diff --git a/README.en-US.md b/README.en-US.md deleted file mode 100644 index cec77e2..0000000 --- a/README.en-US.md +++ /dev/null @@ -1,110 +0,0 @@ -# Azure OpenAI Proxy - -[English](./README.en-US.md) | Simplified Chinese - -Azure OpenAI Proxy is a tool that transforms OpenAI API requests into Azure OpenAI API requests, allowing OpenAI-compatible applications to seamlessly use Azure Open AI. - -## Prerequisites - -An Azure OpenAI account is required to use Azure OpenAI Proxy. - -## Azure Deployment - -[![Deploy to Azure](https://aka.ms/deploytoazurebutton)](https://portal.azure.com/#create/Microsoft.Template/uri/https%3A%2F%2Fraw.githubusercontent.com%2Fscalaone%2Fazure-openai-proxy%2Fmain%2Fdeploy%2Fazure-deploy.json) - -Remember to: - -- Select the region that matches your Azure OpenAI resource for best performance. -- If deployment fails because the 'proxywebapp' name is already taken, change the resource prefix and redeploy. -- The deployed proxy app is part of a B1 pricing tier Azure web app plan, which can be modified in the Azure Portal after deployment. - -## Docker Deployment - -To deploy using Docker, execute the following command: - -`docker run -d -p 3000:3000 scalaone/azure-openai-proxy` - -## Local Execution and Testing (Command Line) - -Follow these steps: - -1. Install NodeJS 18. -2. Clone the repository in the command line window. -3. Run `npm install` to install the dependencies. -4. Run `npm start` to start the application. -5. Use the script below for testing. Replace `AZURE_RESOURCE_ID`, `AZURE_MODEL_DEPLOYMENT`, and `AZURE_API_KEY` before running. The default value for `AZURE_API_VERSION` is `2023-05-15` and is optional. - -
-Test script - -```bash -curl -X "POST" "http://localhost:3000/v1/chat/completions" \ --H 'Authorization: AZURE_RESOURCE_ID:AZURE_MODEL_DEPLOYMENT:AZURE_API_KEY:AZURE_API_VERSION' \ --H 'Content-Type: application/json; charset=utf-8' \ --d $'{ - "messages": [ - { - "role": "system", - "content": "You are an AI assistant that helps people find information." - }, - { - "role": "user", - "content": "hi." - } - ], - "temperature": 1, - "model": "gpt-3.5-turbo", - "stream": false -}' -``` - -
- -## Tested Applications - -The azure-openai-proxy has been tested and confirmed to work with the following applications: - -| Application Name | Docker-compose File | -| --------------------------------------------------------------- | --------------------------------------------------------------- | -| [chatgpt-lite](https://github.com/blrchen/chatgpt-lite) | [docker-compose.yml](./e2e/chatgpt-lite/docker-compose.yml) | -| [chatgpt-next-web](https://github.com/Yidadaa/ChatGPT-Next-Web) | [docker-compose.yml](./e2e/chatgpt-next-web/docker-compose.yml) | -| [chatbot-ui](https://github.com/mckaywrigley/chatbot-ui) | [docker-compose.yml](./e2e/chatbot-ui/docker-compose.yml) | -| [chatgpt-web](https://github.com/Chanzhaoyu/chatgpt-web) | [docker-compose.yml](./e2e/chatgpt-web/docker-compose.yml) | -| [chatgpt-mininal](https://github.com/blrchen/chatgpt-mininal) | [docker-compose.yml](./e2e/chatgpt-mininal/docker-compose.yml) | - -To