├── Dockerfile ├── LICENSE ├── README.md ├── README_EN.md ├── app.py ├── build.py ├── center.py ├── concurrent_test.py ├── config.yaml ├── demo ├── Fastgpt_plug-in_get.json └── code_interpreter_openai.py ├── requirements.txt └── static └── swagger.yaml /Dockerfile: -------------------------------------------------------------------------------- 1 | # 第一阶段：构建阶段 2 | FROM python:3.10-slim AS builder 3 | 4 | # 设置工作目录 5 | WORKDIR /app 6 | 7 | # 复制依赖文件 8 | COPY requirements.txt . 9 | 10 | # 安装构建依赖 11 | RUN apt-get update && apt-get install -y \ 12 | build-essential \ 13 | libssl-dev \ 14 | libffi-dev \ 15 | python3-dev \ 16 | && apt-get clean \ 17 | && pip install --no-cache-dir --upgrade pip \ 18 | && pip install --no-cache-dir -r requirements.txt 19 | 20 | # 第二阶段：运行阶段 21 | FROM python:3.10-slim 22 | 23 | # 设置工作目录 24 | WORKDIR /app 25 | 26 | # 从构建阶段复制必要的文件 27 | COPY --from=builder /usr/local/lib/python3.10/site-packages /usr/local/lib/python3.10/site-packages 28 | COPY --from=builder /usr/local/bin /usr/local/bin 29 | COPY . . 30 | 31 | # 设置环境变量 32 | ENV PYTHONUNBUFFERED=1 33 | 34 | # 暴露 Flask 端口 35 | EXPOSE 5000 36 | 37 | # 运行 Flask 应用 38 | CMD ["gunicorn", "-b", "0.0.0.0:5000", "app:app"] 39 | 40 | ARG HTTP_PROXY 41 | ARG HTTPS_PROXY 42 | ARG NO_PROXY 43 | 44 | ENV HTTP_PROXY=${HTTP_PROXY} 45 | ENV HTTPS_PROXY=${HTTPS_PROXY} 46 | ENV NO_PROXY=${NO_PROXY} 47 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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Interpretation of Sections 15 and 16. 613 | 614 | If the disclaimer of warranty and limitation of liability provided 615 | above cannot be given local legal effect according to their terms, 616 | reviewing courts shall apply local law that most closely approximates 617 | an absolute waiver of all civil liability in connection with the 618 | Program, unless a warranty or assumption of liability accompanies a 619 | copy of the Program in return for a fee. 620 | 621 | END OF TERMS AND CONDITIONS 622 | 623 | How to Apply These Terms to Your New Programs 624 | 625 | If you develop a new program, and you want it to be of the greatest 626 | possible use to the public, the best way to achieve this is to make it 627 | free software which everyone can redistribute and change under these terms. 628 | 629 | To do so, attach the following notices to the program. It is safest 630 | to attach them to the start of each source file to most effectively 631 | state the exclusion of warranty; and each file should have at least 632 | the "copyright" line and a pointer to where the full notice is found. 633 | 634 | 635 | Copyright (C) 636 | 637 | This program is free software: you can redistribute it and/or modify 638 | it under the terms of the GNU General Public License as published by 639 | the Free Software Foundation, either version 3 of the License, or 640 | (at your option) any later version. 641 | 642 | This program is distributed in the hope that it will be useful, 643 | but WITHOUT ANY WARRANTY; without even the implied warranty of 644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 645 | GNU General Public License for more details. 646 | 647 | You should have received a copy of the GNU General Public License 648 | along with this program. If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Code Interpreter API 🚀 2 | 3 | [English](https://github.com/leezhuuuuu/Code-Interpreter-Api/blob/main/README_EN.md) | [中文](https://github.com/leezhuuuuu/Code-Interpreter-Api/blob/main/README.md) 4 | 5 | 6 | [![](https://img.shields.io/github/license/leezhuuuuu/Code-Interpreter-Api.svg)](LICENSE) 7 | ![](https://img.shields.io/github/stars/leezhuuuuu/Code-Interpreter-Api.svg) 8 | ![](https://img.shields.io/github/forks/leezhuuuuu/Code-Interpreter-Api.svg) 9 | ![](https://img.shields.io/docker/pulls/leezhuuu/code_interpreter.svg) 10 | 11 | ## 概述 🌟 12 | 13 | Code Interpreter API 是一个集调度中心与沙箱环境于一体的项目，致力于打造全球最好用的代码解释器，旨在提供一个安全、可靠的 API 接口，用于远程运行代码并获取执行结果，加速各类AI Agent开发，是众多AI爱好者的福音。该项目创新性地结合了 Docker 容器技术，实现了对 Python 代码的安全隔离运行。此外，项目还支持将生成的图像数据存储到 PostgreSQL 数据库中，并通过 API 端点进行访问，提供了丰富的数据处理与存储能力。 14 | 您可以在[这里](https://fastgpt.leez.tech/chat/share?shareId=emvjwl8hgqu4pj314k7yakpp)访问由Fastgpt构建的Demo。 15 | 16 | ## 项目状态 📊 17 | 18 | 您可以通过访问我们的[状态监控页面](https://status.leez.tech/)来实时查看本项目的运行状态、性能指标和可用性信息。 19 | 20 | ## 技术栈 🛠️ 21 | 22 | - **后端框架**：Flask (Python) 23 | - **数据库**：PostgreSQL 24 | - **容器化**：Docker 25 | - **ORM**：SQLAlchemy 26 | - **并发处理**：threading, Queue 27 | - **身份验证**：Bearer Token 28 | - **外部请求**：requests 29 | - **代码隔离**：subprocess 30 | 31 | ## 特性 🌈 32 | 33 | - **多语言支持**：目前主要支持 Python 代码的执行。 34 | - **图像处理**：支持将代码生成的图像数据转换为 Base64 格式，并可存储在数据库中。 35 | - **Docker 容器隔离**：每个代码执行请求在独立的 Docker 容器中运行，确保安全性和资源隔离。 36 | - **PostgreSQL 数据库集成**：图像数据可以存储到数据库中，并通过 RESTful API 进行访问。 37 | - **身份验证**：可选的 Bearer 令牌身份验证以确保安全访问。 38 | - **环境变量**：可通过环境变量进行配置。 39 | - **错误处理**：全面的错误处理和超时管理。 40 | 41 | ## 运行环境 🖥️ 42 | 43 | - Python 3.8 及以上 44 | - Docker 45 | - PostgreSQL 46 | 47 | ## 快速开始 🚀 48 | 49 | ### 1. 克隆项目 50 | 51 | ```bash 52 | git clone https://github.com/leezhuuuuu/Code-Interpreter-Api.git 53 | cd Code-Interpreter-Api 54 | ``` 55 | 56 | ### 2. 安装依赖 57 | 58 | ```bash 59 | pip install -r requirements.txt 60 | ``` 61 | 62 | ### 3. 配置文件 63 | 64 | 项目使用 `config.yaml` 作为配置文件。确保该文件中包含以下配置： 65 | 66 | - **域名**：用于访问存储的图像。 67 | - **Docker 镜像**：指定用于运行代码的 Docker 镜像。 68 | - **端口范围**：为 Docker 容器指定端口范围。 69 | - **PostgreSQL 配置**：包括数据库名、用户名、密码、主机和端口。 70 | - **资源限制**：为 Docker 容器指定内存和 CPU 限制。 71 | - **超时时间**：指定代码执行的超时时间。 72 | 73 | ### 4. 获取 Docker 镜像 74 | 75 | 请确保已安装 Docker。然后，您可以根据需要选择以下两种方法之一来获取 Docker 镜像： 76 | 77 | #### 方法一：构建自定义镜像 78 | 79 | 运行 `build.py`，将根据配置文件自动生成 `requirements.txt` 文件并构建自定义镜像，可根据个人需求自定义配置容器环境依赖： 80 | 81 | ```bash 82 | python3 build.py 83 | ``` 84 | 85 | #### 方法二：拉取提前构建好的镜像 86 | 87 | 如果您不想构建镜像，可以直接从 Docker Hub 拉取提前构建好的镜像： 88 | 89 | ```bash 90 | docker pull leezhuuu/code_interpreter:latest 91 | ``` 92 | 93 | ### 5. 启动项目 94 | 95 | 使用以下命令启动项目： 96 | 97 | ```bash 98 | python3 center.py 99 | ``` 100 | 101 | 该命令将自动启动 Flask 应用，并在配置的调度中心端口上运行。 102 | 103 | ## 使用指南 📖 104 | 105 | ### 1. 运行代码 106 | 107 | 通过 POST 或 GET 请求访问 `/runcode` 端点，可以运行指定的代码。请求数据应包含以下字段： 108 | 109 | - **languageType**：代码的语言类型（当前仅支持 Python）。 110 | - **variables**：可选，传递给代码的变量。 111 | - **code**：要执行的代码。 112 | 113 | ### 2. 访问图像 114 | 115 | 通过 GET 请求访问 `/image/` 端点，可以获取存储在数据库中的图像数据。 116 | 117 | ## API 端点 🌐 118 | 119 | ### `POST /runcode` 120 | 121 | #### 请求 122 | 123 | ```json 124 | { 125 | "languageType": "python", 126 | "variables": {}, 127 | "code": "print('Hello, World!')" 128 | } 129 | ``` 130 | 131 | #### 响应 132 | 133 | ```json 134 | { 135 | "output": "Hello, World!\n" 136 | } 137 | ``` 138 | [![Run in Hoppscotch](https://hopp.sh/badge.svg)](https://hopp.sh/r/hqyKw95KDVnl) 139 | 140 | ### `GET /runcode` 141 | 142 | #### 请求 143 | 144 | ``` 145 | /runcode?languageType=python&variables={}&code=print('Hello, World!') 146 | ``` 147 | 148 | #### 响应 149 | 150 | ```json 151 | { 152 | "output": "Hello, World!