人工智能机器学习自然语言处理神经网络生成对抗网络 java AIGC盛行，带你轻松调用开发

文章目录

前言一、AIGC简介二、开通体验开通模型获取API-KEY

三、基于java实现调用1.设置API-KEY2.体验大语言模型多轮对话演示补充流式输出

3.体验通义千问VL使用官方提供照片本地文件多轮对话流式输出

总结

前言

本篇文章基于java和阿里云的通义千问大模型手把手带你使用AIGC开发，实现文本对话和图像分析。

一、AIGC简介

你知道什么是AIGC吗？不知道？没关系，我来告诉你：

AIGC就是由AI自动创作生成的内容（AI Generated Content），比如图片、视频、音乐、文字等。AIGC就像一支神奇的画笔，拥有无限的创造力。这支画笔的特别之处在于，它是由AI打造的。AI利用它的理解力、想象力和创作力，根据指定的需求和风格，创作出各种内容：文章、短篇小说、报告、音乐、图像，甚至是视频。AIGC的出现，打开了一个全新的创作世界，为人们提供了无数的可能性。AI，就是人工智能。它的目标是让机器能够像人一样有智能，能够看、听、说、想、做。要实现这个目标，AI需要用到重要的技术：深度学习、NLP（自然语言处理）、神经网络和生成式对抗网络（GAN）。

️通过上面的讲诉，无论你曾经不知道还是模棱两可，现在应该大概了解了，下面带你走进AIGC，用程序员的身份打开AIGC。

二、开通体验

开通模型获取API-KEY

大家不要害怕开通不会产生收费，本文讲述的完全是免费就可使用的方法。

登录阿里云进入控制台后，鼠标移到下图位置

然后出现如下界面，找到人工智能与机器学习下的模型服务灵积，点击

参照开发文档，开通DashScope并创建API-KEY

总结文档上的开通步骤如下：

在控制台中点击总览，去开通

立开通（大家不要怕，这是不会产生扣费的）开通后，点击管理中心的 API-KEY 菜单项，然后创建新的API-KEY 就会有个Accesskeyid和Secret值（这俩值要记住真正的开发中有用，本文章没用到）的弹窗，然后点击已创建的AIP-KEY查看并复制，这个会用到。

三、基于java实现调用

打开IDEA，开始操作了

1.设置API-KEY

先了解以下如何设置API-KEY值的：

import com.alibaba.dashscope.utils.Constants;

Constants.apiKey="这就是你的API-KEY的值（上面复制的）";

2.体验大语言模型

多轮对话演示

创建一个测试类：代码如下：

import com.alibaba.dashscope.aigc.generation.Generation;

import com.alibaba.dashscope.aigc.generation.GenerationResult;

import com.alibaba.dashscope.aigc.generation.models.QwenParam;

import com.alibaba.dashscope.common.Message;

import com.alibaba.dashscope.common.MessageManager;

import com.alibaba.dashscope.common.Role;

import com.alibaba.dashscope.exception.ApiException;

import com.alibaba.dashscope.exception.InputRequiredException;

import com.alibaba.dashscope.exception.NoApiKeyException;

import com.alibaba.dashscope.utils.Constants;

import com.alibaba.dashscope.utils.JsonUtils;

import org.mockito.internal.matchers.Contains;

import java.awt.*;

class test {

public static void callWithMessage()

throws NoApiKeyException, ApiException, InputRequiredException {

// 设置API-KEY值

Constants.apiKey="你的API-KEY值";

Generation gen = new Generation();

MessageManager msgManager = new MessageManager(10);

Message systemMsg =

Message.builder().role(Role.SYSTEM.getValue()).content("You are a helpful assistant.").build();//告知模型他是个助手（设置角色）

Message userMsg = Message.builder().role(Role.USER.getValue()).content("你好，周末去哪里玩？").build();//对话问题

msgManager.add(systemMsg);

msgManager.add(userMsg);

QwenParam param =

QwenParam.builder().model(Generation.Models.QWEN_PLUS).messages(msgManager.get())

.resultFormat(QwenParam.ResultFormat.MESSAGE)

.topP(0.8)

.enableSearch(true)