test locally, follow these steps: - -1. Clone the repository in a command-line window. -2. Update the `OPENAPI_API_KEY` environment variable with `AZURE_RESOURCE_ID:AZURE_MODEL_DEPLOYMENT:AZURE_API_KEY`. Alternatively, update the OPENAPI_API_KEY value in the docker-compose.yml file directly. -3. Navigate to the directory containing the `docker-compose.yml` file for the application you want to test. -4. Execute the build command: `docker-compose build`. -5. Start the service: `docker-compose up -d`. -6. Access the application locally using the port defined in the docker-compose.yml file. For example, visit http://localhost:3000. - -## FAQs - -
-Q: What are `AZURE_RESOURCE_ID`,`AZURE_MODEL_DEPLOYMENT`, and `AZURE_API_KEY`? - -A: These can be found in the Azure management portal. See the image below for reference: - -![resource-and-model](./resource-and-model.jpg) - -
- -
-Q: How can I use gpt-4 and gpt-4-32k models? - -A: To use gpt-4 and gpt-4-32k models, follow the key format below: - -`AZURE_RESOURCE_ID:gpt-3.5-turbo|AZURE_MODEL_DEPLOYMENT,gpt-4|AZURE_MODEL_DEPLOYMENT,gpt-4-32k|AZURE_MODEL_DEPLOYMENT:AZURE_API_KEY:AZURE_API_VERSION` - -
- -## Contributing - -We welcome all PR submissions. - -## Disclaimer - -This code is intended for demonstration and testing purposes only. diff --git a/README.md b/README.md index ffe847d..b946c61 100644 --- a/README.md +++ b/README.md @@ -1,40 +1,43 @@ # Azure OpenAI Proxy -[English](./README.en-US.md) | 简体中文 +English | [简体中文](./README.zh-CN.md) -Azure OpenAI Proxy 是一个 OpenAI API 的代理工具，能将 OpenAI API 请求转为 Azure OpenAI API 请求，从而让只支持 OpenAI 的应用程序无缝使用 Azure OpenAI。 +Azure OpenAI Proxy is a tool that transforms OpenAI API requests into Azure OpenAI API requests, allowing OpenAI-compatible applications to seamlessly use Azure Open AI. -## 使用条件 +## Prerequisites -你需要有一个 Azure OpenAI 账户才能使用 Azure OpenAI Proxy。 +An Azure OpenAI account is required to use Azure OpenAI Proxy. -## Azure 部署 +## Azure Deployment [![Deploy to Azure](https://aka.ms/deploytoazurebutton)](https://portal.azure.com/#create/Microsoft.Template/uri/https%3A%2F%2Fraw.githubusercontent.com%2Fscalaone%2Fazure-openai-proxy%2Fmain%2Fdeploy%2Fazure-deploy.json) -请注意： +Remember to: -- 选择与你的 Azure OpenAI 资源相匹配的区域以获得最佳性能。 -- 如果部署失败是因为 'proxywebapp' 名称已被占用，只需修改资源前缀再重新部署。 -- 已部署的代理应用位于 B1 定价层级的 Azure 网页应用计划下，你可以在部署后在 Azure 门户中进行更新。 +- Select the region that matches your Azure OpenAI resource for best performance. +- If deployment fails because the 'proxywebapp' name is already taken, change the resource prefix and redeploy. +- The deployed proxy app is part of a B1 pricing tier Azure web app plan, which can be modified in the Azure Portal after deployment. -## Docker 部署 +## Docker Deployment + +To deploy using Docker, execute the following command: ```bash docker run -d -p 3000:3000 scalaone/azure-openai-proxy ``` -## 本地运行和测试，命令行方式 +## Local Execution and Testing -1. 