @Resource
    private ChatModel chatModel;

    @GetMapping("/chat1")
    public String chat1(@RequestParam(name = "msg", defaultValue = "你是谁") String msg) {
        return chatModel.chat(msg);
    }
}

@RestController
public class LowApiController {
    @Resource
    private ChatModel chatModel;

    @GetMapping("/chat1")
    public String chat1(@RequestParam(name = "msg", defaultValue = "你是谁") String msg) {
        return chatModel.chat(msg);
    }

    @GetMapping("/chat2")
    public String chat2(@RequestParam(name = "msg", defaultValue = "你是谁") String msg) {
        ChatResponse chatResponse = chatModel.chat(UserMessage.from(msg));
        String text = chatResponse.aiMessage().text();
        TokenUsage tokenUsage = chatResponse.tokenUsage();
        System.out.println("本次 token 消耗：" + tokenUsage);
        return text;
    }
}

public interface ChatAssistant {
    String chat(String prompt);
}

package com.hk.study.config;

import com.hk.study.service.ChatAssistant;
import dev.langchain4j.model.chat.ChatModel;
import dev.langchain4j.model.openai.OpenAiChatModel;
import dev.langchain4j.service.AiServices;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;

@Configuration
public class LLMConfig {
    @Bean
    public ChatModel chatModel() {
        return OpenAiChatModel.builder()
                .apiKey(System.getenv("aliQwen-api"))
                .modelName("qwen-plus")
                .baseUrl("https://dashscope.aliyuncs.com/compatible-mode/v1")
                .build();
    }

    @Bean
    public ChatAssistant chatAssistant(ChatModel chatModel) {
        return AiServices.create(ChatAssistant.class, chatModel);
    }
}

@RestController
public class HighApiController {
    @Resource
    private ChatAssistant chatAssistant;

    @GetMapping("chatv2")
    public String chatv2(String msg) {
        return chatAssistant.chat(msg);
    }
}

@Bean
public ChatModel chatModel() {
    return OpenAiChatModel.builder()
            .apiKey(System.getenv("aliQwen-api"))
            .modelName("qwen-plus")
            .baseUrl("https://dashscope.aliyuncs.com/compatible-mode/v1")
            // 开启日志，日志级别设置为 DEBUG 才会打印日志
            .logRequests(true)
            .logResponses(true)
            .build();
}

server.port=8003
spring.application.name=langChain4j-03lowhigh
# 开启 langchain4j 的日志，日志级别设置为 DEBUG 才会打印日志
logging.level.dev.langchain4j=DEBUG

public class TestChatModelListener implements ChatModelListener {
    @Override
    public void onRequest(ChatModelRequestContext requestContext) {
        // onRequest 配置的 k:v 键值对，在 onResponse 阶段可以获得，上下文传递参数好用
        String uuidValue = IdUtil.simpleUUID();
        requestContext.attributes().put("TraceID", uuidValue);
        System.out.println("配置请求参数：TraceID == " + uuidValue);
    }

    @Override
    public void onResponse(ChatModelResponseContext responseContext) {
        Object object = responseContext.attributes().get("TraceID");
        System.out.println("获取请求参数：TraceID == " + object);
    }

    @Override
    public void onError(ChatModelErrorContext errorContext) {
        System.out.println("出错了...");
    }
}

@Bean
public ChatModel chatModel() {
    return OpenAiChatModel.builder()
            .apiKey(System.getenv("aliQwen-api"))
            .modelName("qwen-plus")
            .baseUrl("https://dashscope.aliyuncs.com/compatible-mode/v1")
            .listeners(List.of(new TestChatModelListener()))
            .build();
}

@Bean
public ChatModel chatModel() {
    return OpenAiChatModel.builder()
            .apiKey(System.getenv("aliQwen-api"))
            .modelName("qwen-plus")
            .baseUrl("https://dashscope.aliyuncs.com/compatible-mode/v1")
            .logRequests(true)
            .logResponses(true)
            .maxRetries(2)
            .build();
}

@Bean
public ChatModel chatModel() {
    return OpenAiChatModel.builder()
            .apiKey(System.getenv("aliQwen-api"))
            .modelName("qwen-plus")
            .baseUrl("https://dashscope.aliyuncs.com/compatible-mode/v1")
            .logRequests(true)
            .maxRetries(2)
            .timeout(Duration.ofSeconds(1))
            .build();
}