\n" 153 | } 154 | ``` 155 | [![Run in Hoppscotch](https://hopp.sh/badge.svg)](https://hopp.sh/r/UEkwk6u6Howq) 156 | 157 | ### `POST /runcode` 复杂示例 158 | 159 | #### 请求 160 | 161 | ```json 162 | { 163 | "languageType": "python", 164 | "variables": {}, 165 | "code": "import matplotlib.pyplot as plt\nimport numpy as np\n\n# Define vertices of the triangle\nvertices = np.array([[0, 0], [1, 0], [0.5, np.sqrt(3)/2], [0, 0]])\n\n# Create a new figure\nplt.figure()\n\n# Plot the triangle\nplt.plot(vertices[:, 0], vertices[:, 1], 'b-')\n\n# Set axis limits\nplt.xlim(-0.1, 1.1)\nplt.ylim(-0.1, 1.1)\n\n# Save the plot as triangle.png\nplt.savefig('triangle.png')\nplt.close()" 166 | } 167 | ``` 168 | 169 | #### 响应 170 | 171 | ```json 172 | { 173 | "images": { 174 | "triangle.png": "https://code.leez.tech/image/cec3bee5-c45b-47c5-814f-7dc90831450e_triangle.png" 175 | }, 176 | "output": "" 177 | } 178 | ``` 179 | [![Run in Hoppscotch](https://hopp.sh/badge.svg)](https://hopp.sh/r/8c2Q1nPhuTg3) 180 | 181 | 182 | ## 错误处理 🚨 183 | 184 | 应用程序返回适当的 HTTP 状态码和错误消息以应对不同场景： 185 | 186 | - **400 Bad Request**：无效的 JSON 或参数。 187 | - **401 Unauthorized**：缺失或无效的令牌。 188 | - **405 Method Not Allowed**：无效的 HTTP 方法。 189 | - **504 Gateway Timeout**：请求超时。 190 | 191 | ## Docker 集成 🐳 192 | 193 | 应用程序使用 Docker 在隔离环境中运行代码。您可以选择构建自定义镜像或拉取提前构建好的镜像。 194 | 195 | ## PostgreSQL 集成 🐘 196 | 197 | 代码执行期间生成的图像存储在 PostgreSQL 数据库中。数据库连接详细信息配置在 `config.yaml` 中。 198 | 199 | ## 并发管理 🔄 200 | 201 | 应用程序使用线程处理多个并发请求，并使用信号量控制并发请求的数量。 202 | 203 | ## 测试 🧪 204 | 205 | ### 并发测试 206 | 207 | 应用程序包含一个并发测试脚本 `concurrent_test.py`，可以运行以验证并发功能： 208 | 209 | ```bash 210 | python3 concurrent_test.py 211 | ``` 212 | 213 | ## 许可证 📄 214 | 215 | 本项目基于 GNU 许可证。详见 `LICENSE` 文件。 216 | 217 | ## 贡献 🤝 218 | 219 | 欢迎贡献！请提交问题或拉取请求。 220 | 221 | ## 作者 ✍️ 222 | 223 | - leezhuuuuu 224 | 225 | ## 致谢 🙏 226 | 227 | - Flask 228 | - Docker 229 | - PostgreSQL 230 | - SQLAlchemy 231 | 232 | ## GitHub Star History 233 | 234 | [![Star History Chart](https://api.star-history.com/svg?repos=leezhuuuuu/Code-Interpreter-Api&type=Date)](https://star-history.com/#leezhuuuuu/Code-Interpreter-Api&Date) 235 | 236 | ## 特别鸣谢 237 | 238 | IBM Logo 239 | 240 | 感谢IBM对本项目提供的算力支持。 241 | -------------------------------------------------------------------------------- /README_EN.md: -------------------------------------------------------------------------------- 1 | # Code Interpreter API 🚀 2 | 3 | [English](https://github.com/leezhuuuuu/Code-Interpreter-Api/blob/main/README_EN.md) | [中文](https://github.com/leezhuuuuu/Code-Interpreter-Api/blob/main/README.md) 4 | 5 | [![](https://img.shields.io/github/license/leezhuuuuu/Code-Interpreter-Api.svg)](LICENSE) 6 | ![](https://img.shields.io/github/stars/leezhuuuuu/Code-Interpreter-Api.svg) 7 | ![](https://img.shields.io/github/forks/leezhuuuuu/Code-Interpreter-Api.svg) 8 | ![](https://img.shields.io/docker/pulls/leezhuuu/code_interpreter.svg) 9 | 10 | ## Overview 🌟 11 | 12 | Code Interpreter API is a project that integrates a scheduling center with a sandbox environment, dedicated to creating the world's best code interpreter. It aims to provide a secure and reliable API interface for remotely running code and obtaining execution results, accelerating the development of various AI Agents. This project innovatively combines Docker container technology to achieve secure isolated execution of Python code. Additionally, the project supports storing generated image data in a PostgreSQL database and accessing it through API endpoints, offering rich data processing and storage capabilities. 13 | You can access a demo built with Fastgpt [here](https://fastgpt.leez.tech/chat/share?shareId=emvjwl8hgqu4pj314k7yakpp). 14 | 15 | ## Project Status 📊 16 | 17 | You can view the real-time running status, performance metrics, and availability information of this project by visiting our [status monitoring page](https://status.leez.tech/). 18 | 19 | ## Tech Stack 🛠️ 20 | 21 | - **Backend Framework**: Flask (Python) 22 | - **Database**: PostgreSQL 23 | - **Containerization**: Docker 24 | - **ORM**: SQLAlchemy 25 | - **Concurrency Handling**: threading, Queue 26 | - **Authentication**: Bearer Token 27 | - **External Requests**: requests 28 | - **Code Isolation**: subprocess 29 | 30 | ## Features 🌈 31 | 32 | - **Multi-language Support**: Currently mainly supports Python code execution. 33 | - **Image Processing**: Supports converting code-generated image data to Base64 format and storing it in the database. 34 | - **Docker Container Isolation**: Each code execution request runs in an isolated Docker container, ensuring security and resource isolation. 35 | - **PostgreSQL Database Integration**: Image data can be stored in the database and accessed via RESTful API. 36 | - **Authentication**: Optional Bearer token authentication to ensure secure access. 37 | - **Environment Variables**: Configurable through environment variables. 38 | - **Error Handling**: Comprehensive error handling and timeout management. 39 | 40 | ## Running Environment 🖥️ 41 | 42 | - Python 3.8 and above 43 | - Docker 44 | - PostgreSQL 45 | 46 | ## Quick Start 🚀 47 | 48 | ### 1. Clone the Project 49 | 50 | ```bash 51 | git clone https://github.com/leezhuuuuu/Code-Interpreter-Api.git 52 | cd Code-Interpreter-Api 53 | ``` 54 | 55 | ### 2. Install Dependencies 56 | 57 | ```bash 58 | pip install -r requirements.txt 59 | ``` 60 | 61 | ### 3. Configuration File 62 | 63 | The project uses `config.yaml` as the configuration file. Ensure the file contains the following configurations: 64 | 65 | - **Domain**: For accessing stored images. 66 | - **Docker Image**: Specify the Docker image used for running code. 67 | - **Port Range**: Specify port range for Docker containers. 68 | - **PostgreSQL Configuration**: Including database name, username, password, host, and port. 69 | - **Resource Limits**: Specify memory and CPU limits for Docker containers. 70 | - **Timeout**: Specify timeout for code execution. 71 | 72 | ### 4. Get Docker Image 73 | 74 | Ensure Docker is installed. Then, you can choose one of the following two methods to get the Docker image: 75 | 76 | #### Method 1: Build Custom Image 77 | 78 | Run `build.py`, which will automatically generate a `requirements.txt` file based on the configuration file and build a custom image. You can customize the container environment dependencies according to your needs: 79 | 80 | ```bash 81 | python3 build.py 82 | ``` 83 | 84 | #### Method 2: Pull Pre-built Image 85 | 86 | If you don't want to build the image, you can directly pull the pre-built image from Docker Hub: 87 | 88 | ```bash 89 | docker pull leezhuuu/code_interpreter:latest 90 | ``` 91 | 92 | ### 5. Start the Project 93 | 94 | Use the following command to start the project: 95 | 96 | ```bash 97 | python3 center.py 98 | ``` 99 | 100 | This command will automatically start the Flask application and run it on the configured scheduling center port. 101 | 102 | ## Usage Guide 📖 103 | 104 | ### 1. Run Code 105 | 106 | Access the `/runcode` endpoint via POST or GET request to run specified code. The request data should include the following fields: 107 | 108 | - **languageType**: The language type of the code (currently only supports Python). 