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ChatGPT Java SDK支持流式输出、Gpt插件、联网。支持OpenAI官方所有接口。ChatGPT的Java客户端。OpenAI GPT-3.5-Turb GPT-4 Api Client for Java

Home Page: https://chatgpt-java.unfbx.com

License: Apache License 2.0

Java 100.00%
chatgpt gpt-35-turbo gpt-4 java chatgpt-java openai-api openai-images openai-whisper whisper openai-chatgpt

chatgpt-java's Introduction

it’s an “unofficial" or "community-maintained” library. 这是一个非官方的社区维护的库。有bug欢迎朋友们指出,互相学习。

原创发布转载注明出处!

文档地址:https://chatgpt-java.unfbx.com/

星火大模型Java SDK: https://github.com/Grt1228/SparkDesk-Java

To English Doc -> English Doc

💬 联系我,ChatGPT相关学习交流咨询全部免费。

一起探讨chatgpt-java,SDK问题咨询
项目产品开发交流
群失效关注公众号恢复:chatgpt-java
二维码 二维码

📖 项目简介

ChatGPT的Java客户端 OpenAI官方Api的Java SDK,可以快速接入项目使用。支持OpenAI官方全部接口,同时支持Tokens计算。参考文档:Tokens_README.md

Assistant Dall-e-3 FineTuneJob TTS ChatCompletionWithPicture
自定义知识库、AI助理 AI生成图片 微调job 文本转语音 附加图片的ChatCompletion
TikToken Chat Completions Images Speech To Text 余额查询
Token计算 GPT-3.5、4.0对话模型 GPT-3.0对话 图片模型 语音转文字,语音翻译 余额查询
Embeddings Files Moderations Fine-tune Models
嵌入 自定义训练模型 文本审核,敏感词鉴别 微调 模型检索相关

支持流式输出:

流式输出实现方式 小程序 安卓 ios H5
SSE参考:OpenAISSEEventSourceListener 不支持 支持 支持 支持
WebSocket参考:OpenAIWebSocketEventSourceListener 支持 支持 支持 支持

基于本SDK开发的Demo项目,整合Spring Boot 实现CahtGPT对话模式,思路可以参考: https://github.com/Grt1228/chatgpt-steam-output

🚩 特性

  • 支持附加图片的ChatCompletion、指定返回数据格式、Tool Call、Dall-e-3生成图片、FineTuneJob、文本转语音TTS。
  • 支持GPT插件模式 参考实现PluginTest
  • 支持当key异常(失效、过期、封禁)时,自定义动态处理key 参考实现DynamicKeyOpenAiAuthInterceptor
  • 支持当key异常时的告警处理(钉钉、飞书、email、企业微信等等需要自定义开发)参考实现DynamicKeyOpenAiAuthInterceptor
  • 支持多种Tokens计算方式
  • 支持自定义OkhttpClient
  • 支持自定义多Apikey
  • 支持自定义ApiKey的获取策略
  • 支持余额查询
  • 支持个人账户信息查询
  • 支持GPT3、GPT3.5、GPT4.0、GPT3.5—0614、GPT4.0—0614...
  • 支持全部OpenAI的Api