<?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">
    <modelVersion>4.0.0</modelVersion>
    <parent>
        <groupId>com.hk</groupId>
        <artifactId>langcChain4J-study</artifactId>
        <version>1.0-SNAPSHOT</version>
    </parent>
    <artifactId>langChain4j-04chatimage</artifactId>
    <properties>
        <maven.compiler.source>21</maven.compiler.source>
        <maven.compiler.target>21</maven.compiler.target>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    </properties>
    <dependencies>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-web</artifactId>
        </dependency>
        <!--langchain4j-open-ai 基础-->
        <!--所有调用均基于 OpenAI 协议标准，实现一致的接口设计与规范 LangChain4j 提供与许多 LLM 提供商的集成 从最简单的开始方式是从 OpenAI 集成开始 https://docs.langchain4j.dev/get-started -->
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j-open-ai</artifactId>
        </dependency>
        <!--langchain4j 高阶-->
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j</artifactId>
        </dependency>
        <!--lombok-->
        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
            <optional>true</optional>
        </dependency>
        <!--hutool-->
        <dependency>
            <groupId>cn.hutool</groupId>
            <artifactId>hutool-all</artifactId>
            <version>5.8.22</version>
        </dependency>
        <!--test-->
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-test</artifactId>
            <scope>test</scope>
        </dependency>
    </dependencies>
    <build>
        <plugins>
            <plugin>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-maven-plugin</artifactId>
            </plugin>
        </plugins>
    </build>
</project>

server.port=8004
spring.application.name=langchain4j-04chatimage

@Configuration
public class LLMConfig {
    @Bean
    public ChatModel chatModel() {
        return OpenAiChatModel.builder()
                .apiKey(System.getenv("aliQwen-api"))
                .modelName("qwen-vl-max")
                .baseUrl("https://dashscope.aliyuncs.com/compatible-mode/v1")
                .build();
    }
}

@RestController
public class ImageModelController {
    @Resource
    private ChatModel chatModel;

    @Value("classpath:mi.jpg")
    private org.springframework.core.io.Resource imageResource;

    @GetMapping("/image")
    public String image() throws IOException {
        // 1、将图片通过 Base64 编码转为字符串
        byte[] imageBytes = imageResource.getContentAsByteArray();
        String encodeToString = Base64.getEncoder().encodeToString(imageBytes);
        // 2、构建提示词 userMessage
        UserMessage userMessage = UserMessage.from(
                TextContent.from("从以下图片中获取来源网站名称，股价走势和 5 月 30 号股价"),
                ImageContent.from(encodeToString, "image/jpg")
        );
        // 3、调用模型获取回答
        ChatResponse chatResponse = chatModel.chat(userMessage);
        String response = chatResponse.aiMessage().text();
        return response;
    }
}

<!--langchain4j-community 引入阿里云百炼平台依赖管理清单-->
<langchain4j-community.version>1.0.1-beta6</langchain4j-community.version>

<!--引入阿里云百炼平台依赖管理清单
     https://docs.langchain4j.dev/integrations/language-models/dashscope
     -->
<dependency>
    <groupId>dev.langchain4j</groupId>
    <artifactId>langchain4j-community-bom</artifactId>
    <version>${langchain4j-community.version}</version>
    <type>pom</type>
    <scope>import</scope>
</dependency>

<?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">
    <modelVersion>4.0.0</modelVersion>
    <parent>
        <groupId>com.hk</groupId>
        <artifactId>langcChain4J-study</artifactId>
        <version>1.0-SNAPSHOT</version>
    </parent>
    <artifactId>langChain4j-05chatimage</artifactId>
    <properties>
        <maven.compiler.source>21</maven.compiler.source>
        <maven.compiler.target>21</maven.compiler.target>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    </properties>
    <dependencies>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-web</artifactId>
        </dependency>
        <!--langchain4j-open-ai 基础-->
        <!--所有调用均基于 OpenAI 协议标准，实现一致的接口设计与规范 LangChain4j 提供与许多 LLM 提供商的集成 从最简单的开始方式是从 OpenAI 集成开始 https://docs.langchain4j.dev/get-started -->
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j-open-ai</artifactId>
        </dependency>
        <!--langchain4j 高阶-->
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j</artifactId>
        </dependency>
        <!--DashScope (Qwen) 接入阿里云百炼平台 https://docs.langchain4j.dev/integrations/language-models/dashscope -->
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j-community-dashscope-spring-boot-starter</artifactId>
        </dependency>
        <!--lombok-->
        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
            <optional>true</optional>
        </dependency>
        <!--hutool-->
        <dependency>
            <groupId>cn.hutool</groupId>
            <artifactId>hutool-all</artifactId>
            <version>5.8.22</version>
        </dependency>
        <!--test-->
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-test</artifactId>
            <scope>test</scope>
        </dependency>
    </dependencies>
    <build>
        <plugins>
            <plugin>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-maven-plugin</artifactId>
            </plugin>
        </plugins>
    </build>
</project>

server.port=8005
spring.application.name=langchain4j-05chatimage

@Configuration
public class LLMConfig {
    @Bean
    public WanxImageModel wanxImageModel() {
        return WanxImageModel.builder()
                .apiKey(System.getenv("aliQwen-api"))
                .modelName("wanx2.1-t2i-turbo")
                .build();
    }
}

