本篇文章为你整理了OpenAI Java SDK——chatgpt（open java perspective）的详细内容，包含有java opencv api open java perspective open java file openjdk javac OpenAI Java SDK——chatgpt，希望能帮助你了解 OpenAI Java SDK——chatgpt。
chatgpt-java是一个OpenAI的Java版SDK，支持开箱即用。目前以支持官网全部Api。支持最新版本GPT-3.5-Turbo模型以及whisper-1模型。增加chat聊天对话以及语音文件转文字，语音翻译。
开源地址：https://github.com/Grt1228/chatgpt-java
导入pom依赖
dependency
groupId com.unfbx /groupId
artifactId chatgpt-java /artifactId
version 1.0.4 /version
/dependency
package com.unfbx.eventTest.test;
import com.unfbx.chatgpt.OpenAiClient;
import com.unfbx.chatgpt.entity.completions.CompletionResponse;
import java.util.Arrays;
public class TestB {
public static void main(String[] args) {
//代理可以为null
Proxy proxy = new Proxy(Proxy.Type.HTTP, new InetSocketAddress("192.168.1.111", 7890));
OpenAiClient openAiClient = OpenAiClient.builder()
.apiKey("sk-**************")
.proxy(proxy)
.build();
//简单模型
//CompletionResponse completions = //openAiClient.completions("我想申请转专业，从计算机专业转到会计学专业，帮我完成一份两百字左右的申请书");
//最新GPT-3.5-Turbo模型
Message message = Message.builder().role(Message.Role.USER).content("你好啊我的伙伴！").build();
ChatCompletion chatCompletion = ChatCompletion.builder().messages(Arrays.asList(message)).build();
ChatCompletionResponse chatCompletionResponse = openAiClient.chatCompletion(chatCompletion);
chatCompletionResponse.getChoices().forEach(e - {
System.out.println(e.getMessage());
支持流式输出
官方对于解决请求缓慢的情况推荐使用流式输出模式。
主要是基于SSE 实现的（可以百度下这个技术）。也是最近在了解到SSE。OpenAI官网在接受Completions接口的时候，有提到过这个技术。 Completion对象本身有一个stream属性，当stream为true时候Api的Response返回就会变成Http长链接。 具体可以看下文档：https://platform.openai.com/docs/api-reference/completions/create
package com.unfbx.chatgpt;
********************
* @author https:www.unfbx.com
* 2023-02-28
public class OpenAiStreamClientTest {
private OpenAiStreamClient client;
@Before
public void before() {
//创建流式输出客户端
Proxy proxy = new Proxy(Proxy.Type.HTTP, new InetSocketAddress("192.168.1.111", 7890));
client = OpenAiStreamClient.builder()
.connectTimeout(50)
.readTimeout(50)
.writeTimeout(50)
.apiKey("sk-******************************")
.proxy(proxy)
.build();
//GPT-3.5-Turbo模型
@Test
public void chatCompletions() {
ConsoleEventSourceListener eventSourceListener = new ConsoleEventSourceListener();
Message message = Message.builder().role(Message.Role.USER).content("你好啊我的伙伴！").build();
ChatCompletion chatCompletion = ChatCompletion.builder().messages(Arrays.asList(message)).build();
client.streamChatCompletion(chatCompletion, eventSourceListener);
CountDownLatch countDownLatch = new CountDownLatch(1);
try {
countDownLatch.await();
} catch (InterruptedException e) {
e.printStackTrace();
//常规对话模型
@Test
public void completions() {
ConsoleEventSourceListener eventSourceListener = new ConsoleEventSourceListener();
Completion q = Completion.builder()
.prompt("我想申请转专业，从计算机专业转到会计学专业，帮我完成一份两百字左右的申请书")
.stream(true)
.build();
client.streamCompletions(q, eventSourceListener);
CountDownLatch countDownLatch = new CountDownLatch(1);
try {
countDownLatch.await();
} catch (InterruptedException e) {
e.printStackTrace();
输出的是sse流式数据：
22:51:23.620 [OkHttp - OpenAI建立sse连接...