📑 更新日志

  • 1.1.5 Bug Fix
  • 1.1.3 支持Assistant、Run、Thread、Message Api。测试案例OpenAiClientTest
  • 1.1.2-beta0 支持附加图片的ChatCompletion、指定返回数据格式、Tool Call、Dall-e-3生成图片、FineTuneJob、文本转语音TTS。官方文档示例:chatgpt-java.unfbx.com 。测试案例OpenAiClientTest
  • 1.1.1-beta0 function call改成GPT插件模式调用更加简单的调用方式.参考实现PluginTest
  • 1.0.15 moderations接口更新,代码优化,序列化修复。
  • 1.0.14 升级支持最新版Gpt-3.5—0614、Gpt-4.0—0614等模型, 支持function-calling完整使用案例参考:OpenAiClientFunctionTest
  • 1.0.13 支持当key异常(失效、过期、封禁)时,自定义动态处理key,参考实现DynamicKeyOpenAiAuthInterceptor ,支持key异常时的告警处理(钉钉、飞书、email、企业微信等等需要自定义开发)
  • 1.0.12 tokens计算优化、删除模型接口修改、语音接口更新支持官方最新参数
  • 1.0.11 增加新的余额查询接口参考:OpenAiClientTestOpenAiStreamClientTest ,修复tokens计算慢的问题,
  • 1.0.10 支持tokens计算:TikTokensTest ,更多详细的资料参考文档:Tokens_README.md
  • 1.0.9 支持自定义key使用策略参考:OpenAiClientTestOpenAiStreamClientTest ,弃用ChatGPTClient,优化Moderation接口
  • 1.0.8 修改OpenAiClient和OpenAiStreamClient的自定义相关实现,超时设置,代理设置,自定义拦截器设置改为通过自定义OkHttpClient实现,将OkHttpClient交由用户自定义控制更加合理,可以实现更多的参数自定义。支持多Api Keys配置。
  • 1.0.7 修复反序列化报错Bug:#79 ,Image SDK枚举值bug:#76 ,感谢两位朋友指出:@CCc3120@seven-cm
  • 1.0.6 支持余额查询参考:OpenAiClientTestOpenAiStreamClientTest creditGrants方法,支持最新GPT-4模型,参考:ChatCompletion.Model构建消息体传入模型即可。感谢群友提供的余额接口地址以及@PlexPt 提供的模型参数
  • 1.0.5 支持自定义Api Host,使用Builder构建。参考下面的快速开始部分代码。
  • 1.0.4 官方最新的ChatGPT Stream模式下的Api返回值改动。
  • 1.0.3 支持最新的GPT-3.5-Turbo模型和Whisper-1模型,支持语音功能转文字,语音翻译。OpenAiClient和OpenAiStreamClient支持Builder构造,支持代理。
  • 1.0.2 支持Stream流式输出,参考:OpenAiStreamClient
  • 1.0.1 支持自定义超时时间,自定义OkHttpClient拦截器,参考:OpenAiClient构造函数
  • 1.0.0 支持所有的OpenAI官方接口

🚀 快速开始

本项目支持默认输出流式输出。完整SDK测试案例参考:

SDK测试案例 Tokens计算测试案例 完整Function-Call调用案例
OpenAiClientTestOpenAiStreamClientTest Tokens计算参考:TikTokensTest OpenAiClientFunctionTest

方式一

1、导入pom依赖

<dependency>
    <groupId>com.unfbx</groupId>
    <artifactId>chatgpt-java</artifactId>
    <version>1.0.14-beta1</version>
</dependency>

2、流式客户端使用示例:

更多SDK示例参考:OpenAiStreamClientTest

默认OkHttpClient

public class Test {
    public static void main(String[] args) {
        OpenAiStreamClient client = OpenAiStreamClient.builder()
                .apiKey(Arrays.asList("sk-********","sk-********"))
                //自定义key的获取策略:默认KeyRandomStrategy
                //.keyStrategy(new KeyRandomStrategy())
                .keyStrategy(new FirstKeyStrategy())
                //自己做了代理就传代理地址,没有可不不传
//                .apiHost("https://自己代理的服务器地址/")
                .build();
        //聊天模型:gpt-3.5
        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();
        }
    }
}

自定义OkHttpClient客户端使用示例:

public class Test {
    public static void main(String[] args) {
        //国内访问需要做代理,国外服务器不需要
        Proxy proxy = new Proxy(Proxy.Type.HTTP, new InetSocketAddress("127.0.0.1", 7890));
        HttpLoggingInterceptor httpLoggingInterceptor = new HttpLoggingInterceptor(new OpenAILogger());
        //!!!!千万别再生产或者测试环境打开BODY级别日志!!!!
        //!!!生产或者测试环境建议设置为这三种级别:NONE,BASIC,HEADERS,!!!
        httpLoggingInterceptor.setLevel(HttpLoggingInterceptor.Level.HEADERS);
        OkHttpClient okHttpClient = new OkHttpClient
                .Builder()
                .proxy(proxy)//自定义代理
                .addInterceptor(httpLoggingInterceptor)//自定义日志
                .connectTimeout(30, TimeUnit.SECONDS)//自定义超时时间
                .writeTimeout(30, TimeUnit.SECONDS)//自定义超时时间
                .readTimeout(30, TimeUnit.SECONDS)//自定义超时时间
                .build();
        OpenAiStreamClient client = OpenAiStreamClient.builder()
                .apiKey(Arrays.asList("sk-********","sk-********"))
                //自定义key的获取策略:默认KeyRandomStrategy
                //.keyStrategy(new KeyRandomStrategy())
                .keyStrategy(new FirstKeyStrategy())
                .okHttpClient(okHttpClient)
                //自己做了代理就传代理地址,没有可不不传
//                .apiHost("https://自己代理的服务器地址/")
                .build();
    }
}