@RestController
public class ImageModelController {
    @Resource
    private WanxImageModel wanxImageModel;

    @GetMapping("/chat/image-1")
    public String image1() {
        Response<Image> generate = wanxImageModel.generate("一张图，描述：一个人在沙滩上");
        return generate.content().url().toString();
    }

    @GetMapping("/chat/image-2")
    public String image2() throws NoApiKeyException {
        String prompt = "近景镜头，18 岁的中国女孩，古代服饰，圆脸，正面看着镜头，" +
                "民族优雅的服装，商业摄影，室外，电影级光照，半身特写，精致的淡妆，锐利的边缘。";
        ImageSynthesisParam build = ImageSynthesisParam.builder()
                .apiKey(System.getenv("aliQwen-api"))
                .model("wanx2.1-t2i-turbo")
                .prompt(prompt)
                .n(2)
                .size("1024*1024")
                .build();
        ImageSynthesis imageSynthesis = new ImageSynthesis();
        ImageSynthesisResult result = imageSynthesis.call(build);
        return JsonUtils.toJson(result);
    }
}

<?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">
    <modelVersion>4.0.0</modelVersion>
    <parent>
        <groupId>com.hk</groupId>
        <artifactId>langcChain4J-study</artifactId>
        <version>1.0-SNAPSHOT</version>
    </parent>
    <artifactId>langChain4j-06chatstream</artifactId>
    <properties>
        <maven.compiler.source>21</maven.compiler.source>
        <maven.compiler.target>21</maven.compiler.target>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    </properties>
    <dependencies>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-web</artifactId>
        </dependency>
        <!--langchain4j-open-ai + langchain4j + langchain4j-reactor-->
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j-open-ai</artifactId>
        </dependency>
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j</artifactId>
        </dependency>
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j-reactor</artifactId>
        </dependency>
        <!--lombok-->
        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
            <optional>true</optional>
        </dependency>
        <!--hutool-->
        <dependency>
            <groupId>cn.hutool</groupId>
            <artifactId>hutool-all</artifactId>
            <version>5.8.22</version>
        </dependency>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-test</artifactId>
            <scope>test</scope>
        </dependency>
    </dependencies>
    <build>
        <plugins>
            <plugin>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-maven-plugin</artifactId>
            </plugin>
        </plugins>
    </build>
</project>

server.port=8006
spring.application.name=langchain4j-06chat-stream
# 设置响应的字符编码，避免流式返回输出乱码
server.servlet.encoding.charset=utf-8
server.servlet.encoding.enabled=true
server.servlet.encoding.force=true

public interface ChatAssistant {
    Flux<String> chat(String prompt);
}

@Configuration
public class LLMConfig {
    @Bean
    public StreamingChatModel streamingChatModel() {
        return OpenAiStreamingChatModel.builder()
                .apiKey(System.getenv("aliQwen-api"))
                .modelName("qwen-plus")
                .baseUrl("https://dashscope.aliyuncs.com/compatible-mode/v1")
                .build();
    }

    @Bean
    public ChatAssistant chatAssistant(StreamingChatModel streamingChatModel) {
        return AiServices.create(ChatAssistant.class, streamingChatModel);
    }
}

@RestController
public class StreamingChatModelController {
    @Resource
    private StreamingChatModel streamingChatModel;

    @Resource
    private ChatAssistant chatAssistant;

    // 方式一：使用 Flux.create 手动创建 Flux
    @GetMapping("/chat1")
    public Flux<String> chat1(String msg) {
        return Flux.create(fluxSink -> {
            streamingChatModel.chat(msg, new StreamingChatResponseHandler() {
                @Override
                public void onPartialResponse(String s) {
                    System.out.println(s);
                    fluxSink.next(s);
                }

                @Override
                public void onCompleteResponse(ChatResponse chatResponse) {
                    System.out.println("---response over: " + chatResponse);
                    fluxSink.complete();
                }

                @Override
                public void onError(Throwable throwable) {
                    fluxSink.error(throwable);
                }
            });
        });
    }

    // 方式二
    @GetMapping("/chat2")
    public Flux<String> chat2(String msg) {
        return chatAssistant.chat(msg);
    }
}