安装 NodeJS 18。 -2. 克隆代码到命令行窗口。 -3. 运行 `npm install` 安装依赖项。 -4. 运行 `npm start` 启动应用程序。 -5. 运行下面脚本测试，运行前需要把`AZURE_RESOURCE_ID`，`AZURE_MODEL_DEPLOYMENT`，`AZURE_API_KEY`和`AZURE_API_VERSION`替换，`AZURE_API_VERSION`参数可选，默认是`2023-05-15`。 +Follow these steps: -
-测试脚本 +1. Install NodeJS 18. +2. Clone the repository in the command line window. +3. Run `npm install` to install the dependencies. +4. Run `npm start` to start the application. +5. Use the script below for testing. Replace `AZURE_RESOURCE_ID`, `AZURE_MODEL_DEPLOYMENT`, and `AZURE_API_KEY` before running. The default value for `AZURE_API_VERSION` is `2023-05-15` and is optional. +
+Test script ```bash curl -X "POST" "http://localhost:3000/v1/chat/completions" \ -H 'Authorization: AZURE_RESOURCE_ID:AZURE_MODEL_DEPLOYMENT:AZURE_API_KEY:AZURE_API_VERSION' \ @@ -55,14 +58,13 @@ curl -X "POST" "http://localhost:3000/v1/chat/completions" \ "stream": false }' ``` -
-## 已测试应用 +## Tested Applications -以下应用已经过测试，确认可以与 azure-openai-proxy 一起工作： +The azure-openai-proxy has been tested and confirmed to work with the following applications: -| 应用名称 | E2E测试 Docker-compose 文件 | +| Application Name | Docker-compose File for E2E Test | | --------------------------------------------------------------- | --------------------------------------------------------------- | | [chatgpt-lite](https://github.com/blrchen/chatgpt-lite) | [docker-compose.yml](./e2e/chatgpt-lite/docker-compose.yml) | | [chatgpt-next-web](https://github.com/Yidadaa/ChatGPT-Next-Web) | [docker-compose.yml](./e2e/chatgpt-next-web/docker-compose.yml) | @@ -70,37 +72,28 @@ curl -X "POST" "http://localhost:3000/v1/chat/completions" \ | [chatgpt-web](https://github.com/Chanzhaoyu/chatgpt-web) | [docker-compose.yml](./e2e/chatgpt-web/docker-compose.yml) | | [chatgpt-minimal](https://github.com/blrchen/chatgpt-minimal) | [docker-compose.yml](./e2e/chatgpt-minimal/docker-compose.yml) | -要在本地运行测试，请按照以下步骤操作： +To test locally, follow these steps: -1. 在命令行窗口中克隆代码。 -2. 更新环境变量`OPENAPI_API_KEY`的值为`AZURE_RESOURCE_ID:AZURE_MODEL_DEPLOYMENT:AZURE_API_KEY`。或者，直接在`docker-compose.yml`文件中更新`OPENAPI_API_KEY`值。 -3. 导航到包含要测试的应用程序的`docker-compose.yml`文件所在的目录。 -4. 执行构建命令：`docker-compose build`。 -5. 启动服务：`docker-compose up -d`。 -6. 根据`docker-compose.yml`文件中定义的公开端口，启动应用以在本地进行测试。例如，访问 http://localhost:3000。 +1. Clone the repository in a command-line window. +2. Update the `OPENAI_API_KEY` environment variable with `AZURE_RESOURCE_ID:AZURE_MODEL_DEPLOYMENT:AZURE_API_KEY`. Alternatively, update the OPENAI_API_KEY value in the docker-compose.yml file directly. +3. Navigate to the directory containing the `docker-compose.yml` file for the application you want to test. +4. Execute the build command: `docker-compose build`. +5. Start the service: `docker-compose up -d`. +6. Access the application locally using the port defined in the docker-compose.yml file. For example, visit http://localhost:3000. -## 常见问题 +## FAQs