109 | - **variables**: Optional, variables to be passed to the code. 110 | - **code**: The code to be executed. 111 | 112 | ### 2. Access Images 113 | 114 | Access the `/image/` endpoint via GET request to retrieve image data stored in the database. 115 | 116 | ## API Endpoints 🌐 117 | 118 | ### `POST /runcode` 119 | 120 | #### Request 121 | 122 | ```json 123 | { 124 | "languageType": "python", 125 | "variables": {}, 126 | "code": "print('Hello, World!')" 127 | } 128 | ``` 129 | 130 | #### Response 131 | 132 | ```json 133 | { 134 | "output": "Hello, World!\n" 135 | } 136 | ``` 137 | [![Run in Hoppscotch](https://hopp.sh/badge.svg)](https://hopp.sh/r/hqyKw95KDVnl) 138 | 139 | ### `GET /runcode` 140 | 141 | #### Request 142 | 143 | ``` 144 | /runcode?languageType=python&variables={}&code=print('Hello, World!') 145 | ``` 146 | 147 | #### Response 148 | 149 | ```json 150 | { 151 | "output": "Hello, World!\n" 152 | } 153 | ``` 154 | [![Run in Hoppscotch](https://hopp.sh/badge.svg)](https://hopp.sh/r/UEkwk6u6Howq) 155 | 156 | ### `POST /runcode` Complex Example 157 | 158 | #### Request 159 | 160 | ```json 161 | { 162 | "languageType": "python", 163 | "variables": {}, 164 | "code": "import matplotlib.pyplot as plt\nimport numpy as np\n\n# Define vertices of the triangle\nvertices = np.array([[0, 0], [1, 0], [0.5, np.sqrt(3)/2], [0, 0]])\n\n# Create a new figure\nplt.figure()\n\n# Plot the triangle\nplt.plot(vertices[:, 0], vertices[:, 1], 'b-')\n\n# Set axis limits\nplt.xlim(-0.1, 1.1)\nplt.ylim(-0.1, 1.1)\n\n# Save the plot as triangle.png\nplt.savefig('triangle.png')\nplt.close()" 165 | } 166 | ``` 167 | 168 | #### Response 169 | 170 | ```json 171 | { 172 | "images": { 173 | "triangle.png": "https://code.leez.tech/image/cec3bee5-c45b-47c5-814f-7dc90831450e_triangle.png" 174 | }, 175 | "output": "" 176 | } 177 | ``` 178 | [![Run in Hoppscotch](https://hopp.sh/badge.svg)](https://hopp.sh/r/8c2Q1nPhuTg3) 179 | 180 | ## Error Handling 🚨 181 | 182 | The application returns appropriate HTTP status codes and error messages for different scenarios: 183 | 184 | - **400 Bad Request**: Invalid JSON or parameters. 185 | - **401 Unauthorized**: Missing or invalid token. 186 | - **405 Method Not Allowed**: Invalid HTTP method. 187 | - **504 Gateway Timeout**: Request timeout. 188 | 189 | ## Docker Integration 🐳 190 | 191 | The application uses Docker to run code in an isolated environment. You can choose to build a custom image or pull a pre-built image. 192 | 193 | ## PostgreSQL Integration 🐘 194 | 195 | Images generated during code execution are stored in the PostgreSQL database. Database connection details are configured in `config.yaml`. 196 | 197 | ## Concurrency Management 🔄 198 | 199 | The application uses threads to handle multiple concurrent requests and uses semaphores to control the number of concurrent requests. 200 | 201 | ## Testing 🧪 202 | 203 | ### Concurrency Testing 204 | 205 | The application includes a concurrency test script `concurrent_test.py` that can be run to verify concurrent functionality: 206 | 207 | ```bash 208 | python3 concurrent_test.py 209 | ``` 210 | 211 | ## License 📄 212 | 213 | This project is licensed under the GNU License. See the `LICENSE` file for details. 214 | 215 | ## Contributing 🤝 216 | 217 | Contributions are welcome! Please submit issues or pull requests. 218 | 219 | ## Author ✍️ 220 | 221 | - leezhuuuuu 222 | 223 | ## Acknowledgements 🙏 224 | 225 | - Flask 226 | - Docker 227 | - PostgreSQL 228 | - SQLAlchemy 229 | 230 | ## GitHub Star History 231 | 232 | [![Star History Chart](https://api.star-history.com/svg?repos=leezhuuuuu/Code-Interpreter-Api&type=Date)](https://star-history.com/#leezhuuuuu/Code-Interpreter-Api&Date) 233 | 234 | ## Special Thanks 235 | 236 | IBM Logo 237 | 238 | Special thanks to IBM for providing computing power support for this project. -------------------------------------------------------------------------------- /app.py: -------------------------------------------------------------------------------- 1 | from flask import Flask, request, jsonify, Response, render_template_string 2 | import subprocess 3 | import sys 4 | import threading 5 | import time 6 | import requests 7 | from functools import wraps 8 | import urllib.parse 9 | import re 10 | import json 11 | import base64 12 | import os 13 | import glob 14 | 15 | app = Flask(__name__) 16 | 17 | # 从环境变量中读取配置，如果未设置则使用默认值 18 | OUTPUT_BASE64 = os.getenv('OUTPUT_BASE64', 'True').lower() == 'true' 19 | AUTH_TOKEN = os.getenv('AUTH_TOKEN', '') 20 | # HOST = os.getenv('HOST', '127.0.0.1') 21 | HOST = os.getenv('HOST', '0.0.0.0') 22 | PORT = int(os.getenv('PORT', 5000)) 23 | TIMEOUT = int(os.getenv('TIMEOUT', 30)) 24 | REMOVE_PYTHON_CODE_BLOCK = os.getenv('REMOVE_PYTHON_CODE_BLOCK', 'True').lower() == 'true' 25 | 26 | # 配置变量，决定是否启用单元测试，默认启用 27 | ENABLE_UNIT_TESTS = False 28 | 29 | def auth_required(f): 30 | @wraps(f) 31 | def decorated(*args, **kwargs): 32 | if AUTH_TOKEN: 33 | auth_header = request.headers.get('Authorization') 34 | if not auth_header or not auth_header.startswith('Bearer '): 35 | return jsonify({'error': 'Authorization header is missing or invalid'}), 401 36 | token = auth_header.split('Bearer ')[1] 37 | if token != AUTH_TOKEN: 38 | return jsonify({'error': 'Invalid token'}), 401 39 | return f(*args, **kwargs) 40 | return decorated 41 | 42 | def extract_code(code): 43 | if REMOVE_PYTHON_CODE_BLOCK: 44 | match = re.search(r'```python\s*(.*?)\s*```', code, re.DOTALL) 45 | if match: 46 | return match.group(1) 47 | return code 48 | 49 | def run_code(language, code, variables, timeout): 50 | try: 51 | # 根据语言类型选择解释器 52 | if language == 'python': 53 | # 提取代码中的有效部分 54 | code = extract_code(code) 55 | # 将变量注入到代码环境中 56 | var_definitions = '\n'.join(f"{key} = {value}" for key, value in variables.items()) 57 | code_with_vars = f"{var_definitions}\n{code}" 58 | # 使用subprocess运行代码 59 | result = subprocess.run([sys.executable, '-c', code_with_vars], capture_output=True, text=True, timeout=timeout) 60 | return result.stdout, result.stderr 61 | elif language == 'bash': 62 | # 将变量注入到bash环境中 63 | env = os.environ.copy() 64 | env.update({key: str(value) for key, value in variables.items()}) 65 | 66 | # 使用subprocess运行bash代码 67 | result = subprocess.run(['bash', '-c', code], capture_output=True, text=True, timeout=timeout, env=env) 68 | return result.stdout, result.stderr 69 | else: 70 | return None, "Unsupported language" 71 | except subprocess.TimeoutExpired: 72 | return None, "Code execution timed out" 73 | except Exception as e: 74 | return None, str(e) 75 | 76 | def convert_image_to_base64(image_path): 77 | with open(image_path, "rb") as image_file: 78 | encoded_string = base64.b64encode(image_file.read()).decode('utf-8') 79 | return encoded_string 80 | 81 | def unescape_string(s): 82 | return s.encode('utf-8').decode('unicode_escape') 83 | 84 | @app.route('/runcode', methods=['POST', 'GET']) 85 | @auth_required 86 | def run_code_endpoint(): 87 | if request.method == 'POST': 88 | data = request.get_json() 89 | if not data: 90 | return jsonify({'error': 'Invalid JSON'}), 400 91 | language = data.get('languageType', 'python') 92 | variables = data.get('variables', {}) 93 | code = data.get('code', '') 94 | elif request.method == 'GET': 95 | query_string = request.query_string.decode('utf-8') 96 | print("Query String:",query_string) 97 | # 检查query_string中是否有"+" 98 | if '+' in query_string: 99 | # query_string的+替换为空格 100 | query_string = re.sub(r'\+', ' ', query_string) 101 | print("Query String:",query_string) 102 | 103 | # 如果没有+，则直接输出query_string 104 | else: 105 | print("Query String:",query_string) 106 | 107 | 108 | # 使用正则表达式提取参数 109 | language_match = re.search(r'languageType=("?)