A lightweight open-source project for validating, installing, running, inspecting, and safely removing AI application environment templates on clean Linux servers.
IOE focuses on a practical problem: AI applications are becoming easier to build, but their self-hosted installation steps are still inconsistent across projects.
Current public status: documentation-first preview.
The public installer entrypoints install-ioe.sh and install.sh
are reserved, but they are intentionally inactive until the local preview installer
has passed clean VPS testing.
They do not install packages, download code, start containers, change firewall rules, create users, or modify the host system.
Many self-hosted AI applications ship with their own README, environment variables, ports, data paths, Docker Compose files, scripts, and health check behavior. This works for individual projects, but it creates repeated work for users and maintainers.
IOE aims to provide a small, predictable lifecycle layer around AI application environment templates.
The public standard is centered around a simple lifecycle:
ioectl validate module <module.yaml>
ioectl module install <module.yaml>
ioectl module start <module_id>
ioectl module status <module_id>
ioectl module logs <module_id>
ioectl module stop <module_id>
ioectl module remove <module_id>The goal is not to replace Docker, Docker Compose, Linux package managers, cloud platforms, or existing application frameworks. IOE adds a lightweight standard layer around them.
A consistent module.yaml structure for describing installable AI application environments.
A common set of actions for validation, installation, startup, status, logs, stop, and removal.
Structured output such as --json for scripts, CI systems, and automation tools.
A stable lifecycle surface while runtime details can evolve through adapters.
Clear default locations for application data, backups, and model assets.
Removal should not delete persistent user data unless a destructive action is explicitly requested.
The current public repository is focused on documentation, template standards, example module declarations, contribution rules, and public review safeguards.
The runnable preview installer will be enabled only after clean server testing is completed and documented.
IOE AI Env Installer is released under the MIT License.
Users may review, modify, and use the project according to the license terms.
Contributions should follow the public contribution, review, dependency, template, third-party content, and security guidelines in the GitHub repository.
Templates and scripts should be easy to inspect, safe by default, and clear about what they install, download, run, or remove.
This project provides documentation, standards, examples, and tooling direction for self-hosted AI application environment templates.
Users are responsible for their own server environments, deployed applications, security settings, compliance requirements, and third-party software choices.
The project does not provide guarantees regarding third-party applications, external repositories, user-submitted templates, or deployed workloads.