<?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">
    <modelVersion>4.0.0</modelVersion>
    <parent>
        <groupId>com.hk</groupId>
        <artifactId>langcChain4J-study</artifactId>
        <version>1.0-SNAPSHOT</version>
    </parent>
    <artifactId>langChain4j-07chatmemory</artifactId>
    <properties>
        <maven.compiler.source>21</maven.compiler.source>
        <maven.compiler.target>21</maven.compiler.target>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    </properties>
    <dependencies>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-web</artifactId>
        </dependency>
        <!--langchain4j-open-ai + langchain4j + langchain4j-reactor-->
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j-open-ai</artifactId>
        </dependency>
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j</artifactId>
        </dependency>
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j-reactor</artifactId>
        </dependency>
        <!--lombok-->
        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
            <optional>true</optional>
        </dependency>
        <!--hutool-->
        <dependency>
            <groupId>cn.hutool</groupId>
            <artifactId>hutool-all</artifactId>
            <version>5.8.22</version>
        </dependency>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-test</artifactId>
            <scope>test</scope>
        </dependency>
    </dependencies>
    <build>
        <plugins>
            <plugin>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-maven-plugin</artifactId>
            </plugin>
        </plugins>
    </build>
</project>

server.port=8007
spring.application.name=langchain4j-07chat-memory
# 设置响应的字符编码
server.servlet.encoding.charset=utf-8
server.servlet.encoding.enabled=true
server.servlet.encoding.force=true

public interface ChatMemoryAssistant {
    /**
     * 聊天带记忆缓存功能
     *
     * @param userId 用户 ID
     * @param prompt 消息
     * @return String
     */
    String chatWithChatMemory(@MemoryId Long userId, @UserMessage String prompt);
}

@Configuration
public class LLMConfig {
    @Bean
    public ChatModel chatModel() {
        return OpenAiChatModel.builder()
                .apiKey(System.getenv("aliQwen-api"))
                .modelName("qwen-long")
                .baseUrl("https://dashscope.aliyuncs.com/compatible-mode/v1")
                .build();
    }

    @Bean("chatMessageWindowChatMemory")
    public ChatMemoryAssistant chatMessageWindowChatMemory(ChatModel chatModel) {
        return AiServices.builder(ChatMemoryAssistant.class)
                .chatModel(chatModel)
                // 每个 memoryId 对应创建一个 ChatMemory
                .chatMemoryProvider(memoryId -> MessageWindowChatMemory.withMaxMessages(20))
                .build();
    }

    @Bean
    public ChatMemoryAssistant chatTokenWindowChatMemory(ChatModel chatModel) {
        // TokenCountEstimator 默认的 token 分词器，需要结合 Tokenizer 计算 ChatMessage 的 token 数量
        OpenAiTokenCountEstimator openAiTokenCountEstimator = new OpenAiTokenCountEstimator("gpt-4");
        return AiServices.builder(ChatMemoryAssistant.class)
                .chatModel(chatModel)
                // 每个 memoryId 对应创建一个 ChatMemory
                .chatMemoryProvider(memoryId -> TokenWindowChatMemory.withMaxTokens(100, openAiTokenCountEstimator))
                .build();
    }
}

@RestController
public class ChatMemoryController {
    @Resource(name = "chatMessageWindowChatMemory")
    private ChatMemoryAssistant chatMessageWindowChatMemory;

    @Resource(name = "chatTokenWindowChatMemory")
    private ChatMemoryAssistant chatTokenWindowChatMemory;

    // MessageWindowChatMemory 实现聊天功能
    @GetMapping("/chatv1")
    public void chatv1() {
        chatMessageWindowChatMemory.chatWithChatMemory(1L, "你好！我的名字是 Java.");
        String answer01 = chatMessageWindowChatMemory.chatWithChatMemory(1L, "我的名字是什么");
        System.out.println("answer01 返回结果：" + answer01);
        chatMessageWindowChatMemory.chatWithChatMemory(3L, "你好！我的名字是 C++");
        String answer02 = chatMessageWindowChatMemory.chatWithChatMemory(3L, "我的名字是什么");
        System.out.println("answer02 返回结果：" + answer02);
    }

    // TokenWindowChatMemory 实现聊天功能
    @GetMapping("/chatv2")
    public void chatv2() {
        chatTokenWindowChatMemory.chatWithChatMemory(1L, "你好！我的名字是 Java.");
        String answer01 = chatTokenWindowChatMemory.chatWithChatMemory(1L, "我的名字是什么");
        System.out.println("answer01 返回结果：" + answer01);
        chatTokenWindowChatMemory.chatWithChatMemory(3L, "你好！我的名字是 C++");
        String answer02 = chatTokenWindowChatMemory.chatWithChatMemory(3L, "我的名字是什么");
        System.out.println("answer02 返回结果：" + answer02);
    }
}