输出日志(text是持续输出的):

23:03:59.158 [省略无效信息] INFO com.unfbx.chatgpt.sse.ConsoleEventSourceListener - OpenAI建立sse连接...
23:03:59.160 [省略无效信息] INFO com.unfbx.chatgpt.sse.ConsoleEventSourceListener - OpenAI返回数据:{"id": "cmpl-6pIHnOOJiiUEVMesXwxzzcSQFoZHj", "object": "text_completion", "created": 1677683039, "choices": [{"text": "\n", "index": 0, "logprobs": null, "finish_reason": null}], "model": "text-davinci-003"}
23:03:59.172 [省略无效信息] INFO com.unfbx.chatgpt.sse.ConsoleEventSourceListener - OpenAI返回数据:{"id": "cmpl-6pIHnOOJiiUEVMesXwxzzcSQFoZHj", "object": "text_completion", "created": 1677683039, "choices": [{"text": "\n", "index": 0, "logprobs": null, "finish_reason": null}], "model": "text-davinci-003"}
23:03:59.251 [省略无效信息] INFO com.unfbx.chatgpt.sse.ConsoleEventSourceListener - OpenAI返回数据:{"id": "cmpl-6pIHnOOJiiUEVMesXwxzzcSQFoZHj", "object": "text_completion", "created": 1677683039, "choices": [{"text": "\u5fc3", "index": 0, "logprobs": null, "finish_reason": null}], "model": "text-davinci-003"}
23:03:59.313 [省略无效信息] INFO com.unfbx.chatgpt.sse.ConsoleEventSourceListener - OpenAI返回数据:{"id": "cmpl-6pIHnOOJiiUEVMesXwxzzcSQFoZHj", "object": "text_completion", "created": 1677683039, "choices": [{"text": "\u60c5", "index": 0, "logprobs": null, "finish_reason": null}], "model": "text-davinci-003"}
23:03:59.380 [省略无效信息] INFO com.unfbx.chatgpt.sse.ConsoleEventSourceListener - OpenAI返回数据:{"id": "cmpl-6pIHnOOJiiUEVMesXwxzzcSQFoZHj", "object": "text_completion", "created": 1677683039, "choices": [{"text": "\u8212", "index": 0, "logprobs": null, "finish_reason": null}], "model": "text-davinci-003"}
23:03:59.439 [省略无效信息] INFO com.unfbx.chatgpt.sse.ConsoleEventSourceListener - OpenAI返回数据:{"id": "cmpl-6pIHnOOJiiUEVMesXwxzzcSQFoZHj", "object": "text_completion", "created": 1677683039, "choices": [{"text": "\u7545", "index": 0, "logprobs": null, "finish_reason": null}], "model": "text-davinci-003"}
23:03:59.532 [省略无效信息] INFO com.unfbx.chatgpt.sse.ConsoleEventSourceListener - OpenAI返回数据:{"id": "cmpl-6pIHnOOJiiUEVMesXwxzzcSQFoZHj", "object": "text_completion", "created": 1677683039, "choices": [{"text": "\uff0c", "index": 0, "logprobs": null, "finish_reason": null}], "model": "text-davinci-003"}
23:03:59.579 [省略无效信息] INFO com.unfbx.chatgpt.sse.ConsoleEventSourceListener - OpenAI返回数据:{"id": "cmpl-6pIHnOOJiiUEVMesXwxzzcSQFoZHj", "object": "text_completion", "created": 1677683039, "choices": [{"text": "\u5fc3", "index": 0, "logprobs": null, "finish_reason": null}], "model": "text-davinci-003"}
23:03:59.641 [省略无效信息] INFO com.unfbx.chatgpt.sse.ConsoleEventSourceListener - OpenAI返回数据:{"id": "cmpl-6pIHnOOJiiUEVMesXwxzzcSQFoZHj", "object": "text_completion", "created": 1677683039, "choices": [{"text": "\u65f7", "index": 0, "logprobs": null, "finish_reason": null}], "model": "text-davinci-003"}
23:03:59.673 [省略无效信息] INFO com.unfbx.chatgpt.sse.ConsoleEventSourceListener - OpenAI返回数据:{"id": "cmpl-6pIHnOOJiiUEVMesXwxzzcSQFoZHj", "object": "text_completion", "created": 1677683039, "choices": [{"text": "\u795e", "index": 0, "logprobs": null, "finish_reason": null}], "model": "text-davinci-003"}
23:03:59.751 [省略无效信息] INFO com.unfbx.chatgpt.sse.ConsoleEventSourceListener - OpenAI返回数据:{"id": "cmpl-6pIHnOOJiiUEVMesXwxzzcSQFoZHj", "object": "text_completion", "created": 1677683039, "choices": [{"text": "\u6021", "index": 0, "logprobs": null, "finish_reason": null}], "model": "text-davinci-003"}
23:03:59.782 [省略无效信息] INFO com.unfbx.chatgpt.sse.ConsoleEventSourceListener - OpenAI返回数据:{"id": "cmpl-6pIHnOOJiiUEVMesXwxzzcSQFoZHj", "object": "text_completion", "created": 1677683039, "choices": [{"text": "\u3002", "index": 0, "logprobs": null, "finish_reason": null}], "model": "text-davinci-003"}
23:03:59.815 [省略无效信息] INFO com.unfbx.chatgpt.sse.ConsoleEventSourceListener - OpenAI返回数据:[DONE]
23:03:59.815 [省略无效信息] INFO com.unfbx.chatgpt.sse.ConsoleEventSourceListener - OpenAI返回数据结束了
23:03:59.815 [省略无效信息] INFO com.unfbx.chatgpt.sse.ConsoleEventSourceListener - OpenAI关闭sse连接...