([^"&]+)\1', query_string) 110 | variables_match = re.search(r'variables=("?)([^"&]+)\1', query_string) 111 | code_match = re.search(r'code=("?)([^"&]+)\1', query_string) 112 | print("code_match:",code_match) 113 | if not language_match or not variables_match or not code_match: 114 | return jsonify({'error': 'Invalid parameters'}), 400 115 | 116 | 117 | 118 | language = urllib.parse.unquote(language_match.group(2)) 119 | variables = urllib.parse.unquote(variables_match.group(2)) 120 | code = urllib.parse.unquote(code_match.group(2)) 121 | print("code:",code) 122 | 123 | # 处理转义字符 124 | language = unescape_string(language) 125 | variables = unescape_string(variables) 126 | code = unescape_string(code) 127 | print("code:",code) 128 | 129 | try: 130 | variables = json.loads(variables) 131 | except json.JSONDecodeError: 132 | return jsonify({'error': 'Invalid variables format'}), 400 133 | 134 | # 打印解析后的JSON参数 135 | print("Parsed JSON Parameters:") 136 | print(json.dumps({ 137 | 'languageType': language, 138 | 'variables': variables, 139 | 'code': code 140 | }, indent=4)) 141 | else: 142 | return jsonify({'error': 'Unsupported HTTP method'}), 405 143 | 144 | # 运行代码 145 | stdout, stderr = run_code(language, code, variables, TIMEOUT) 146 | 147 | if stderr: 148 | return jsonify({'error': stderr}), 400 149 | else: 150 | # 查找当前目录中的所有图片文件 151 | image_files = glob.glob('*.png') + glob.glob('*.jpg') + glob.glob('*.jpeg') + glob.glob('*.gif') 152 | 153 | if image_files: 154 | image_data = {} 155 | for image_path in image_files: 156 | encoded_image = convert_image_to_base64(image_path) 157 | image_data[image_path] = encoded_image 158 | os.remove(image_path) # 删除生成的图片文件 159 | 160 | if not OUTPUT_BASE64: 161 | # 如果 OUTPUT_BASE64 不是 True，则输出原始图片 162 | html_content = ''.join([f'{image_path}' for image_path in image_data.keys()]) 163 | return Response(html_content, mimetype='text/html') 164 | 165 | else: 166 | return jsonify({'output': stdout, 'images': image_data}), 200 167 | else: 168 | return jsonify({'output': stdout}), 200 169 | 170 | @app.route('/', methods=['GET']) 171 | def welcome_page(): 172 | return render_template_string('

欢迎使用lee\'s code-interpreter

') 173 | 174 | def run_test_case(test_case): 175 | url = f'http://{HOST}:{PORT}/runcode' 176 | if test_case['method'] == 'GET': 177 | params = { 178 | 'languageType': test_case['language'], 179 | 'variables': test_case['variables'], 180 | 'code': test_case['code'] 181 | } 182 | headers = {'Authorization': f'Bearer {AUTH_TOKEN}'} if AUTH_TOKEN else {} 183 | print("Request Params:") 184 | print(params) 185 | 186 | response = requests.get(url, params=params, headers=headers) 187 | elif test_case['method'] == 'POST': 188 | data = { 189 | 'languageType': test_case['language'], 190 | 'variables': test_case['variables'], 191 | 'code': test_case['code'] 192 | } 193 | headers = {'Authorization': f'Bearer {AUTH_TOKEN}'} if AUTH_TOKEN else {} 194 | print("Request Data:") 195 | print(data) 196 | 197 | response = requests.post(url, json=data, headers=headers) 198 | else: 199 | raise ValueError("Unsupported HTTP method in test case") 200 | 201 | # 打印返回JSON 202 | print("Response JSON:") 203 | print(response.json()) 204 | 205 | def test_run_code_endpoint(): 206 | test_cases = [ 207 | { 208 | 'method': 'GET', 209 | 'language': 'python', 210 | 'variables': str({}), 211 | 'code': "print('Hello, World!')" 212 | }, 213 | { 214 | 'method': 'GET', 215 | 'language': '"python"', 216 | 'variables': str({}), 217 | 'code': '"print(\'Hello, World!\')"' 218 | }, 219 | { 220 | 'method': 'GET', 221 | 'language': 'python', 222 | 'variables': str({}), 223 | 'code': "print('Hello%20World')" 224 | }, 225 | { 226 | 'method': 'POST', 227 | 'language': 'python', 228 | 'variables': {}, 229 | 'code': "print(5 ** 11)" 230 | }, 231 | { 232 | 'method': 'POST', 233 | 'language': 'python', 234 | 'variables': {'m': 7, 'n': 4}, 235 | 'code': "print(m * n)" 236 | }, 237 | { 238 | 'method': 'POST', 239 | 'language': 'python', 240 | 'variables': {}, 241 | 'code': "```python\nprint('Hello from code block!')\n```" 242 | } 243 | ] 244 | 245 | for test_case in test_cases: 246 | run_test_case(test_case) 247 | 248 | if __name__ == '__main__': 249 | # 启动Flask应用 250 | threading.Thread(target=app.run, kwargs={'host': HOST, 'port': PORT, 'debug': False}).start() 251 | 252 | # 等待Flask应用启动 253 | time.sleep(1) 254 | 255 | # 运行单元测试 256 | if ENABLE_UNIT_TESTS: 257 | test_run_code_endpoint() 258 | print("All tests executed!") 259 | -------------------------------------------------------------------------------- /build.py: -------------------------------------------------------------------------------- 1 | import yaml 2 | import subprocess 3 | import os 4 | 5 | # 读取配置文件，指定编码为 utf-8 6 | with open('config.yaml', 'r', encoding='utf-8') as file: 7 | config = yaml.safe_load(file) 8 | 9 | DEPENDENCIES = config['dependencies'] 10 | INTERPRETER_IMAGE = config['interpreter_image'] 11 | # 从配置文件中读取代理设置 12 | HTTP_PROXY = config.get('http_proxy', '') 13 | HTTPS_PROXY = config.get('https_proxy', '') 14 | 15 | # 动态生成 requirements.txt 16 | def generate_requirements(dependencies): 17 | with open('requirements.txt', 'w', encoding='utf-8') as f: 18 | for dep in dependencies: 19 | f.write(f"{dep}\n") 20 | 21 | generate_requirements(DEPENDENCIES) 22 | print("Generated requirements.txt with specified dependencies.") 23 | 24 | # 构建 Docker 镜像 25 | def build_docker_image(image_name): 26 | build_command = [ 27 | "docker", "build", 28 | "--build-arg", f"HTTP_PROXY={HTTP_PROXY}", 29 | "--build-arg", f"HTTPS_PROXY={HTTPS_PROXY}", 30 | "-t", image_name, 31 | "." 