<?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">
    <modelVersion>4.0.0</modelVersion>
    <parent>
        <groupId>com.hk</groupId>
        <artifactId>langcChain4J-study</artifactId>
        <version>1.0-SNAPSHOT</version>
    </parent>
    <artifactId>langChain4j-08chatprompt</artifactId>
    <properties>
        <maven.compiler.source>21</maven.compiler.source>
        <maven.compiler.target>21</maven.compiler.target>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    </properties>
    <dependencies>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-web</artifactId>
        </dependency>
        <!--langchain4j-open-ai + langchain4j + langchain4j-reactor-->
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j-open-ai</artifactId>
        </dependency>
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j</artifactId>
        </dependency>
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j-reactor</artifactId>
        </dependency>
        <!--lombok-->
        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
            <optional>true</optional>
        </dependency>
        <!--hutool-->
        <dependency>
            <groupId>cn.hutool</groupId>
            <artifactId>hutool-all</artifactId>
            <version>5.8.22</version>
        </dependency>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-test</artifactId>
            <scope>test</scope>
        </dependency>
    </dependencies>
    <build>
        <plugins>
            <plugin>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-maven-plugin</artifactId>
            </plugin>
        </plugins>
    </build>
</project>

server.port=8008
spring.application.name=langchain4j-08chat-prompt
# 设置响应的字符编码
server.servlet.encoding.charset=utf-8
server.servlet.encoding.enabled=true
server.servlet.encoding.force=true

public interface LawAssistant {
    @SystemMessage("你是一位专业的中国法律顾问，只回答与中国法律相关的问题。" +
            "输出限制：对于其他领域的问题禁止回答，直接返回'抱歉，我只能回答中国法律相关的问题。'")
    @UserMessage("请回答以下法律问题：{{question}},字数控制在{{length}}以内")
    String chat(@V("question") String question, @V("length") int length);
}

@Configuration
public class LLMConfig {
    @Bean
    public ChatModel chatModel() {
        return OpenAiChatModel.builder()
                .apiKey(System.getenv("aliQwen-api"))
                .modelName("qwen-long")
                .baseUrl("https://dashscope.aliyuncs.com/compatible-mode/v1")
                .build();
    }

    @Bean
    public LawAssistant lawAssistant(ChatModel chatModel) {
        return AiServices.create(LawAssistant.class, chatModel);
    }
}

@RestController
public class ChatPromptController {
    @Resource
    private LawAssistant lawAssistant;

    @GetMapping(value = "/chatprompt/test1")
    public void test1() {
        String chat = lawAssistant.chat("什么是知识产权？", 2000);
        System.out.println(chat);
        System.out.println("========================================================");
        String chat2 = lawAssistant.chat("什么是 java？", 2000);
        System.out.println(chat2);
        System.out.println("========================================================");
        String chat3 = lawAssistant.chat("介绍下西瓜和芒果", 2000);
        System.out.println(chat3);
        System.out.println("========================================================");
        String chat4 = lawAssistant.chat("飞机发动机原理", 2000);
        System.out.println(chat4);
    }
}

@Data
@StructuredPrompt("根据中国{{legal}}法律，解答以下问题：{{question}}")
public class LawPrompt {
    private String legal;
    private String question;
}

public interface LawAssistant {
    @SystemMessage("你是一位专业的中国法律顾问，只回答与中国法律相关的问题。" +
            "输出限制：对于其他领域的问题禁止回答，直接返回'抱歉，我只能回答中国法律相关的问题。'")
    @UserMessage("请回答以下法律问题：{{question}},字数控制在{{length}}以内")
    String chat(@V("question") String question, @V("length") int length);

    @SystemMessage("你是一位专业的中国法律顾问，只回答与中国法律相关的问题。" +
            "输出限制：对于其他领域的问题禁止回答，直接返回'抱歉，我只能回答中国法律相关的问题。'")
    String chat(LawPrompt lawPrompt);
}

@RestController
public class ChatPromptController {
    @Resource
    private LawAssistant lawAssistant;

    ......

    @GetMapping(value = "/chatprompt/test2")
    public String test2() {
        LawPrompt prompt = new LawPrompt();
        prompt.setLegal("知识产权");
        prompt.setQuestion("TRIPS 协议？");
        String chat = lawAssistant.chat(prompt);
        System.out.println(chat);
        return chat;
    }
}

@Resource
private ChatModel chatModel;

@GetMapping(value = "/chatprompt/test3")
public String test3() {
    // 默认 PromptTemplate 构造使用 it 属性作为默认占位符
    String role = "财务会计";
    String question = "人民币大写";
    //1 构造 PromptTemplate 模板
    PromptTemplate template = PromptTemplate.from("你是一个{{it}}助手，{{question}}怎么办");
    //2 由 PromptTemplate 生成 Prompt
    Prompt prompt = template.apply(Map.of("it", role, "question", question));
    //3 Prompt 提示词变成 UserMessage
    UserMessage userMessage = prompt.toUserMessage();
    //4 调用大模型
    ChatResponse chatResponse = chatModel.chat(userMessage);
    //4.1 后台打印
    System.out.println(chatResponse.aiMessage().text());
    //4.2 前台返回
    return chatResponse.aiMessage().text();
}