3、默认客户端使用示例(支持全部API):

更多SDK示例参考:OpenAiClientTest

默认OkHttpClient

public class Test {
    public static void main(String[] args) {
        OpenAiClient openAiClient = OpenAiClient.builder()
                .apiKey(Arrays.asList("sk-********","sk-********"))
                //自定义key的获取策略:默认KeyRandomStrategy
                //.keyStrategy(new KeyRandomStrategy())
                .keyStrategy(new FirstKeyStrategy())
                //自己做了代理就传代理地址,没有可不不传
//                .apiHost("https://自己代理的服务器地址/")
                .build();
                //聊天模型:gpt-3.5
        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());
        });
    }
}

自定义OkHttpClient客户端使用示例:

public class Test {
    public static void main(String[] args) {
        //国内访问需要做代理,国外服务器不需要
        Proxy proxy = new Proxy(Proxy.Type.HTTP, new InetSocketAddress("127.0.0.1", 7890));
        HttpLoggingInterceptor httpLoggingInterceptor = new HttpLoggingInterceptor(new OpenAILogger());
        //!!!!千万别再生产或者测试环境打开BODY级别日志!!!!
        //!!!生产或者测试环境建议设置为这三种级别:NONE,BASIC,HEADERS,!!!
        httpLoggingInterceptor.setLevel(HttpLoggingInterceptor.Level.HEADERS);
        OkHttpClient okHttpClient = new OkHttpClient
                .Builder()
                .proxy(proxy)//自定义代理
                .addInterceptor(httpLoggingInterceptor)//自定义日志输出
                .addInterceptor(new OpenAiResponseInterceptor())//自定义返回值拦截
                .connectTimeout(10, TimeUnit.SECONDS)//自定义超时时间
                .writeTimeout(30, TimeUnit.SECONDS)//自定义超时时间
                .readTimeout(30, TimeUnit.SECONDS)//自定义超时时间
                .build();
        //构建客户端
        OpenAiClient openAiClient = OpenAiClient.builder()
                .apiKey(Arrays.asList("sk-********","sk-********"))
                //自定义key的获取策略:默认KeyRandomStrategy
                //.keyStrategy(new KeyRandomStrategy())
                .keyStrategy(new FirstKeyStrategy())
                .okHttpClient(okHttpClient)
                //自己做了代理就传代理地址,没有可不不传
//                .apiHost("https://自己代理的服务器地址/")
                .build();
                //聊天模型:gpt-3.5
        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());
        });
    }
}

方式二(下载源码直接运行)

下载源码打包

❔ QA

Q A
如何实现连续对话? issues:#8
如何实现流式输出? 升级1.0.2版本,参考源码:OpenAiStreamClientTest
如何整合SpringBoot实现流式输出的Api接口? 参考另外一个项目:chatgpt-steam-output
最新版GPT-3.5-TURBO是否支持? 升级1.0.3 已经支持ChatCompletion, 参考测试案例:OpenAiStreamClientTestOpenAiStreamClientTest
最新版语言转文字和语言翻译是否支持? 升级1.0.3 已经支持whisper参考测试案例:OpenAiStreamClientTestOpenAiStreamClientTest