32 | ] 33 | 34 | # 设置环境变量 35 | env = os.environ.copy() 36 | if HTTP_PROXY: 37 | env['HTTP_PROXY'] = HTTP_PROXY 38 | if HTTPS_PROXY: 39 | env['HTTPS_PROXY'] = HTTPS_PROXY 40 | 41 | subprocess.run(build_command, check=True, env=env) 42 | print(f"Built Docker image {image_name}") 43 | 44 | build_docker_image(INTERPRETER_IMAGE) 45 | -------------------------------------------------------------------------------- /center.py: -------------------------------------------------------------------------------- 1 | import yaml 2 | import subprocess 3 | import uuid 4 | from flask import Flask, request, jsonify, redirect, url_for 5 | from queue import Queue 6 | import requests 7 | import threading 8 | import time 9 | import os 10 | import atexit 11 | import base64 12 | import signal 13 | from sqlalchemy import create_engine, Column, String, LargeBinary, Integer 14 | from sqlalchemy.orm import declarative_base, sessionmaker 15 | from sqlalchemy.exc import OperationalError, IntegrityError 16 | import psycopg2 17 | from flask_swagger_ui import get_swaggerui_blueprint 18 | 19 | app = Flask(__name__) 20 | 21 | # 读取配置文件，指定编码为 utf-8 22 | with open('config.yaml', 'r', encoding='utf-8') as file: 23 | config = yaml.safe_load(file) 24 | 25 | DOMAIN = config['domain'] 26 | INTERPRETER_IMAGE = config['interpreter_image'] 27 | PORT_START = config['interpreter_port_range']['start'] 28 | PORT_END = config['interpreter_port_range']['end'] 29 | DEPENDENCIES = config['dependencies'] 30 | RESOURCE_LIMITS = config.get('resource_limits', {}) 31 | MEMORY_LIMIT = RESOURCE_LIMITS.get('memory') 32 | CPU_LIMIT = RESOURCE_LIMITS.get('cpus') 33 | POSTGRES = config['postgres'] 34 | TIMEOUT = config.get('timeout', 30) # 默认超时时间为30秒 35 | TIMEOUT_SECONDS = config.get('timeout_seconds', 60) # 从配置中读取超时时间 36 | SCHEDULER_PORT = config['scheduler_port'] # 自定义调度中心端口 37 | HOST = config.get('host', '0.0.0.0') # 自定义 host 地址 38 | 39 | # 容器管理 40 | containers = [] 41 | ports = list(range(PORT_START, PORT_END + 1)) 42 | lock = threading.Lock() 43 | request_queue = Queue() 44 | result_dict = {} # 用于存储结果的字典 45 | current_container_index = 0 46 | semaphore = threading.Semaphore(len(ports)) # 控制并发请求的信号量 47 | 48 | # 检查 PostgreSQL 容器是否存在 49 | POSTGRES_CONTAINER_NAME = "postgres_code_interpreter" 50 | POSTGRES_VOLUME_NAME = "postgres_code_interpreter_volume" 51 | 52 | def is_postgres_container_running(): 53 | result = subprocess.run(["docker", "ps", "-a", "--filter", f"name={POSTGRES_CONTAINER_NAME}", "--format", "{{.Names}}"], capture_output=True, text=True) 54 | return POSTGRES_CONTAINER_NAME in result.stdout.strip().split('\n') 55 | 56 | def wait_for_postgres_ready(): 57 | retry_attempts = 10 58 | retry_delay = 5 # seconds 59 | for attempt in range(retry_attempts): 60 | try: 61 | conn = psycopg2.connect( 62 | dbname=POSTGRES['db'], 63 | user=POSTGRES['user'], 64 | password=POSTGRES['password'], 65 | host=POSTGRES['host'], 66 | port=POSTGRES['port'] 67 | ) 68 | conn.close() 69 | print("PostgreSQL is ready") 70 | return True 71 | except psycopg2.OperationalError as e: 72 | print(f"Waiting for PostgreSQL to be ready: {e}") 73 | time.sleep(retry_delay) 74 | return False 75 | 76 | if not is_postgres_container_running(): 77 | subprocess.run([ 78 | "docker", "run", "--name", POSTGRES_CONTAINER_NAME, "-d", 79 | "-e", f"POSTGRES_USER={POSTGRES['user']}", 80 | "-e", f"POSTGRES_PASSWORD={POSTGRES['password']}", 81 | "-e", f"POSTGRES_DB={POSTGRES['db']}", 82 | "-v", f"{POSTGRES_VOLUME_NAME}:/var/lib/postgresql/data", 83 | "-p", f"{POSTGRES['port']}:5432", 84 | "postgres" 85 | ], check=True) 86 | 87 | if not wait_for_postgres_ready(): 88 | print("Failed to connect to PostgreSQL after multiple attempts.") 89 | exit(1) 90 | 91 | # PostgreSQL 配置 92 | DATABASE_URL = f"postgresql://{POSTGRES['user']}:{POSTGRES['password']}@{POSTGRES['host']}:{POSTGRES['port']}/{POSTGRES['db']}" 93 | engine = None 94 | Base = declarative_base() 95 | Session = None 96 | session = None 97 | 98 | def init_db(): 99 | global engine, Session, session 100 | retry_attempts = 5 101 | retry_delay = 5 # seconds 102 | for attempt in range(retry_attempts): 103 | try: 104 | engine = create_engine(DATABASE_URL) 105 | Session = sessionmaker(bind=engine) 106 | session = Session() 107 | Base.metadata.create_all(engine) # 确保数据库模式已创建 108 | print("Database connection successful") 109 | break 110 | except OperationalError as e: 111 | print(f"Database connection failed: {e}") 112 | if attempt < retry_attempts - 1: 113 | print(f"Retrying in {retry_delay} seconds...") 114 | time.sleep(retry_delay) 115 | else: 116 | print("Failed to connect to the database after multiple attempts.") 117 | raise 118 | 119 | class Image(Base): 120 | __tablename__ = 'images' 121 | id = Column(Integer, primary_key=True, autoincrement=True) 122 | filename = Column(String, unique=True, nullable=False) 123 | data = Column(LargeBinary, nullable=False) 124 | 125 | init_db() 126 | 127 | # 启动代码解释器容器 128 | def start_container(port): 129 | container_name = f"code_interpreter_docker_{uuid.uuid4()}" 130 | run_command = [ 131 | "docker", "run", "--name", container_name, "-d", "-p", f"{HOST}:{port}:5000" 132 | ] 133 | if MEMORY_LIMIT: 134 | run_command.extend(["--memory", MEMORY_LIMIT]) 135 | if CPU_LIMIT: 136 | run_command.extend(["--cpus", CPU_LIMIT]) 137 | run_command.append(INTERPRETER_IMAGE) 138 | 139 | subprocess.run(run_command, check=True) 140 | print(f"Started container {container_name} on port {port}") 141 | return container_name, port 142 | 143 | def stop_container(container_name): 144 | subprocess.run(["docker", "stop", container_name]) 145 | subprocess.run(["docker", "rm", container_name]) 146 | print(f"Stopped and removed container {container_name}") 147 | 148 | def start_containers(): 149 | for port in ports: 150 | container_name, port = start_container(port) 151 | containers.append((container_name, port)) 152 | 153 | def stop_containers(): 154 | for container_name, _ in containers: 155 | stop_container(container_name) 156 | 157 | @app.route('/runcode', methods=['POST', 'GET']) 158 | def run_code(): 159 | if request.method == 'POST': 160 | data = request.get_json() 161 | if not data: 162 | return jsonify({'error': 'Invalid JSON'}), 400 163 | elif request.method == 'GET': 164 | query_string = request.query_string.decode('utf-8') 165 | data = {'query_string': query_string} 166 | else: 167 | return jsonify({'error': 'Invalid request method'}), 405 168 | 169 | request_id = str(uuid.uuid4()) # 生成一个唯一的请求ID 170 | request_queue.put((request_id, data)) 171 | 172 | start_time = time.time() 173 | while time.time() - start_time < 10: # 最多等待10秒 174 | if request_id in result_dict: 175 | output = result_dict.pop(request_id) 176 | # 处理返回结果，替换 base64 数据为链接 177 | if 'images' in output: 178 | try: 179 | output = process_images(output) 180 | except Exception as e: 181 | return jsonify({'error': str(e)}), 500 182 | return jsonify(output), 200 183 | 184 | time.sleep(0.1) 185 | 186 | return jsonify({'error': 'Request timed out'}), 504 187 | 188 | def process_images(output): 189 | images = output['images'] 190 | for filename, base64_data in images.items(): 191 | image_data = base64.b64decode(base64_data) 192 | unique_filename = f"{uuid.uuid4()}_{filename}" 193 | image_record = Image(filename=unique_filename, data=image_data) 194 | try: 195 | session.add(image_record) 196 | session.commit() 197 | except IntegrityError as e: 198 | session.rollback() 199 | print(f"Database error: {e}") 200 | continue 201 | if DOMAIN: 202 | images[filename] = f"https://{DOMAIN}/image/{unique_filename}" 203 | else: 204 | images[filename] = f"http://{HOST}:{SCHEDULER_PORT}/image/{unique_filename}" 205 | return output 206 | 207 | @app.route('/image/', methods=['GET']) 208 | def serve_image(filename): 209 | image_record = session.query(Image).filter_by(filename=filename).first() 210 | if image_record: 211 | return image_record.data, 200, {'Content-Type': 'image/png'} 212 | return jsonify({'error': 'Image not found'}), 404 213 | 214 | def handle_requests(): 215 | global current_container_index 216 | while True: 217 | request_id, data = request_queue.get() 218 | if data is None: 219 | break 220 | 221 | semaphore.acquire() # 获取信号量，确保不超过并发限制 222 | 223 | with lock: 224 | container_name, port = containers[current_container_index] 225 | current_container_index = (current_container_index + 1) % len(containers) 226 | 227 | try: 228 | if 'query_string' in data: 229 | response = requests.get(f"http://{HOST}:{port}/runcode?