<?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">
    <modelVersion>4.0.0</modelVersion>
    <parent>
        <groupId>com.hk</groupId>
        <artifactId>langcChain4J-study</artifactId>
        <version>1.0-SNAPSHOT</version>
    </parent>
    <artifactId>langChain4j-09chatPersistence</artifactId>
    <properties>
        <maven.compiler.source>21</maven.compiler.source>
        <maven.compiler.target>21</maven.compiler.target>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    </properties>
    <dependencies>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-web</artifactId>
        </dependency>
        <!--langchain4j-open-ai + langchain4j + langchain4j-reactor-->
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j-open-ai</artifactId>
        </dependency>
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j</artifactId>
        </dependency>
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j-reactor</artifactId>
        </dependency>
        <!--spring-boot-starter-data-redis https://docs.langchain4j.dev/tutorials/chat-memory#persistence -->
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-data-redis</artifactId>
        </dependency>
        <!--lombok-->
        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
            <optional>true</optional>
        </dependency>
        <!--hutool-->
        <dependency>
            <groupId>cn.hutool</groupId>
            <artifactId>hutool-all</artifactId>
            <version>5.8.22</version>
        </dependency>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-test</artifactId>
            <scope>test</scope>
        </dependency>
    </dependencies>
    <build>
        <plugins>
            <plugin>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-maven-plugin</artifactId>
            </plugin>
        </plugins>
    </build>
</project>

server.port=8009
spring.application.name=langchain4j-09chat-persistence
# 设置响应的字符编码
server.servlet.encoding.charset=utf-8
server.servlet.encoding.enabled=true
server.servlet.encoding.force=true
# ==========config redis===============
spring.data.redis.host=localhost
spring.data.redis.port=6379
spring.data.redis.password=12345
spring.data.redis.database=0
spring.data.redis.connect-timeout=3s
spring.data.redis.timeout=2s

public interface ChatPersistenceAssistant {
    String chat(@MemoryId Long userId, @UserMessage String message);
}

@Configuration
public class RedisConfig {
    @Bean
    public RedisTemplate<String, Object> redisTemplate(RedisConnectionFactory redisConnectionFactory) {
        RedisTemplate<String, Object> template = new RedisTemplate<>();
        template.setConnectionFactory(redisConnectionFactory);
        //设置 key 序列化方式 string
        template.setKeySerializer(new StringRedisSerializer());
        //设置 value 序列化方式 json
        template.setDefaultSerializer(new GenericJackson2JsonRedisSerializer());
        template.setHashKeySerializer(new StringRedisSerializer());
        template.setHashValueSerializer(new GenericJackson2JsonRedisSerializer());
        template.setEnableTransactionSupport(true);
        template.afterPropertiesSet();
        return template;
    }
}

@Component
public class RedisChatMemoryStore implements ChatMemoryStore {
    private static final String CHAT_MEMORY_KEY_PREFIX = "chat_memory:";

    @Resource
    private RedisTemplate<String, String> redisTemplate;

    @Override
    public List<ChatMessage> getMessages(Object memoryId) {
        String messages = redisTemplate.opsForValue().get(CHAT_MEMORY_KEY_PREFIX + memoryId);
        return ChatMessageDeserializer.messagesFromJson(messages);
    }

    @Override
    public void updateMessages(Object memoryId, List<ChatMessage> list) {
        redisTemplate.opsForValue().set(CHAT_MEMORY_KEY_PREFIX + memoryId, ChatMessageSerializer.messagesToJson(list));
    }

    @Override
    public void deleteMessages(Object memoryId) {
        redisTemplate.delete(CHAT_MEMORY_KEY_PREFIX + memoryId);
    }
}

@Configuration
public class LLMConfig {
    @Resource
    private RedisChatMemoryStore redisChatMemoryStore;

    @Bean
    public ChatModel chatModel() {
        return OpenAiChatModel.builder()
                .apiKey(System.getenv("aliQwen-api"))
                .modelName("qwen-plus")
                .baseUrl("https://dashscope.aliyuncs.com/compatible-mode/v1")
                .build();
    }

    @Bean
    public ChatPersistenceAssistant chatPersistenceAssistant(ChatModel chatModel) {
        ChatMemoryProvider chatMemoryProvider = memoryId -> MessageWindowChatMemory.builder()
                .id(memoryId)
                .maxMessages(10)
                .chatMemoryStore(redisChatMemoryStore)
                .build();
        return AiServices.builder(ChatPersistenceAssistant.class)
                .chatModel(chatModel)
                .chatMemoryProvider(chatMemoryProvider)
                .build();
    }
}

@RestController
public class ChatPersistenceController {
    @Resource
    private ChatPersistenceAssistant chatPersistenceAssistant;