📌 国内访问解决方案

国内访问可以看下这个解决方案:noobnooc/noobnooc#9

📋 开发案例收集

基于本SDK开发案例收集chatgpt-java SDK案例征集

🌟 Star History

Star History Chart

🙏 鸣谢

站在巨人的肩膀:

☕ 打赏

如果项目对你有帮助,可以选择请我喝杯奶茶

微信截图_20230405222411 微信截图_20230405222357

开源协议:LICENSE

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chatgpt-java's Issues

1.0.4版本貌似会有okhttp包冲突问题

引入okHttp 3.8.1版本中的HttpUrl.get方法参数为get(URL url),但是在Retrofit中调用HttpUrl.get(String url),会报NoSuchMethodError: okhttp3.HttpUrl.get(Ljava/lang/String;)Lokhttp3/HttpUrl;
手动引入okHttp3.12.0之后,不再报错

但是使用流展示的实例时,又会遇到新的版本冲突问题,具体原因没有找到,貌似是因为okHttp-see这个包的版本有问题

请问如何实现才能实现上下文有联系的AI对话?

如题,比如我连续提问,后面的答非所问:
`
@test
public void chat() {
//聊天模型:gpt-3.5
Message message = Message.builder().role(Message.Role.USER).content("现在的光刻机最先进的型号是什么!").build();
ChatCompletion chatCompletion = ChatCompletion.builder().messages(Arrays.asList(message)).build();
ChatCompletionResponse chatCompletionResponse = v2.chatCompletion(chatCompletion);
chatCompletionResponse.getChoices().forEach(e -> {
System.out.println(e.getMessage());
});

CompletionResponse completions = v2.completions("那么**企业在用的是什么型号?");
for (Choice choice : completions.getChoices()) {
  System.out.println(choice.getText());
}
completions = v2.completions("是哪家企业?");
for (Choice choice : completions.getChoices()) {
  System.out.println(choice.getText());
}

}

`

在使用ChatGPT 3.5 类模型时遇到的报错

`try {

        val client = buildClient()
        val eventSourceListener = ChatEventSourceListener(chat, Model.CHATGPT_3_5_TURBO)
        val message = Message.builder().role(Message.Role.USER).content(text).build()
        val chatCompletion = ChatCompletion.builder().messages(listOf(message)).build()
        client!!.streamChatCompletion(chatCompletion, eventSourceListener)
        val countDownLatch = CountDownLatch(1)

        try {
            countDownLatch.await()
        } catch (e: InterruptedException) {
            e.printStackTrace()
        }
    } catch (e: Exception) {
        chat.msgs.add(Msg(chat.friend, mutableStateOf(e.stackTraceToString()), dateFormat))
    }`

错误显示

OpenAI SSE链接异常 data: {
"error": {
"message": "Invalid URL (POST /v1/chat/completions)",
"type": "invalid_request_error",
"param": null,
"code": null
}
} 异常 null

请求开发者支持`gpt-3.5-turbo`模型提问

相关链接:https://openai.com/blog/introducing-chatgpt-and-whisper-apishttps://platform.openai.com/docs/guides/chat

目前指定模型为gpt-3.5-turbo构造Completion

        Completion completion = Completion.builder()
                .model("gpt-3.5-turbo")
                .prompt(text)
                .build();

会报错:

com.unfbx.chatgpt.exception.BaseException: Rate limit reached for default-gpt-3.5-turbo in organization org-dbZK脱敏脱敏 on tokens per min. Limit: 40000.000000 / min. Current: 40960.000000 / min. Contact [email protected] if you continue to have issues. Please add a payment method to your account to increase your rate limit. Visit https://platform.openai.com/account/billing to add a payment method.

实测应该没有达到这个速度限制,而且多次请求都提示Current: 40960.000000 / min,不太正常。

感谢

ChatGPTTest运行报错

[main] INFO com.unfbx.chatgpt.ChatGPTClient - 调用ChatGPT请求返回值:{
"error": {
"message": "Unrecognized request arguments supplied: bestOf, frequencyPenalty, maxTokens, presencePenalty, topP",
"type": "invalid_request_error",
"param": null,
"code": null
}
}

