
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 software module written in Java, that can run analytical jobs, to condense raw tracking data from Starwit's Awareness Engine (SAE) into usable knowledge. Software is targeted to be run in a Kubernetes cluster.
This image is supposed to run via https://hub.docker.com/r/starwitorg/urbalytix-chart or https://github.com/starwit/Urbalytix/tree/main/deployment as it needs other components to work.
However to run iamge you can use the following command:
bashdocker run -it --rm -e SPRING_DATASOURCE_URL=jdbc:postgresql://hostname:5432/urbalytix -e SPRING_DATASOURCE_USERNAME=username -e SPRING_DATASOURCE_PASSWORD=password-p 8081:8081 starwitorg/urbalytix:0.0.1
You need to provide coordinates and credentials for a running PostgreSQL instance. Please note, that application uses more data sources and thus more configuration is needed. https://github.com/starwit/Urbalytix for more details.
Project is licensed under AGPL 3 and the license can be found https://github.com/starwit/Urbalytix/blob/main/LICENSE. This component is part of a publicly funded project by the city of Wolfsburg and thus usage in your community is very much encouraged. It is part of a group of software modules that shall help communities to analyze urban space and to gain statistical insights.
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