    @GetMapping("/chat")
    public void chat() {
        chatPersistenceAssistant.chat(1L, "你好！我的名字是 redis");
        chatPersistenceAssistant.chat(2L, "你好！我的名字是 nacos");
        String chat = chatPersistenceAssistant.chat(1L, "我的名字是什么");
        System.out.println(chat);
        System.out.println("=====================================================");
        chat = chatPersistenceAssistant.chat(2L, "我的名字是什么");
        System.out.println(chat);
    }
}

<?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">
    <modelVersion>4.0.0</modelVersion>
    <parent>
        <groupId>com.hk</groupId>
        <artifactId>langcChain4J-study</artifactId>
        <version>1.0-SNAPSHOT</version>
    </parent>
    <artifactId>langChain4j-10chatFunctionCalling</artifactId>
    <properties>
        <maven.compiler.source>21</maven.compiler.source>
        <maven.compiler.target>21</maven.compiler.target>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    </properties>
    <dependencies>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-web</artifactId>
        </dependency>
        <!--langchain4j-open-ai-->
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j-open-ai</artifactId>
        </dependency>
        <!--langchain4j-->
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j</artifactId>
        </dependency>
        <!--langchain4j-reactor-->
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j-reactor</artifactId>
        </dependency>
        <!--httpclient5-->
        <dependency>
            <groupId>org.apache.httpcomponents.client5</groupId>
            <artifactId>httpclient5</artifactId>
            <version>5.5</version>
        </dependency>
        <!--lombok-->
        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
            <optional>true</optional>
        </dependency>
        <!--hutool-->
        <dependency>
            <groupId>cn.hutool</groupId>
            <artifactId>hutool-all</artifactId>
            <version>5.8.22</version>
        </dependency>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-test</artifactId>
            <scope>test</scope>
        </dependency>
    </dependencies>
    <build>
        <plugins>
            <plugin>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-maven-plugin</artifactId>
            </plugin>
        </plugins>
    </build>
</project>

server.port=8010
spring.application.name=langchain4j-10chat-functioncalling

public interface FunctionAssistant {
    String chat(String message);
}

@Configuration
public class LLMConfig {
    @Bean
    public ChatModel chatModel() {
        return OpenAiChatModel.builder()
                .apiKey(System.getenv("aliQwen-api"))
                .modelName("qwen-plus")
                .baseUrl("https://dashscope.aliyuncs.com/compatible-mode/v1")
                .build();
    }

    // 低阶工具 Api
    @Bean
    public FunctionAssistant functionAssistant(ChatModel chatModel) {
        ToolSpecification toolSpecification = ToolSpecification.builder()
                .name("开局发票助手")
                .description("根据用户提交的开票信息，开具发票")
                .parameters(JsonObjectSchema.builder()
                        .addStringProperty("companyName", "公司名称")
                        .addStringProperty("dutyNumber", "税号序列")
                        .addStringProperty("amount", "开票金额，保留两位有效数字")
                        .build())
                .build();
        ToolExecutor toolExecutor = (toolExecutionRequest, memoryId) -> {
            System.out.println("toolExecutionRequest=====" + toolExecutionRequest.id());
            System.out.println("toolExecutionRequest=====" + toolExecutionRequest.name());
            String arguments = toolExecutionRequest.arguments();
            System.out.println("toolExecutionRequest=====" + arguments);
            return "发票已开具";
        };
        return AiServices.builder(FunctionAssistant.class)
                .chatModel(chatModel)
                .tools(Map.of(toolSpecification, toolExecutor))
                .build();
    }
}

@RestController
public class ChatFunctionCallingController {
    @Resource
    private FunctionAssistant functionAssistant;

    @GetMapping("/chat")
    public void chat() {
        String msg = "开张发票，公司：尚硅谷教育科技有限公司 税号：zfdehtrhrt533 金额：668.12";
        String chat = functionAssistant.chat(msg);
        System.out.println("ok:" + chat);
    }
}

@Service
public class WeatherService {
    private static final String WEATHER_API_URL = "https://nXXXX.qweatherapi.com/v7/weather/now?location=%s&key=%s";

    public JsonNode getWeather(String location) throws JsonProcessingException {
        String url = String.format(WEATHER_API_URL, location, "XXXXXX");
        // 发送 HTTP 请求并解析响应
        CloseableHttpClient httpClient = HttpClients.createDefault();
        // 这里省略具体实现，假设使用 RestTemplate 发送 GET 请求并返回 JsonNode
        HttpComponentsClientHttpRequestFactory requestFactory = new HttpComponentsClientHttpRequestFactory(httpClient);
        // 配置 RestTemplate 使用 HttpComponentsClientHttpRequestFactory
        RestTemplate restTemplate = new RestTemplate(requestFactory);
        // 发送 GET 请求并获取响应
        String response = restTemplate.getForObject(url, String.class);
        // 解析响应体为 JsonNode
        JsonNode jsonNode = new ObjectMapper().readTree(response);
        return jsonNode;
    }
}

public class InvoiceHandler {
    @Tool("获取天气信息")
    public String handle(@P("天气状况") String text, @P("风向") String windDir) throws Exception {
        System.out.println("天气状况：" + text + " 风向：" + windDir);
        //----------------------------------
        // 自己的业务逻辑，调用 redis/rabbitmq/kafka/mybatis/顺丰单据/医疗化验报告/支付接口等第 3 方
        //----------------------------------
        System.out.println(new WeatherService().getWeather("101010100"));
        return "获取成功";
    }
}