报错

Exception in thread "main" java.lang.ExceptionInInitializerError
at com.ChatGPT.main(ChatGPT.java:16)
Caused by: org.apache.logging.log4j.LoggingException: log4j-slf4j-impl cannot be present with log4j-to-slf4j
at org.apache.logging.slf4j.Log4jLoggerFactory.validateContext(Log4jLoggerFactory.java:49)
at org.apache.logging.slf4j.Log4jLoggerFactory.newLogger(Log4jLoggerFactory.java:39)
at org.apache.logging.slf4j.Log4jLoggerFactory.newLogger(Log4jLoggerFactory.java:30)
at org.apache.logging.log4j.spi.AbstractLoggerAdapter.getLogger(AbstractLoggerAdapter.java:53)
at org.apache.logging.slf4j.Log4jLoggerFactory.getLogger(Log4jLoggerFactory.java:30)
at org.slf4j.LoggerFactory.getLogger(LoggerFactory.java:363)
at org.slf4j.LoggerFactory.getLogger(LoggerFactory.java:388)
at com.unfbx.chatgpt.OpenAiClient.(OpenAiClient.java:54)

感觉返回时间有点过长

我用单独发送http请求的方式,大概3s内就可以收到返回,但是相同的内容调用您的包,发现返回时间大概要10s甚至更久,不知道这个时长是产生在了哪里?

这个报错有人遇到嘛

Caused by: java.io.IOException: unexpected end of stream on unknown
java.io.EOFException: \n not found: limit=0 content=…

