Quick start
After emily
has been installed along with its requirements, you can start to use it.
Running emily
Start by running emily
in a terminal. This will provide you with a welcome message as well as a list of available commands.
Welcome to the CLI tool!
Choose an option bewlow, or try running a command:
create a new Emily project
to open a new or existing project
list existing Emily projects
mount or unmount local drive from a project
deploy a project to a server or kubernetes
list, add, configure, and remove servers known by emily
configure an environment
login or logout of your Emily account
emily doctor install Emily's requirements
emily drop <project> drop existing project from Emily list and optionally delete it
emily uninstall uninstall Emily
Run for more information
You can also run on all sub-commands e.g.
or visit the at https://emily.ambolt.io
You can also run emily --help
to get more information about the emily
command along with its subcommands.
You can get more information about any emily
command using the --help
flag.
Building a project
Get started by creating a new project with the emily build
command.
Let's create a simple REST API to begin with.
$ build
Project name: >>
An Emily template is a pre-built template which contains essential software that
can assist in the development of microservices. These templates include various
relevant API endpoints depending on which template you choose.
Which Emily template do you want to use?
| API - Simple project with API set up and ready
| Machine learning API [API, Pytorch] - Machine learning template with API and pytorch
| Machine learning [API, DVC, MLFlow, Pytorch] - Machine learning template with API, Data version control (DVC), MLFlow experiment tracking and pytorch
| Machine learning [gRPC] - Machine learning template with gRPC
| Machine Learning Tracking - Machine learning tracking template
>>
Emily project types are pre-built Docker images which contain essential packages
useful in the development of microservices. These images include only the relevant
packages for the type of project your choose.
Which project type best fits your case?
| Slim (contains essential Machine Learning packages)
| Computer Vision
| Natural Language Processing
>>
Which editor do you want to use?
| Visual Studio Code
| Jupyter Notebook
| Jupyter Lab
>>
Creating a new Emily project in ...
Your project will now be opened. When first opening a project, it might take some time while Emily pulls down the Docker image.
You can see all your emily
projects by running emily list
.