-Q：什么是`AZURE_RESOURCE_ID`，`AZURE_MODEL_DEPLOYMENT`，`AZURE_API_KEY` -A: 可以在Azure的管理门户里查找，具体见下图标注 - -![resource-and-model](./resource-and-model.jpg) - +Q: What are `AZURE_RESOURCE_ID`,`AZURE_MODEL_DEPLOYMENT`, and `AZURE_API_KEY`? +A: These can be found in the Azure management portal. See the image below for reference: +![resource-and-model](./docs/images/resource-and-model.jpg)
-
-Q: 如何使用gpt-4 and gpt-4-32k模型 -A: 要使用gpt-4 and gpt-4-32k模型，请使用下列格式的key: - +Q: How can I use gpt-4 and gpt-4-32k models? +A: To use gpt-4 and gpt-4-32k models, follow the key format below: `AZURE_RESOURCE_ID:gpt-3.5-turbo|AZURE_MODEL_DEPLOYMENT,gpt-4|AZURE_MODEL_DEPLOYMENT,gpt-4-32k|AZURE_MODEL_DEPLOYMENT:AZURE_API_KEY:AZURE_API_VERSION` -
-# 贡献代码方式 - -欢迎提交各种 PR。 - -# 免责声明 +## Contributing -此代码仅供演示和测试目的。 +We welcome all PR submissions. diff --git a/README.zh-CN.md b/README.zh-CN.md new file mode 100644 index 0000000..372f8a9 --- /dev/null +++ b/README.zh-CN.md @@ -0,0 +1,99 @@ +# Azure OpenAI Proxy + +[English](./README.md) | 简体中文 + +Azure OpenAI Proxy 是一个 OpenAI API 的代理工具，能将 OpenAI API 请求转为 Azure OpenAI API 请求，从而让只支持 OpenAI 的应用程序无缝使用 Azure OpenAI。 + +## 使用条件 + +你需要有一个 Azure OpenAI 账户才能使用 Azure OpenAI Proxy。 + +## Azure 部署 + +[![Deploy to Azure](https://aka.ms/deploytoazurebutton)](https://portal.azure.com/#create/Microsoft.Template/uri/https%3A%2F%2Fraw.githubusercontent.com%2Fscalaone%2Fazure-openai-proxy%2Fmain%2Fdeploy%2Fazure-deploy.json) + +请注意： + +- 选择与你的 Azure OpenAI 资源相匹配的区域以获得最佳性能。 +- 如果部署失败是因为 'proxywebapp' 名称已被占用，只需修改资源前缀再重新部署。 +- 已部署的代理应用位于 B1 定价层级的 Azure 网页应用计划下，你可以在部署后在 Azure 门户中进行更新。 + +## Docker 部署 + +要使用Docker进行部署，请执行以下命令： + +```bash +docker run -d -p 3000:3000 scalaone/azure-openai-proxy +``` + +## 本地运行和测试 + +遵循以下步骤： + +1. 安装 NodeJS 18。 +2. 克隆代码到命令行窗口。 +3. 运行 `npm install` 安装依赖项。 +4. 运行 `npm start` 启动应用程序。 +5. 运行下面脚本测试，运行前需要把`AZURE_RESOURCE_ID`，`AZURE_MODEL_DEPLOYMENT`，`AZURE_API_KEY`和`AZURE_API_VERSION`替换，`AZURE_API_VERSION`参数可选，默认是`2023-05-15`。 + +
+测试脚本 +```bash +curl -X "POST" "http://localhost:3000/v1/chat/completions" \ +-H 'Authorization: AZURE_RESOURCE_ID:AZURE_MODEL_DEPLOYMENT:AZURE_API_KEY:AZURE_API_VERSION' \ +-H 'Content-Type: application/json; charset=utf-8' \ +-d $'{ + "messages": [ + { + "role": "system", + "content": "You are an AI assistant that helps people find information." + }, + { + "role": "user", + "content": "hi." + } + ], + "temperature": 1, + "model": "gpt-3.5-turbo", + "stream": false +}' +``` +