催更websocket连接

您好,请问websocket连接在实现了嘛~小程序实现不了sse,催催~~~~~

如何实现记住上下文

流式的方式很酷,但是有个困难,我在多次调用streamChatCompletion方法的时候他不能记住上下文,有什么好的思路解决这个问题吗

代理报错 Malformed reply from SOCKS server

00:35:22.701 [http-nio-9209-exec-1] ERROR c.t.c.s.h.GlobalExceptionHandler - [handleRuntimeException,82] - 请求地址'/chat/getQuestion',发生未知异常.
java.lang.RuntimeException: java.net.SocketException: Malformed reply from SOCKS server
at io.reactivex.internal.util.ExceptionHelper.wrapOrThrow(ExceptionHelper.java:46)
at io.reactivex.internal.observers.BlockingMultiObserver.blockingGet(BlockingMultiObserver.java:93)
at io.reactivex.Single.blockingGet(Single.java:2870)
at com.unfbx.chatgpt.OpenAiClient.completions(OpenAiClient.java:352)
at club.tduvr.message.controller.ChatGptController.getQuestion(ChatGptController.java:56)
at java.base/jdk.internal.reflect.DirectMethodHandleAccessor.invoke(DirectMethodHandleAccessor.java:104)
at java.base/java.lang.reflect.Method.invoke(Method.java:577)
at org.springframework.web.method.support.InvocableHandlerMethod.doInvoke(InvocableHandlerMethod.java:205)
at org.springframework.web.method.support.InvocableHandlerMethod.invokeForRequest(InvocableHandlerMethod.java:150)
at org.springframework.web.servlet.mvc.method.annotation.ServletInvocableHandlerMethod.invokeAndHandle(ServletInvocableHandlerMethod.java:117)
at org.springframework.web.servlet.mvc.method.annotation.RequestMappingHandlerAdapter.invokeHandlerMethod(RequestMappingHandlerAdapter.java:895)
at org.springframework.web.servlet.mvc.method.annotation.RequestMappingHandlerAdapter.handleInternal(RequestMappingHandlerAdapter.java:808)
at org.springframework.web.servlet.mvc.method.AbstractHandlerMethodAdapter.handle(AbstractHandlerMethodAdapter.java:87)
at org.springframework.web.servlet.DispatcherServlet.doDispatch(DispatcherServlet.java:1070)
at org.springframework.web.servlet.DispatcherServlet.doService(DispatcherServlet.java:963)
at org.springframework.web.servlet.FrameworkServlet.processRequest(FrameworkServlet.java:1006)
at org.springframework.web.servlet.FrameworkServlet.doGet(FrameworkServlet.java:898)
at javax.servlet.http.HttpServlet.service(HttpServlet.java:645)
at org.springframework.web.servlet.FrameworkServlet.service(FrameworkServlet.java:883)
at javax.servlet.http.HttpServlet.service(HttpServlet.java:750)
at org.apache.catalina.core.ApplicationFilterChain.internalDoFilter(ApplicationFilterChain.java:227)
at org.apache.catalina.core.ApplicationFilterChain.doFilter(ApplicationFilterChain.java:162)
at org.apache.tomcat.websocket.server.WsFilter.doFilter(WsFilter.java:53)
at org.apache.catalina.core.ApplicationFilterChain.internalDoFilter(ApplicationFilterChain.java:189)
at org.apache.catalina.core.ApplicationFilterChain.doFilter(ApplicationFilterChain.java:162)
at org.springframework.web.filter.RequestContextFilter.doFilterInternal(RequestContextFilter.java:100)
at org.springframework.web.filter.OncePerRequestFilter.doFilter(OncePerRequestFilter.java:117)
at org.apache.catalina.core.ApplicationFilterChain.internalDoFilter(ApplicationFilterChain.java:189)
at org.apache.catalina.core.ApplicationFilterChain.doFilter(ApplicationFilterChain.java:162)
at org.springframework.web.filter.FormContentFilter.doFilterInternal(FormContentFilter.java:93)
at org.springframework.web.filter.OncePerRequestFilter.doFilter(OncePerRequestFilter.java:117)
at org.apache.catalina.core.ApplicationFilterChain.internalDoFilter(ApplicationFilterChain.java:189)
at org.apache.catalina.core.ApplicationFilterChain.doFilter(ApplicationFilterChain.java:162)
at org.springframework.boot.actuate.metrics.web.servlet.WebMvcMetricsFilter.doFilterInternal(WebMvcMetricsFilter.java:96)
at org.springframework.web.filter.OncePerRequestFilter.doFilter(OncePerRequestFilter.java:117)
at org.apache.catalina.core.ApplicationFilterChain.internalDoFilter(ApplicationFilterChain.java:189)
at org.apache.catalina.core.ApplicationFilterChain.doFilter(ApplicationFilterChain.java:162)
at org.springframework.web.filter.CharacterEncodingFilter.doFilterInternal(CharacterEncodingFilter.java:201)
at org.springframework.web.filter.OncePerRequestFilter.doFilter(OncePerRequestFilter.java:117)
at org.apache.catalina.core.ApplicationFilterChain.internalDoFilter(ApplicationFilterChain.java:189)
at org.apache.catalina.core.ApplicationFilterChain.doFilter(ApplicationFilterChain.java:162)
at org.apache.catalina.core.StandardWrapperValve.invoke(StandardWrapperValve.java:197)
at org.apache.catalina.core.StandardContextValve.invoke(StandardContextValve.java:97)
at org.apache.catalina.authenticator.AuthenticatorBase.invoke(AuthenticatorBase.java:541)
at org.apache.catalina.core.StandardHostValve.invoke(StandardHostValve.java:135)
at org.apache.catalina.valves.ErrorReportValve.invoke(ErrorReportValve.java:92)
at org.apache.catalina.core.StandardEngineValve.invoke(StandardEngineValve.java:78)
at org.apache.catalina.connector.CoyoteAdapter.service(CoyoteAdapter.java:360)
at org.apache.coyote.http11.Http11Processor.service(Http11Processor.java:399)
at org.apache.coyote.AbstractProcessorLight.process(AbstractProcessorLight.java:65)
at org.apache.coyote.AbstractProtocol$ConnectionHandler.process(AbstractProtocol.java:890)
at org.apache.tomcat.util.net.NioEndpoint$SocketProcessor.doRun(NioEndpoint.java:1789)
at org.apache.tomcat.util.net.SocketProcessorBase.run(SocketProcessorBase.java:49)
at org.apache.tomcat.util.threads.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1191)
at org.apache.tomcat.util.threads.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:659)
at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
at java.base/java.lang.Thread.run(Thread.java:833)
Caused by: java.net.SocketException: Malformed reply from SOCKS server
at java.base/java.net.SocksSocketImpl.readSocksReply(SocksSocketImpl.java:128)
at java.base/java.net.SocksSocketImpl.connect(SocksSocketImpl.java:429)
at java.base/java.net.Socket.connect(Socket.java:633)
at okhttp3.internal.platform.Platform.connectSocket(Platform.kt:128)
at okhttp3.internal.connection.RealConnection.connectSocket(RealConnection.kt:295)
at okhttp3.internal.connection.RealConnection.connect(RealConnection.kt:207)
at okhttp3.internal.connection.ExchangeFinder.findConnection(ExchangeFinder.kt:226)
at okhttp3.internal.connection.ExchangeFinder.findHealthyConnection(ExchangeFinder.kt:106)
at okhttp3.internal.connection.ExchangeFinder.find(ExchangeFinder.kt:74)
at okhttp3.internal.connection.RealCall.initExchange$okhttp(RealCall.kt:255)
at okhttp3.internal.connection.ConnectInterceptor.intercept(ConnectInterceptor.kt:32)
at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.kt:109)
at okhttp3.internal.cache.CacheInterceptor.intercept(CacheInterceptor.kt:95)
at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.kt:109)
at okhttp3.internal.http.BridgeInterceptor.intercept(BridgeInterceptor.kt:83)
at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.kt:109)
at okhttp3.internal.http.RetryAndFollowUpInterceptor.intercept(RetryAndFollowUpInterceptor.kt:76)
at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.kt:109)
at com.unfbx.chatgpt.OpenAiClient.lambda$okHttpClient$2(OpenAiClient.java:271)
at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.kt:109)
at com.unfbx.chatgpt.OpenAiClient.lambda$okHttpClient$1(OpenAiClient.java:268)
at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.kt:109)
at okhttp3.internal.connection.RealCall.getResponseWithInterceptorChain$okhttp(RealCall.kt:201)
at okhttp3.internal.connection.RealCall.execute(RealCall.kt:154)
at retrofit2.OkHttpCall.execute(OkHttpCall.java:204)
at retrofit2.adapter.rxjava2.CallExecuteObservable.subscribeActual(CallExecuteObservable.java:46)
at io.reactivex.Observable.subscribe(Observable.java:12284)
at retrofit2.adapter.rxjava2.BodyObservable.subscribeActual(BodyObservable.java:35)
at io.reactivex.Observable.subscribe(Observable.java:12284)
at io.reactivex.internal.operators.observable.ObservableSingleSingle.subscribeActual(ObservableSingleSingle.java:35)
at io.reactivex.Single.subscribe(Single.java:3666)
at io.reactivex.Single.blockingGet(Single.java:2869)
... 54 common frames omitted