22:51:23.623 [OkHttp - OpenAI返回数据：{****省略无效数据******"model":"gpt-3.5-turbo-0301","choices":[{"delta":{"role":"assistant"},"index":0,"finish_reason":null}]}
22:51:23.625 [OkHttp - OpenAI返回数据：{****省略无效数据******"model":"gpt-3.5-turbo-0301","choices":[{"delta":{"content":"你"},"index":0,"finish_reason":null}]}
22:51:23.636 [OkHttp - OpenAI返回数据：{****省略无效数据******"model":"gpt-3.5-turbo-0301","choices":[{"delta":{"content":"好"},"index":0,"finish_reason":null}]}
22:51:23.911 [OkHttp - OpenAI返回数据：{****省略无效数据******"model":"gpt-3.5-turbo-0301","choices":[{"delta":{"content":"！"},"index":0,"finish_reason":null}]}
22:51:23.911 [OkHttp - OpenAI返回数据：{****省略无效数据******"model":"gpt-3.5-turbo-0301","choices":[{"delta":{"content":"有"},"index":0,"finish_reason":null}]}
22:51:23.911 [OkHttp - OpenAI返回数据：{****省略无效数据******"model":"gpt-3.5-turbo-0301","choices":[{"delta":{"content":"什"},"index":0,"finish_reason":null}]}
22:51:23.911 [OkHttp - OpenAI返回数据：{****省略无效数据******"model":"gpt-3.5-turbo-0301","choices":[{"delta":{"content":"么"},"index":0,"finish_reason":null}]}
22:51:23.911 [OkHttp - OpenAI返回数据：{****省略无效数据******"model":"gpt-3.5-turbo-0301","choices":[{"delta":{"content":"我"},"index":0,"finish_reason":null}]}
22:51:23.911 [OkHttp - OpenAI返回数据：{****省略无效数据******"model":"gpt-3.5-turbo-0301","choices":[{"delta":{"content":"可以"},"index":0,"finish_reason":null}]}
22:51:23.911 [OkHttp - OpenAI返回数据：{****省略无效数据******"model":"gpt-3.5-turbo-0301","choices":[{"delta":{"content":"帮"},"index":0,"finish_reason":null}]}
22:51:23.912 [OkHttp - OpenAI返回数据：{****省略无效数据******"model":"gpt-3.5-turbo-0301","choices":[{"delta":{"content":"助"},"index":0,"finish_reason":null}]}
22:51:23.934 [OkHttp - OpenAI返回数据：{****省略无效数据******"model":"gpt-3.5-turbo-0301","choices":[{"delta":{"content":"你"},"index":0,"finish_reason":null}]}
22:51:24.203 [OkHttp - OpenAI返回数据：{****省略无效数据******"model":"gpt-3.5-turbo-0301","choices":[{"delta":{"content":"的"},"index":0,"finish_reason":null}]}
22:51:24.203 [OkHttp - OpenAI返回数据：{****省略无效数据******"model":"gpt-3.5-turbo-0301","choices":[{"delta":{"content":"吗"},"index":0,"finish_reason":null}]}
22:51:24.203 [OkHttp - OpenAI返回数据：{****省略无效数据******"model":"gpt-3.5-turbo-0301","choices":[{"delta":{"content":"？"},"index":0,"finish_reason":null}]}
22:51:24.276 [OkHttp - OpenAI返回数据：{****省略无效数据******"model":"gpt-3.5-turbo-0301","choices":[{"delta":{},"index":0,"finish_reason":"stop"}]}
22:51:24.276 [OkHttp - OpenAI返回数据：[DONE]
22:51:24.277 [OkHttp - OpenAI返回数据结束了
22:51:24.277 [OkHttp - OpenAI关闭sse连接...
流式输出如何集成Spring Boot实现 api接口?
可以参考项目：https://github.com/Grt1228/chatgpt-steam-output
实现自定义的EventSourceListener，例如：OpenAIEventSourceListener并持有一个SseEmitter，通过SseEmitter进行数据的通信
postman测试
发送请求：Get http://localhost:8080/test/sse?uid=123
看下response （需要新版本postman）
重点关注下header：Content-Type：text/event-stream
如果想结合前端显示自行百度sse前端相关实现
支持最新版的语音转文字，语音翻译api请参考测试代码：OpenAiClientTest.java
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