{data['query_string']}", timeout=TIMEOUT_SECONDS) 230 | else: 231 | response = requests.post(f"http://{HOST}:{port}/runcode", json=data, timeout=TIMEOUT_SECONDS) 232 | output = response.json() 233 | except requests.exceptions.Timeout: 234 | output = {'error': 'Code execution timed out'} 235 | except Exception as e: 236 | output = {'error': str(e)} 237 | 238 | result_dict[request_id] = output # 将结果放入结果字典 239 | 240 | request_queue.task_done() 241 | print(f"Finished processing request {request_id}: {output}") 242 | 243 | # 异步重置容器 244 | reset_container(container_name, port) 245 | 246 | def reset_container(container_name, port): 247 | threading.Thread(target=_reset_container, args=(container_name, port)).start() 248 | 249 | def _reset_container(container_name, port): 250 | print(f"Resetting container {container_name}") 251 | stop_container(container_name) 252 | new_container_name, _ = start_container(port) 253 | with lock: 254 | for i, (name, p) in enumerate(containers): 255 | if name == container_name: 256 | containers[i] = (new_container_name, port) 257 | break 258 | semaphore.release() # 释放信号量 259 | 260 | def signal_handler(signal, frame): 261 | print('Stopping containers and exiting program...') 262 | stop_containers() 263 | if session: 264 | session.close() 265 | engine.dispose() 266 | os._exit(0) 267 | 268 | signal.signal(signal.SIGINT, signal_handler) 269 | 270 | # 启动多个工作线程来处理请求 271 | for _ in range(len(ports)): 272 | threading.Thread(target=handle_requests).start() 273 | 274 | start_containers() 275 | atexit.register(stop_containers) 276 | 277 | @app.route('/') 278 | def index(): 279 | return redirect("https://github.com/leezhuuuuu/Code-Interpreter-Api") 280 | 281 | # Swagger 配置 282 | SWAGGER_URL = '/doc' # Swagger UI 的 URL 283 | API_URL = '/static/swagger.yaml' # Swagger 配置文件的 URL 284 | 285 | # 动态设置 Swagger UI 的默认请求地址 286 | swagger_config = { 287 | 'app_name': "Code Interpreter API", 288 | 'urls.primaryName': "Code Interpreter API", 289 | 'urls.primaryValue': f"https://{DOMAIN}" if DOMAIN else f"http://{HOST}:{SCHEDULER_PORT}" 290 | } 291 | 292 | # 创建 Swagger UI 蓝图 293 | swaggerui_blueprint = get_swaggerui_blueprint( 294 | SWAGGER_URL, 295 | API_URL, 296 | config=swagger_config # 使用动态配置 297 | ) 298 | 299 | app.register_blueprint(swaggerui_blueprint, url_prefix=SWAGGER_URL) 300 | 301 | if __name__ == '__main__': 302 | app.run(host=HOST, port=SCHEDULER_PORT, threaded=True) # 使用自定义 host 和调度中心端口 -------------------------------------------------------------------------------- /concurrent_test.py: -------------------------------------------------------------------------------- 1 | import aiohttp 2 | import asyncio 3 | 4 | async def post_request(session, url, headers, json_data): 5 | async with session.post(url, headers=headers, json=json_data) as response: 6 | response_text = await response.text() 7 | print(response_text) 8 | return response_text 9 | 10 | async def main(concurrent_requests): 11 | url = 'http://127.0.0.1:8000/runcode' 12 | headers = { 13 | 'User-Agent': 'Apifox/1.0.0 (https://apifox.com)', 14 | 'Content-Type': 'application/json', 15 | 'Authorization': 'Bearer 114514', 16 | 'Accept': '*/*', 17 | 'Host': '127.0.0.1:8000', 18 | 'Connection': 'keep-alive' 19 | } 20 | json_data = { 21 | "languageType": "python", 22 | "variables": {}, 23 | "code": "```python\nimport time\nprint('Hello from code block!')\ntime.sleep(3)\n```" 24 | } 25 | 26 | async with aiohttp.ClientSession() as session: 27 | tasks = [post_request(session, url, headers, json_data) for _ in range(concurrent_requests)] 28 | await asyncio.gather(*tasks) 29 | 30 | if __name__ == '__main__': 31 | concurrent_requests = 5 # 设置并发数 32 | asyncio.run(main(concurrent_requests)) 33 | -------------------------------------------------------------------------------- /config.yaml: -------------------------------------------------------------------------------- 1 | domain: "" #填写域名后对外提供链接将使用域名替代 ip:scheduler_port 2 | interpreter_image: "leezhuuu/code_interpreter" 3 | scheduler_port: 5000 # 调度中心自定义端口 4 | host: "0.0.0.0" # 调度中心自定义 host 地址 5 | interpreter_port_range: # 设置端口范围为 8001-8003，端口范围决定容器数量 6 | start: 8001 7 | end: 8003 8 | dependencies: # 定义容器的依赖项，以下为默认依赖项,可以根据需要自行更改，仅在生成自定义镜像时生效 9 | - numpy 10 | - pandas 11 | - scipy 12 | - matplotlib 13 | - seaborn 14 | - scikit-learn 15 | - opencv-python 16 | - opencv-python-headless 17 | - Pillow 18 | - requests 19 | - Flask 20 | - pyyaml 21 | - sympy 22 | - plotly 23 | - bokeh 24 | - statsmodels 25 | - jupyter 26 | - ipython 27 | - jupyterlab 28 | - pytest 29 | - hypothesis 30 | - Flask-Cors 31 | - Werkzeug 32 | - Gunicorn 33 | - handcalcs 34 | resource_limits: 35 | memory: "" # 可以自定义内存限制，例如 "2g"、"500m" 等，不填则默认不进行限制 36 | cpus: "" # 可以自定义 CPU 限制，例如 "1.5"、"0.5" 等，不填则默认不进行限制 37 | timeout_seconds: 60 # 设置超时时间为 1 分钟（60 秒） 38 | postgres: 39 | user: "user" # 数据库用户名,请自行更改 40 | password: "password" # 数据库密码,请自行更改 41 | db: "code_interpreter_db" 42 | host: "localhost" 43 | port: "5432" # 数据库端口,请自行更改 44 | mode: "docker" # 选择运行模式，可以是 "docker"、"podman" 或 "k8s"，k8s模式正在开发中 45 | kubeconfig_path: "/path/to/kubeconfig.yaml" # Kubernetes 配置文件路径 46 | k8s_interpreter_yaml: "/path/to/code-interpreter.yaml" # Kubernetes 部署配置文件路径 47 | -------------------------------------------------------------------------------- /demo/Fastgpt_plug-in_get.json: -------------------------------------------------------------------------------- 1 | { 2 | "nodes": [ 3 | { 4 | "nodeId": "pluginInput", 5 | "name": "自定义插件输入", 6 | "intro": "可以配置插件需要哪些输入，利用这些输入来运行插件", 7 | "avatar": "core/workflow/template/workflowStart", 8 | "flowNodeType": "pluginInput", 9 | "showStatus": false, 10 | "position": { 11 | "x": 355.26262363800697, 12 | "y": -185.4640717105371 13 | }, 14 | "version": "481", 15 | "inputs": [ 16 | { 17 | "renderTypeList": [ 18 | "JSONEditor" 19 | ], 20 | "selectedTypeIndex": 0, 21 | "valueType": "string", 22 | "canEdit": true, 23 | "key": "code", 24 | "label": "code", 25 | "description": "代码解释器执行所需要的python代码片段", 26 | "required": true, 27 | "defaultValue": "print(\"hello,world!