.build();

GenerationResult result = gen.call(param);

System.out.println(result);//输出回复

msgManager.add(result);

System.out.println(JsonUtils.toJson(result));//JSON格式输出回复

param.setPrompt("找个近点的");//继续问题

param.setMessages(msgManager.get());

result = gen.call(param);

System.out.println(result);

System.out.println(JsonUtils.toJson(result));

}

public static void main(String[] args){

try {

callWithMessage();

} catch (ApiException | NoApiKeyException | InputRequiredException e) {

System.out.println(e.getMessage());

}

System.exit(0);

}

上诉代码就是向模型提问周末去哪玩，模型给出回复后，又继续说让他说个近点的地方

补充流式输出

import java.util.Arrays;

import java.util.concurrent.Semaphore;

import com.alibaba.dashscope.aigc.generation.Generation;

import com.alibaba.dashscope.aigc.generation.GenerationResult;

import com.alibaba.dashscope.aigc.generation.models.QwenParam;

import com.alibaba.dashscope.common.Message;

import com.alibaba.dashscope.common.ResultCallback;

import com.alibaba.dashscope.common.Role;

import com.alibaba.dashscope.exception.ApiException;

import com.alibaba.dashscope.exception.InputRequiredException;

import com.alibaba.dashscope.exception.NoApiKeyException;

import com.alibaba.dashscope.utils.JsonUtils;

import io.reactivex.Flowable;

import com.alibaba.dashscope.utils.Constants;

public class Main {

public static void streamCallWithMessage()

throws NoApiKeyException, ApiException, InputRequiredException {

Constants.apiKey="你的API-KEY值";

Generation gen = new Generation();

Message userMsg = Message

.builder()

.role(Role.USER.getValue())

.content("如何做西红柿炖牛腩？")

.build();

QwenParam param =

QwenParam.builder().model(Generation.Models.QWEN_PLUS).messages(Arrays.asList(userMsg))

.resultFormat(QwenParam.ResultFormat.MESSAGE)

.topP(0.8)

.enableSearch(true)

.incrementalOutput(true) // get streaming output incrementally

.build();

Flowable result = gen.streamCall(param);

StringBuilder fullContent = new StringBuilder();

result.blockingForEach(message -> {

fullContent.append(message.getOutput().getChoices().get(0).getMessage().getContent());

System.out.println(JsonUtils.toJson(message));

});

System.out.println("Full content: \n" + fullContent.toString());

}

public static void streamCallWithCallback()

throws NoApiKeyException, ApiException, InputRequiredException,InterruptedException {

Generation gen = new Generation();

Message userMsg = Message

.builder()

.role(Role.USER.getValue())

.content("如何做西红柿炖牛腩？")

.build();

QwenParam param = QwenParam

.builder()

.model(Generation.Models.QWEN_PLUS)

.resultFormat(QwenParam.ResultFormat.MESSAGE)

.messages(Arrays.asList(userMsg))

.topP(0.8)

.incrementalOutput(true) // get streaming output incrementally

.build();

Semaphore semaphore = new Semaphore(0);

StringBuilder fullContent = new StringBuilder();

gen.streamCall(param, new ResultCallback() {

@Override

public void onEvent(GenerationResult message) {

fullContent.append(message.getOutput().getChoices().get(0).getMessage().getContent());

System.out.println(message);

}

@Override

public void onError(Exception err){

System.out.println(String.format("Exception: %s", err.getMessage()));

semaphore.release();

}

@Override

public void onComplete(){

System.out.println("Completed");

semaphore.release();

}

});

semaphore.acquire();

System.out.println("Full content: \n" + fullContent.toString());

}

public static void main(String[] args) {

try {

streamCallWithMessage();

} catch (ApiException | NoApiKeyException | InputRequiredException e) {

System.out.println(e.getMessage());

}

try {

streamCallWithCallback();

} catch (ApiException | NoApiKeyException | InputRequiredException | InterruptedException e) {

System.out.println(e.getMessage());

}

System.exit(0);