@Configuration
public class LLMConfig {
    @Bean
    public ChatModel chatModel() {
        return OpenAiChatModel.builder()
                .apiKey(System.getenv("aliQwen-api"))
                .modelName("qwen-plus")
                .baseUrl("https://dashscope.aliyuncs.com/compatible-mode/v1")
                .build();
    }

    // 低阶工具 Api
    @Bean("lowfunction")
    public FunctionAssistant functionAssistant(ChatModel chatModel) {
        ToolSpecification toolSpecification = ToolSpecification.builder()
                .name("开局发票助手")
                .description("根据用户提交的开票信息，开具发票")
                .parameters(JsonObjectSchema.builder()
                        .addStringProperty("companyName", "公司名称")
                        .addStringProperty("dutyNumber", "税号序列")
                        .addStringProperty("amount", "开票金额，保留两位有效数字")
                        .build())
                .build();
        ToolExecutor toolExecutor = (toolExecutionRequest, memoryId) -> {
            System.out.println("toolExecutionRequest=====" + toolExecutionRequest.id());
            System.out.println("toolExecutionRequest=====" + toolExecutionRequest.name());
            String arguments = toolExecutionRequest.arguments();
            System.out.println("toolExecutionRequest=====" + arguments);
            return "发票已开具";
        };
        return AiServices.builder(FunctionAssistant.class)
                .chatModel(chatModel)
                .tools(Map.of(toolSpecification, toolExecutor))
                .build();
    }

    // 高阶工具 Api
    @Bean("highfunction")
    public FunctionAssistant highFunctionAssistant(ChatModel chatModel) {
        return AiServices.builder(FunctionAssistant.class)
                .chatModel(chatModel)
                .tools(new InvoiceHandler())
                .build();
    }
}

@RestController
public class ChatFunctionCallingController {
    // @Resource(name = "lowfunction")
    // private FunctionAssistant functionAssistant;
    @Resource(name = "highfunction")
    private FunctionAssistant highFunctionAssistant;

    // @GetMapping("/chat")
    // public void chat() {
    //     String msg = "开张发票，公司：尚硅谷教育科技有限公司 税号：zfdehtrhrt533 金额：668.12";
    //     String chat = functionAssistant.chat(msg);
    //     System.out.println("ok:" + chat);
    // }
    @GetMapping("/chat2")
    public void chat2() {
        String chat = highFunctionAssistant.chat("北京今天的天气");
        System.out.println("ok:" + chat);
    }
}

LangChain4J Java 集成指南：从入门到高级应用

1、介绍

2、入门案例

（1）LangChain4J 支持的语言模型

（2）获取百炼平台信息

1）获取 Key

2）获取模型名称

3）获取 baseUrl

（3）创建父工程

1）创建工程

2）修改 pom 文件

（4）建立第一个案例模块

1）新建模块

2）修改 pom 文件

3）添加配置文件

4）添加配置类

5）编写业务类

6）测试

（5）多模型共存 (deepseek)

1）获取 Key

2）获取模型名称

3）获取 baseUrl

（6）修改工程

1）修改配置类

2）修改业务类

3）测试

3、与 springBoot 整合

（1）了解

（2）案例实现

1）新建模块

2）修改 pom 文件

3）添加配置文件

4）低阶 Api 业务类

5）自定义接口类

6）高阶 Api 业务类

7）测试

4、低阶 Api 和高阶 Api

（1）介绍

（2）案例实现

1）新建模块

2）修改 pom 文件

3）添加配置文件

4）添加配置类

5）低阶 api 调用业务类

6）测试低阶 api 调用

7）修改业务类获取 Token 调用

8）高阶 api 调用

1、定义 AiServices 接口

2、修改配置类

3、业务类

9）测试高阶 api

5、模型的参数配置

（1）日志配置

1）修改配置类

2）修改配置文件

3）测试

（2）监控配置

1）编写监听类

2）修改配置类

3）测试

（3）重试机制

1）修改配置类

2）测试

（4）超时机制

1）修改配置类

2）测试

6、多模态视觉

（1）出处

（2）图形理解案例实现

1）创建模块

2）修改 pom

3）添加配置文件

4）添加配置类

5）编写业务类

6）测试

（3）引入第三方案例实现

0）修改父工程 pom 文件

1）创建模块

2）修改 pom

3）添加配置文件