\")", 28 | "toolDescription": "代码解释器执行所需要的python代码片段" 29 | }, 30 | { 31 | "renderTypeList": [ 32 | "JSONEditor" 33 | ], 34 | "selectedTypeIndex": 0, 35 | "valueType": "string", 36 | "canEdit": true, 37 | "key": "languageType", 38 | "label": "languageType", 39 | "description": "需要运行的编程语言类型，默认为python", 40 | "required": true, 41 | "defaultValue": "python" 42 | }, 43 | { 44 | "renderTypeList": [ 45 | "JSONEditor" 46 | ], 47 | "selectedTypeIndex": 0, 48 | "valueType": "string", 49 | "canEdit": true, 50 | "key": "variables", 51 | "label": "variables", 52 | "description": "代码解释器运行时所设置的变量", 53 | "required": false, 54 | "defaultValue": "{\"m\": 7,\"n\": 4}", 55 | "toolDescription": "代码解释器运行时所设置的变量" 56 | } 57 | ], 58 | "outputs": [ 59 | { 60 | "id": "code", 61 | "valueType": "string", 62 | "key": "code", 63 | "label": "code", 64 | "type": "hidden" 65 | }, 66 | { 67 | "id": "languageType", 68 | "valueType": "string", 69 | "key": "languageType", 70 | "label": "languageType", 71 | "type": "hidden" 72 | }, 73 | { 74 | "id": "variables", 75 | "valueType": "string", 76 | "key": "variables", 77 | "label": "variables", 78 | "type": "hidden" 79 | } 80 | ] 81 | }, 82 | { 83 | "nodeId": "pluginOutput", 84 | "name": "自定义插件输出", 85 | "intro": "自定义配置外部输出，使用插件时，仅暴露自定义配置的输出", 86 | "avatar": "core/workflow/template/pluginOutput", 87 | "flowNodeType": "pluginOutput", 88 | "showStatus": false, 89 | "position": { 90 | "x": 1670.1337182171503, 91 | "y": -158.4298364770928 92 | }, 93 | "version": "481", 94 | "inputs": [ 95 | { 96 | "renderTypeList": [ 97 | "reference" 98 | ], 99 | "valueType": "string", 100 | "canEdit": true, 101 | "key": "output", 102 | "label": "output", 103 | "description": "", 104 | "value": [ 105 | "sNGG0lGPN09Z", 106 | "is2e10Qdqgbe" 107 | ] 108 | }, 109 | { 110 | "renderTypeList": [ 111 | "reference" 112 | ], 113 | "valueType": "string", 114 | "canEdit": true, 115 | "key": "images", 116 | "label": "images", 117 | "description": "如果程序有图片生成时，images返回图片对应的链接", 118 | "value": [ 119 | "sNGG0lGPN09Z", 120 | "chi2PEIP0ity" 121 | ] 122 | } 123 | ], 124 | "outputs": [] 125 | }, 126 | { 127 | "nodeId": "sNGG0lGPN09Z", 128 | "name": "HTTP 请求", 129 | "intro": "可以发出一个 HTTP 请求，实现更为复杂的操作（联网搜索、数据库查询等）", 130 | "avatar": "core/workflow/template/httpRequest", 131 | "flowNodeType": "httpRequest468", 132 | "showStatus": true, 133 | "position": { 134 | "x": 1098.1937779736922, 135 | "y": -404.10745204326895 136 | }, 137 | "version": "481", 138 | "inputs": [ 139 | { 140 | "key": "system_addInputParam", 141 | "renderTypeList": [ 142 | "addInputParam" 143 | ], 144 | "valueType": "dynamic", 145 | "label": "", 146 | "required": false, 147 | "description": "core.module.input.description.HTTP Dynamic Input", 148 | "customInputConfig": { 149 | "selectValueTypeList": [ 150 | "string", 151 | "number", 152 | "boolean", 153 | "object", 154 | "arrayString", 155 | "arrayNumber", 156 | "arrayBoolean", 157 | "arrayObject", 158 | "any", 159 | "chatHistory", 160 | "datasetQuote", 161 | "dynamic", 162 | "selectApp", 163 | "selectDataset" 164 | ], 165 | "showDescription": false, 166 | "showDefaultValue": true 167 | } 168 | }, 169 | { 170 | "key": "system_httpMethod", 171 | "renderTypeList": [ 172 | "custom" 173 | ], 174 | "valueType": "string", 175 | "label": "", 176 | "value": "GET", 177 | "required": true 178 | }, 179 | { 180 | "key": "system_httpReqUrl", 181 | "renderTypeList": [ 182 | "hidden" 183 | ], 184 | "valueType": "string", 185 | "label": "", 186 | "description": "core.module.input.description.Http Request Url", 187 | "placeholder": "https://api.ai.com/getInventory", 188 | "required": false, 189 | "value": "https://code.leez.tech/runcode" 190 | }, 191 | { 192 | "key": "system_httpHeader", 193 | "renderTypeList": [ 194 | "custom" 195 | ], 196 | "valueType": "any", 197 | "value": [], 198 | "label": "", 199 | "description": "core.module.input.description.Http Request Header", 200 | "placeholder": "core.module.input.description.Http Request Header", 201 | "required": false 202 | }, 203 | { 204 | "key": "system_httpParams", 205 | "renderTypeList": [ 206 | "hidden" 207 | ], 208 | "valueType": "any", 209 | "value": [ 210 | { 211 | "key": "code", 212 | "type": "string", 213 | "value": "{{code}}" 214 | }, 215 | { 216 | "key": "languageType", 217 | "type": "string", 218 | "value": "{{languageType}}" 219 | }, 220 | { 221 | "key": "variables", 222 | "type": "string", 223 | "value": "{{variables}}" 224 | } 225 | ], 226 | "label": "", 227 | "required": false 228 | }, 229 | { 230 | "key": "system_httpJsonBody", 231 | "renderTypeList": [ 232 | "hidden" 233 | ], 234 | "valueType": "any", 235 | "value": "", 236 | "label": "", 237 | "required": false 238 | }, 239 | { 240 | "renderTypeList": [ 241 | "reference" 242 | ], 243 | "valueType": "string", 244 | "canEdit": true, 245 | "key": "code", 246 | "label": "code", 247 | "customInputConfig": { 248 | "selectValueTypeList": [ 249 | "string", 250 | "number", 251 | "boolean", 252 | "object", 253 | "arrayString", 254 | "arrayNumber", 255 | "arrayBoolean", 256 | "arrayObject", 257 | "any", 258 | "chatHistory", 259 | "datasetQuote", 260 | "dynamic", 261 | "selectApp", 262 | "selectDataset" 263 | ], 264 | "showDescription": false, 265 | "showDefaultValue": true 266 | }, 267 | "required": true, 268 | "value": [ 269 | "pluginInput", 270 | "code" 271 | ] 272 | }, 273 | { 274 | "renderTypeList": [ 275 | "reference" 276 | ], 277 | "valueType": "string", 278 | "canEdit": true, 279 | "key": "languageType", 280 | "label": "languageType", 281 | "customInputConfig": { 282 | "selectValueTypeList": [ 283 | "string", 284 | "number", 285 | "boolean", 286 | "object", 287 | "arrayString", 288 | "arrayNumber", 289 | "arrayBoolean", 290 | "arrayObject", 291 | "any", 292 | "chatHistory", 293 | "datasetQuote", 294 | "dynamic", 295 | "selectApp", 296 | "selectDataset" 297 | ], 298 | "showDescription": false, 299 | "showDefaultValue": true 300 | }, 301 | "required": true, 302 | "value": [ 303 | "pluginInput", 304 | "languageType" 305 | ] 306 | }, 307 | { 308 | "renderTypeList": [ 309 | "reference" 310 | ], 311 | "valueType": "string", 312 | "canEdit": true, 313 | "key": "variables", 314 | "label": "variables", 315 | "customInputConfig": { 316 | "selectValueTypeList": [ 317 | "string", 318 | "number", 319 | "boolean", 320 | "object", 321 | "arrayString", 322 | "arrayNumber", 323 | "arrayBoolean", 324 | "arrayObject", 325 | "any", 326 | "chatHistory", 327 | "datasetQuote", 328 | "dynamic", 329 | "selectApp", 330 | "selectDataset" 331 | ], 332 | "showDescription": false, 333 | "showDefaultValue": true 334 | }, 335 | "required": true, 336 | "value": [ 337 | "pluginInput", 338 | "variables" 339 | ] 340 | } 341 | ], 342 | "outputs": [ 343 | { 344 | "id": "error", 345 | "key": "error", 346 | "label": "请求错误", 347 | "description": "HTTP请求错误信息，成功时返回空", 348 | "valueType": "object", 349 | "type": "static" 350 | }, 351 | { 352 | "id": "httpRawResponse", 353 | "key": "httpRawResponse", 354 | "label": "原始响应", 355 | "required": true, 356 | "description": "HTTP请求的原始响应。