ChatGPTTest 替换 apiKey 报错

错误信息:
{
"error": {
"message": "Unrecognized request arguments supplied: bestOf, frequencyPenalty, maxTokens, presencePenalty, topP",
"type": "invalid_request_error",
"param": null,
"code": null
}
}

请教大佬,通过chatGPT生成的图片,一般怎么下载呀,我通过URL下载的时候会报错

chatGPT生成的url为:
https://oaidalleapiprodscus.blob.core.windows.net/private/org-x2tDof6L8GQcT9HVev8uEEvq/user-QKO2z3TMxUYqYwTpR55INmEC/img-qBCyuxcVP2RHrpvmUUU3AjkP.png?st=2023-03-10T14%3A45%3A30Z&se=2023-03-10T16%3A45%3A30Z&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=2023-03-10T03%3A35%3A18Z&ske=2023-03-11T03%3A35%3A18Z&sks=b&skv=2021-08-06&sig=lCj9fQwr6USg1ryf4wNB3HSRiAdpDE1XEmV9y9eKluQ%3D

Linux上的代码为:
`public static void download(String urlString, String filename, String savePath) {

URL url = null;
HttpsURLConnection con = null;
try {
    url = new URL(urlString);
    try {
        // trust all hosts
        trustAllHosts();
        HttpsURLConnection https = (HttpsURLConnection) url.openConnection();
        //如果请求是https,忽略证书校验
        if (url.getProtocol().toLowerCase().equals("https")) {
            https.setHostnameVerifier(DO_NOT_VERIFY);
            con = https;
        } else {
            con = (HttpsURLConnection) url.openConnection();
        }
        
        //设置请求超时为5s
        con.setConnectTimeout(50 * 1000);
        // 输入流
        InputStream is = con.getInputStream();
        
        // 1K的数据缓冲
        byte[] bs = new byte[1024];
        // 读取到的数据长度
        int len;
        // 输出的文件流
        File sf = new File(savePath);
        if (!sf.exists()) {
            sf.mkdirs();
        }
    /* 获取图片的扩展名(我没用到,所以先注释了)
    String extensionName = urlString.substring(urlString.lastIndexOf(".") + 1);*/
        OutputStream os = new FileOutputStream(sf.getPath() + "/" + filename);
        // 开始读取
        while ((len = is.read(bs)) != -1) {
            os.write(bs, 0, len);
        }
        // 完毕,关闭所有链接
        os.close();
        is.close();
    } catch (MalformedURLException e) {
        e.printStackTrace();
    } catch (IOException e) {
        e.printStackTrace();
    }
} catch (MalformedURLException e) {
    e.printStackTrace();
}

}`
报错信息如下:超时时间设置很长也没有作用
java.net.ConnectException: Connection timed out (Connection timed out)

请求超时问题

为什么用了梯子能通过浏览器访问chatgpt接口,然而使用hutools发送请求超时(访问国内的网站能够响应得到数据)
800_LI (2)
userAvater

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