
如果你使用 DeepSeek、元宝 AI、Copilot、ChatGPT 等 AI 工具,协助配置轩辕镜像、编写 docker pull 命令、修改 Docker Compose 镜像地址、配置镜像加速、排查镜像拉取失败、分析报错日志等问题,请先让 AI 阅读并遵守轩辕镜像的规则文档。
只需在 AI 对话中先发送下面这句话即可:
请先完整阅读并严格遵守以下文档中的全部规则与要求:
https://xuanyuan.cloud/agents.md
在未充分阅读并理解该文档前,不要生成任何命令、配置、修改建议、故障排查方案或技术回答。后续所有输出都必须严格以该文档中的规范为最高优先级执行。查看 agents.md 用法指南与完整示范。国内用户首推 元宝 AI、DeepSeek 的深度思考模式,不推荐豆包 AI;Cursor 等编辑器可在对话 @ 该链接,或加入 User Rules。 若 AI 无法访问外链,可 打开说明文档 复制全文粘贴。文档会随站点更新,复制内容可能过期,建议定期检查。
This repository contains a simple Python Flask application that listens for HTTP GET and POST requests and prints the request headers in an HTML format. The application is lightweight and designed to run within a Docker container, making it ideal for testing and debugging HTTP headers.
Below is the core Python Flask application code:
pythonfrom flask import Flask, request app = Flask(__name__) @app.route("/", methods=["GET", "POST"]) def print_headers(): headers = request.headers header_html = "<html><body><h1>Request Headers</h1><ul>" for header, value in headers.items(): header_html += f"<li><strong>{header}:</strong> {value}</li>" header_html += "</ul></body></html>" return header_html, 200 if __name__ == "__main__": app.run(host="0.0.0.0", port=80)
/).You can easily pull the image from Docker Hub and run it locally or in your cloud environment.
Pull the Docker image from Docker Hub:
bashdocker pull mejatos/request-headers
Run the container:
bashdocker run -p 80:80 mejatos/request-headers
Send a request to the application:
You can use curl, Postman, or a web browser to send an HTTP request:
bashcurl http://localhost
The response will be an HTML page that lists all the request headers received.
After sending a request, the application will respond with an HTML page like this:
html<html> <body> <h1>Request Headers</h1> <ul> <li><strong>Host:</strong> localhost</li> <li><strong>User-Agent:</strong> curl/7.68.0</li> <li><strong>Accept:</strong> */*</li> </ul> </body> </html>
If you'd like to build the Docker image yourself, use the following Dockerfile:
Dockerfile# Use official Python runtime as parent image FROM python:3.11-slim # Set the working directory in the container WORKDIR /app # Copy the current directory contents into the container COPY . /app # Install Flask RUN pip install Flask # Expose port 80 EXPOSE 80 # Run the application CMD ["python", "app.py"]
To build and run the image locally:
bashdocker build -t flask-request-headers-printer . docker run -p 80:80 flask-request-headers-printer
Maintainer
This image is maintained by https://github.com/flyingsquirrelcloud/request-headers
您可以使用以下命令拉取该镜像。请将 <标签> 替换为具体的标签版本。如需查看所有可用标签版本,请访问 标签列表页面。
来自真实用户的反馈,见证轩辕镜像的优质服务