只能接受字符串或JSON类型响应数据。", 357 | "valueType": "any", 358 | "type": "static" 359 | }, 360 | { 361 | "id": "system_addOutputParam", 362 | "key": "system_addOutputParam", 363 | "type": "dynamic", 364 | "valueType": "dynamic", 365 | "label": "", 366 | "customFieldConfig": { 367 | "selectValueTypeList": [ 368 | "string", 369 | "number", 370 | "boolean", 371 | "object", 372 | "arrayString", 373 | "arrayNumber", 374 | "arrayBoolean", 375 | "arrayObject", 376 | "any", 377 | "chatHistory", 378 | "datasetQuote", 379 | "dynamic", 380 | "selectApp", 381 | "selectDataset" 382 | ], 383 | "showDescription": false, 384 | "showDefaultValue": false 385 | } 386 | }, 387 | { 388 | "id": "is2e10Qdqgbe", 389 | "valueType": "string", 390 | "type": "dynamic", 391 | "key": "output", 392 | "label": "output" 393 | }, 394 | { 395 | "id": "chi2PEIP0ity", 396 | "valueType": "string", 397 | "type": "dynamic", 398 | "key": "images", 399 | "label": "images" 400 | } 401 | ] 402 | } 403 | ], 404 | "edges": [ 405 | { 406 | "source": "pluginInput", 407 | "target": "sNGG0lGPN09Z", 408 | "sourceHandle": "pluginInput-source-right", 409 | "targetHandle": "sNGG0lGPN09Z-target-left" 410 | }, 411 | { 412 | "source": "sNGG0lGPN09Z", 413 | "target": "pluginOutput", 414 | "sourceHandle": "sNGG0lGPN09Z-source-right", 415 | "targetHandle": "pluginOutput-target-left" 416 | } 417 | ] 418 | } -------------------------------------------------------------------------------- /demo/code_interpreter_openai.py: -------------------------------------------------------------------------------- 1 | import json 2 | import requests 3 | 4 | # API endpoint 5 | API_ENDPOINT = "https://api.openai.com/v1/chat/completions" 6 | # Your API key 7 | API_KEY = 'sk-xxxxxx' 8 | # Model to use 9 | MODEL = 'gpt-4o' 10 | 11 | def run_program(code): 12 | """Run a given Python program and return the output""" 13 | try: 14 | # Prepare the request payload 15 | payload = { 16 | "languageType": "python", 17 | "variables": {}, 18 | "code": code 19 | } 20 | 21 | # Send the request to the code execution endpoint 22 | response = requests.post("https://code.leez.tech/runcode", json=payload) 23 | 24 | # Parse the response 25 | response_json = response.json() 26 | result = {} 27 | if "output" in response_json: 28 | result["output"] = response_json["output"] 29 | if "images" in response_json: 30 | result["images"] = response_json["images"] 31 | 32 | # Print the response from https://code.leez.tech/runcode 33 | print("Response from https://code.leez.tech/runcode:") 34 | print(json.dumps(response_json, indent=4)) 35 | 36 | return json.dumps(result) 37 | except Exception as e: 38 | return json.dumps({"error": str(e)}) 39 | 40 | def run_conversation(user_prompt): 41 | messages = [ 42 | { 43 | "role": "system", 44 | "content": "You are a programming assistant. Use the run_program function to execute code and provide the results." 45 | }, 46 | { 47 | "role": "user", 48 | "content": user_prompt, 49 | } 50 | ] 51 | tools = [ 52 | { 53 | "type": "function", 54 | "function": { 55 | "name": "run_program", 56 | "description": "Run a given Python program and return the output", 57 | "parameters": { 58 | "type": "object", 59 | "properties": { 60 | "code": { 61 | "type": "string", 62 | "description": "The Python code to execute", 63 | } 64 | }, 65 | "required": ["code"], 66 | }, 67 | }, 68 | } 69 | ] 70 | request_json = { 71 | "model": MODEL, 72 | "messages": messages, 73 | "tools": tools, 74 | "tool_choice": "auto", 75 | "max_tokens": 4096 76 | } 77 | 78 | # Print the request JSON 79 | print("Request JSON:") 80 | print(json.dumps(request_json, indent=4)) 81 | 82 | # Send the request to the API 83 | headers = { 84 | "Content-Type": "application/json", 85 | "Authorization": f"Bearer {API_KEY}" 86 | } 87 | response = requests.post(API_ENDPOINT, headers=headers, data=json.dumps(request_json)) 88 | 89 | # Print the response JSON 90 | print("Response JSON:") 91 | response_json = response.json() 92 | print(json.dumps(response_json, indent=4)) 93 | 94 | response_message = response_json['choices'][0]['message'] 95 | tool_calls = response_message.get('tool_calls', []) 96 | if tool_calls: 97 | available_functions = { 98 | "run_program": run_program, 99 | } 100 | messages.append(response_message) 101 | for tool_call in tool_calls: 102 | function_name = tool_call['function']['name'] 103 | function_to_call = available_functions[function_name] 104 | function_args = json.loads(tool_call['function']['arguments']) 105 | function_response = function_to_call( 106 | code=function_args.get("code") 107 | ) 108 | messages.append( 109 | { 110 | "tool_call_id": tool_call['id'], 111 | "role": "tool", 112 | "name": function_name, 113 | "content": function_response, 114 | } 115 | ) 116 | second_request_json = { 117 | "model": MODEL, 118 | "messages": messages 119 | } 120 | 121 | # Print the second request JSON 122 | print("Second Request JSON:") 123 | print(json.dumps(second_request_json, indent=4)) 124 | 125 | # Send the second request to the API 126 | second_response = requests.post(API_ENDPOINT, headers=headers, data=json.dumps(second_request_json)) 127 | 128 | # Print the second response JSON 129 | print("Second Response JSON:") 130 | second_response_json = second_response.json() 131 | print(json.dumps(second_response_json, indent=4)) 132 | 133 | return second_response_json['choices'][0]['message']['content'] 134 | 135 | # user_prompt = "计算9的11次方，并用中文输出结果。" 136 | user_prompt = "使用python生成一个三角形图片" 137 | print(run_conversation(user_prompt)) -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | Flask==2.0.3 2 | PyYAML==5.4.1 3 | SQLAlchemy==1.4.22 4 | psycopg2-binary==2.9.1 5 | requests==2.26.0 6 | werkzeug==2.0.2 -------------------------------------------------------------------------------- /static/swagger.yaml: -------------------------------------------------------------------------------- 1 | openapi: 3.0.0 2 | info: 3 | title: Code Interpreter API 4 | description: API documentation for the Code Interpreter service 5 | version: 1.0.0 6 | servers: 7 | - url: http://{host}:{port} 8 | variables: 9 | host: 10 | default: localhost 11 | port: 12 | default: 5000 13 | paths: 14 | /runcode: 15 | post: 16 | summary: Run code 17 | requestBody: 18 | required: true 19 | content: 20 | application/json: 21 | schema: 22 | type: object 23 | properties: 24 | code: 25 | type: string 26 | example: print("Hello, World!") 27 | responses: 28 | '200': 29 | description: Successful response 30 | content: 31 | application/json: 32 | schema: 33 | type: object 34 | properties: 35 | result: 36 | type: string 37 | '400': 38 | description: Invalid request 39 | '504': 40 | description: Request timed out 41 | /image/{filename}: 42 | get: 43 | summary: Get image by filename 44 | parameters: 45 | - name: filename 46 | in: path 47 | required: true 48 | schema: 49 | type: string 50 | responses: 51 | '200': 52 | description: Successful response 53 | content: 54 | image/png: 55 | schema: 56 | type: string 57 | format: binary 58 | '404': 59 | description: Image not found 60 | --------------------------------------------------------------------------------