+ +## 已测试应用 + +以下应用已经过测试，确认可以与 azure-openai-proxy 一起工作： + +| 应用名称 | E2E测试 Docker-compose 文件 | +| --------------------------------------------------------------- | --------------------------------------------------------------- | +| [chatgpt-lite](https://github.com/blrchen/chatgpt-lite) | [docker-compose.yml](./e2e/chatgpt-lite/docker-compose.yml) | +| [chatgpt-next-web](https://github.com/Yidadaa/ChatGPT-Next-Web) | [docker-compose.yml](./e2e/chatgpt-next-web/docker-compose.yml) | +| [chatbot-ui](https://github.com/mckaywrigley/chatbot-ui) | [docker-compose.yml](./e2e/chatbot-ui/docker-compose.yml) | +| [chatgpt-web](https://github.com/Chanzhaoyu/chatgpt-web) | [docker-compose.yml](./e2e/chatgpt-web/docker-compose.yml) | +| [chatgpt-minimal](https://github.com/blrchen/chatgpt-minimal) | [docker-compose.yml](./e2e/chatgpt-minimal/docker-compose.yml) | + +要在本地运行测试，请按照以下步骤操作： + +1. 在命令行窗口中克隆代码。 +2. 更新环境变量`OPENAI_API_KEY`的值为`AZURE_RESOURCE_ID:AZURE_MODEL_DEPLOYMENT:AZURE_API_KEY`。或者，直接在`docker-compose.yml`文件中更新`OPENAI_API_KEY`值。 +3. 导航到包含要测试的应用程序的`docker-compose.yml`文件所在的目录。 +4. 执行构建命令：`docker-compose build`。 +5. 启动服务：`docker-compose up -d`。 +6. 根据`docker-compose.yml`文件中定义的公开端口，启动应用以在本地进行测试。例如，访问 http://localhost:3000。 + +## 常见问题 + +
+Q：什么是`AZURE_RESOURCE_ID`，`AZURE_MODEL_DEPLOYMENT`，`AZURE_API_KEY` +A: 可以在Azure的管理门户里查找，具体见下图标注 +![resource-and-model](./docs/images/resource-and-model.jpg) +
+
+Q: 如何使用gpt-4 and gpt-4-32k模型 +A: 要使用gpt-4 and gpt-4-32k模型，请使用下列格式的key: +`AZURE_RESOURCE_ID:gpt-3.5-turbo|AZURE_MODEL_DEPLOYMENT,gpt-4|AZURE_MODEL_DEPLOYMENT,gpt-4-32k|AZURE_MODEL_DEPLOYMENT:AZURE_API_KEY:AZURE_API_VERSION` +
+ +## 贡献代码方式 + +欢迎提交各种 PR。 diff --git a/app/layout.tsx b/app/layout.tsx index dda32c1..3baab72 100644 --- a/app/layout.tsx +++ b/app/layout.tsx @@ -1,14 +1,8 @@ -import type { Metadata } from 'next' +import React, { ReactNode } from 'react' import { Inter } from 'next/font/google' const inter = Inter({ subsets: ['latin'] }) - -export const metadata: Metadata = { - title: 'Create Next App', - description: 'Generated by create next app' -} - -export default function RootLayout({ children }: { children: React.ReactNode }) { +export default function RootLayout({ children }: { children: ReactNode }) { return ( {children} diff --git a/app/page.tsx b/app/page.tsx index e458cd7..bc68a71 100644 --- a/app/page.tsx +++ b/app/page.tsx @@ -1,8 +1,3 @@ -import Image from 'next/image' - export default function Home() { - return ( -
-
- ) + return
} diff --git a/app/v1/models/route.ts b/app/v1/models/route.ts index f19c985..bd40f9a 100644 --- a/app/v1/models/route.ts +++ b/app/v1/models/route.ts @@ -1,4 +1,4 @@ -import { NextRequest, NextResponse } from 'next/server' +import { NextResponse } from 'next/server' export async function GET() { const models = { diff --git a/resource-and-model.jpg b/docs/images/resource-and-model.jpg similarity index 100% rename from resource-and-model.jpg rename to docs/images/resource-and-model.jpg