Why I‘m getting 404 Resource Not Found to my newly Azure OpenAI deployment?

**题意:**为什么我新部署的Azure OpenAI服务会出现404资源未找到的错误?

问题背景:

I've gone through this quickstart and I created my Azure OpenAI resource + created a model deployment which is in state succeedded. I also playaround it in Azure OpenAI Studio - Microsoft Azure and it works there.

我已经按照快速入门指南操作,创建了我的Azure OpenAI资源,并成功部署了一个模型。我也在Azure OpenAI Studio - Microsoft Azure中测试了它,并且在那里工作正常。

But, If I try to reach it from REST API is returns 404 Resource Not Found. I defined the api-key header, and took the url and json from Code View -> json from inside the playground.

但是,如果我尝试通过REST API访问它,它会返回404资源未找到。我已经定义了api-key头部,并且从playground里面的Code View->json获取了URL和JSON。

I'm executing

POST https://raz-openai.openai.azure.com/openai/deployments/raz-model-2/completions?api-version=2022-12-01 { "prompt": "", "max_tokens": 100 } with api-key header

Am I missing another step?

我是不是遗漏了其他步骤?

问题解决:

I was also getting a 404 calling the Chat Completions API (https://{resource}.openai.azure.com/openai/deployments/{deployment}/chat/completions) and it turned out that I was using the wrong version. Each model has one or more versions that can be found at Azure OpenAI Service REST API reference.

我在调用聊天补全API(https://{resource}.openai.azure.com/openai/deployments/{deployment}/chat/completions)时也遇到了404错误,后来发现是我使用了错误的版本。每个模型都有一个或多个版本,可以在Azure OpenAI服务REST API参考中找到。

For me, hitting the chat completions (ChatGPT), the correct URL with version was:

对于我来说,在调用聊天补全(ChatGPT)时,带有版本的正确URL是:

https://{resource}.openai.azure.com/openai/deployments/{deployment}/chat/completions?api-version=2023-03-15-preview

Any other version will give a 404 Resource Not Found.

任何其他版本都会返回404资源未找到错误。

Also, here are the definitions of those variables:

另外,以下是这些变量的定义:

  • Resource: Take from the Azure endpoint URL, which can be found on the Overview page in your OpenAI Services resource. The format should be something like https://{resource}.openai.azure.com/

资源(Resource):从Azure端点URL中获取,该URL可以在你的OpenAI服务资源的"概览"页面中找到。URL的格式应该类似于https://{resource}.openai.azure.com/,其中{resource}是你的OpenAI资源名称。这个URL是你与Azure OpenAI服务进行交互的基础,用于构建指向不同API端点的请求。

  • Deployment (aka deployment-id): You can find this in the Azure portal under the Model Deployments section. Each model has a "Model Deployment Name" and this is your Deployment ID. This isn't going to be the OpenAI name (like gpt-35-turbo) but rather the name you gave it when creating the model deployment.

部署(Deployment)(也称为部署ID):你可以在Azure门户的"模型部署"部分找到这个信息。每个模型都有一个"模型部署名称",这就是你的部署ID。这个名称不是OpenAI的模型名称(如gpt-35-turbo),而是你在创建模型部署时自己指定的名称。确保在调用API时使用了正确的部署名称,以便能够正确地与你的自定义模型部署进行交互。

相关推荐
mpr0xy2 小时前
编译支持cuda硬件加速的ffmpeg
ai·ffmpeg·nvidia·cuda
想躺平的咸鱼干4 小时前
大模型开发
ai·大模型·ai应用开发技术架构
Ashmcracker19 小时前
Azure DevOps 使用服务主体配置自托管代理 (Self-hosted Agent) 配置指南
microsoft·微软·云计算·azure·devops
OceanBase数据库官方博客1 天前
OceanBase 混合检索解读:向量+标量,应该优先查哪个
ai·oceanbase·分布式数据库·向量检索·混合检索
心疼你的一切2 天前
在AI深度嵌入企业业务的当下——AI时代的融合数据库
数据库·人工智能·ai·vr
AI360labs_atyun2 天前
微软2025教育AI报告:教育群体采用AI的比例显著提升
大数据·人工智能·科技·microsoft·ai
&梧桐树夏2 天前
【AI】文生图&文生视频
人工智能·ai·langchain
后端小张2 天前
智谱AI图生视频:从批处理到多线程优化
开发语言·人工智能·ai·langchain·音视频
YoungHong19923 天前
Claude Code & Kimi K2 环境配置指南 (Windows/macOS/Ubuntu)
ai·cc·claude code·kimi k2
Web极客码3 天前
DeepSeek vs ChatGPT:谁更胜一筹?
人工智能·ai·chatgpt