}

3.体验通义千问VL

下面使用接口实现图片解析

使用官方提供照片

首先大家看一下官方提供的图片：

/**

* @Version: 1.0.0

* @Author: Dragon_王

* @ClassName: test1

* @Description: TODO描述

* @Date: 2023/12/28 17:41

import java.util.Arrays;

import java.util.Collections;

import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversation;

import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationParam;

import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationResult;

import com.alibaba.dashscope.common.MultiModalMessage;

import com.alibaba.dashscope.common.Role;

import com.alibaba.dashscope.exception.ApiException;

import com.alibaba.dashscope.exception.NoApiKeyException;

import com.alibaba.dashscope.exception.UploadFileException;

import com.alibaba.dashscope.utils.Constants;

class test1 {

public static void simpleMultiModalConversationCall()

throws ApiException, NoApiKeyException, UploadFileException {

Constants.apiKey="你的api-key";

MultiModalConversation conv = new MultiModalConversation();

MultiModalMessage userMessage = MultiModalMessage.builder().role(Role.USER.getValue())

.content(Arrays.asList(Collections.singletonMap("image", "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"),

Collections.singletonMap("text", "这是什么?"))).build();// 对话的问题

MultiModalConversationParam param = MultiModalConversationParam.builder()

.model(MultiModalConversation.Models.QWEN_VL_PLUS)

.message(userMessage)

.build();

MultiModalConversationResult result = conv.call(param);

System.out.println(result);

}

public static void main(String[] args) {

try {

simpleMultiModalConversationCall();

} catch (ApiException | NoApiKeyException | UploadFileException e) {

System.out.println(e.getMessage());

}

System.exit(0);

}

本地文件

import java.util.Arrays;

import java.util.HashMap;

import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversation;

import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationParam;

import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationResult;

import com.alibaba.dashscope.common.MultiModalMessage;

import com.alibaba.dashscope.common.Role;

import com.alibaba.dashscope.exception.ApiException;

import com.alibaba.dashscope.exception.NoApiKeyException;

import com.alibaba.dashscope.exception.UploadFileException;

import io.reactivex.Flowable;

import com.alibaba.dashscope.utils.Constants;

public class MultiModalConversationLocalFile2 {

/**

* sample of use local file

* Windows file format: file:///D:/test/images/test.png

* Linux & Mac format: file://The_absolute_local_path

public static void callWithLocalFile()

throws ApiException, NoApiKeyException, UploadFileException {

Constants.apiKey="你的api-key";

String localFilePath = "file://The_file_absolute_path";

MultiModalConversation conv = new MultiModalConversation();

// must create mutable map.

MultiModalMessage userMessage = MultiModalMessage.builder().role(Role.USER.getValue())

.content(Arrays.asList(new HashMap(){{put("image", localFilePath);}},

new HashMap(){{put("text", "这是什么?");}})).build();// 对话问题

MultiModalConversationParam param = MultiModalConversationParam.builder()

.model(MultiModalConversation.Models.QWEN_VL_PLUS)

.message(userMessage)

.build();

Flowable result = conv.streamCall(param);

result.blockingForEach(item -> {

System.out.println(item);

});

}

public static void main(String[] args) {

try {

callWithLocalFile();

} catch (ApiException | NoApiKeyException | UploadFileException e) {

System.out.println(e.getMessage());

}

System.exit(0);

}

多轮对话

import java.util.ArrayList;

import java.util.Arrays;

import java.util.Collections;

import java.util.List;

import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversation;

import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationParam;

import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationResult;

import com.alibaba.dashscope.common.MultiModalMessage;

import com.alibaba.dashscope.common.Role;

import com.alibaba.dashscope.exception.ApiException;

import com.alibaba.dashscope.exception.NoApiKeyException;

import com.alibaba.dashscope.exception.UploadFileException;

import com.alibaba.dashscope.utils.Constants;

public class Main {

private static final String modelName = "qwen-vl-plus";

public static void MultiRoundConversationCall() throws ApiException, NoApiKeyException, UploadFileException {

Constants.apiKey="你的api-key";

MultiModalConversation conv = new MultiModalConversation();

MultiModalMessage systemMessage = MultiModalMessage.builder().role(Role.SYSTEM.getValue())

.content(Arrays.asList(Collections.singletonMap("text", "You are a helpful assistant."))).build();

MultiModalMessage userMessage = MultiModalMessage.builder().role(Role.USER.getValue())

.content(Arrays.asList(Collections.singletonMap("image", "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"),

Collections.singletonMap("text", "图片里有什么动物?"))).build();// 第一个对话问题

List messages = new ArrayList<>();

messages.add(systemMessage);

messages.add(userMessage);

MultiModalConversationParam param = MultiModalConversationParam.builder()

.model(MultiModalConversationUsage2.modelName)

.messages(messages)

.build();

MultiModalConversationResult result = conv.call(param);

System.out.println(result);

// add the result to conversation

messages.add(result.getOutput().getChoices().get(0).getMessage());

MultiModalMessage msg = MultiModalMessage.builder().role(Role.USER.getValue())

.content(Arrays.asList(Collections.singletonMap("text", "图片动物是什么？"))).build();// 第二个对话问题

messages.add(msg);

// new messages

param.setMessages((List)messages);

result = conv.call(param);

System.out.print(result);

}

public static void main(String[] args) {

try {

MultiRoundConversationCall();

} catch (ApiException | NoApiKeyException | UploadFileException e) {

System.out.println(e.getMessage());

}

System.exit(0);

流式输出

只是输出采用的方式不一样

import java.util.Arrays;

import java.util.HashMap;

import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversation;

import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationParam;

import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationResult;

import com.alibaba.dashscope.common.MultiModalMessage;

import com.alibaba.dashscope.common.Role;

import com.alibaba.dashscope.exception.ApiException;

import com.alibaba.dashscope.exception.NoApiKeyException;

import com.alibaba.dashscope.exception.UploadFileException;

import io.reactivex.Flowable;

import com.alibaba.dashscope.utils.Constants;

public class MultiModalConversationStream {

public static void streamCall()

throws ApiException, NoApiKeyException, UploadFileException {

Constants.apiKey="你的api-key";

MultiModalConversation conv = new MultiModalConversation();

// must create mutable map.

MultiModalMessage userMessage = MultiModalMessage.builder().role(Role.USER.getValue())

.content(Arrays.asList(new HashMap(){{put("image", "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg");}},

new HashMap(){{put("text", "基于这幅图，讲一个故事");}})).build();

MultiModalConversationParam param = MultiModalConversationParam.builder()

.model(MultiModalConversation.Models.QWEN_VL_PLUS)

.message(userMessage)

.build();

Flowable result = conv.streamCall(param);

result.blockingForEach(item -> {

System.out.println(item);

});

}

public static void main(String[] args) {

try {

streamCall();

} catch (ApiException | NoApiKeyException | UploadFileException e) {

System.out.println(e.getMessage());

}

System.exit(0);

}

总结

上面就是使用java调用通义千问大模型的案例，上诉代码都可以运行，如果想改变问题，就将对话问题修改就行。如果再自己写一个UI界面的话，你就拥有了自己的AIGC了（虽然是调用的API️）。

好文阅读

评论可见，请评论后查看内容，谢谢！！！

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金钥匙

人工智能机器学习自然语言处理神经网络生成对抗网络 java AIGC盛行，带你轻松调用开发

人工智能【AIGC使用教程】GitHub Copilot 免费注册及在 PyCharm 中的安装使用

模型水印水印溯源功能隐藏安全创意抄袭会议记录｜AIGC 研究讨论会相关内容记录

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金钥匙

人工智能 机器学习 自然语言处理 神经网络 生成对抗网络 java AIGC盛行，带你轻松调用开发

人工智能 【AIGC使用教程】GitHub Copilot 免费注册及在 PyCharm 中的安装使用

模型水印 水印 溯源 功能隐藏 安全 创意抄袭 会议记录｜AIGC 研究讨论会相关内容记录

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人工智能机器学习自然语言处理神经网络生成对抗网络 java AIGC盛行，带你轻松调用开发

人工智能【AIGC使用教程】GitHub Copilot 免费注册及在 PyCharm 中的安装使用

模型水印水印溯源功能隐藏安全创意抄袭会议记录｜AIGC 研究讨论会相关内容记录