# Preparation
After downloading and installing Qunomon, start developing an AIT based on the template.
## User workflow
The development of AITs can be categorized into three scenarios: ① creating anew from an AIT template, ② updating an already developed AIT, and ③ having developed an AIT but not retaining the data locally. The workflow for each scenario is as illustrated below.
``` note:: If you do not intend to publish your created AIT globally, the steps beyond "releasing it on GitHub via a browser" are not necessary.
```
## How to proceed in this tutorial
In this tutorial, you will need to execute commands as shown in the following example.
**example:**
> * ait-cli command
> ```sh
> cd {sample}
> ait-cli sample
> ```
>
> * Launcher
> * windows:
> ```bat
> cd {sample}/tool
> sample.bat
> ```
> * macOS, Linux:
> ```sh
> cd {sample}/tool
> sample.sh
> ```
`ait-cli` is a command line tool to support AIT development. Installation is not required, but recommended.
If you have installed `ait-cli`, please follow the "ait-cli command" command in future procedures. If you have not installed `ait-cli`, please follow the "Launcher".
You can install `ait-cli` with pip.
```sh
pip install ait-cli
```
Detailed installation and usage instructions can be found at the link.
`https://pypi.org/project/ait-cli/`
## Set up AIT templates using ait-cli
Only those who have installed `ait-cli` should follow this procedure.
After performing this procedure, you do not need to perform the following procedures: `Fork the AIT template`, `Change AIT repository name`, and `clone the AIT repository`.
First, prepare the template for AIT development.
Go to the directory where you want to place the AIT template, and execute the following command.
* ait-cli command
```sh
ait-cli create --ait_name {YourAITName}
```
AIT name (the part `{YourAITName}`), we recommend you to follow the naming convention as below.
### Recommended naming convention of AIT
The recommended naming convention of AIT are as follows.
* `{prefix}_{target}_{format}_{task}_{measure}`
| name | mandatory | description |
|---------|-----------|---------------------------------------------------------------------------------|
| prefix | Yes | This represents the type of AIT.
- eval: Quality evaluation
- alyz: Analysis
- misc: Miscellaneous
- generate: Used for AIT that generates data to be input to AIT. |
| target | Yes | Choose either "dataset" or "model" depending on the evaluation target of AIT. |
| task | No | The problem targeted by AIT.
Example.image_classifier |
| format | No | The format of the data processed by AIT.
Example. table |
| measure | No | The quality measured by AIT.
Example. coverage_of_dataset |
* restriction
* The name must be 50 characters or less.
* The available characters are half-width alphanumeric characters and underscore `_`.
## Fork the AIT template
AIT template is available on `https://github.com/aistairc/ait-template`.
Please fork this repository for your own AIT development.
``` important:: The AIT template repository is set to public. After forking, please review and adjust the visibility settings as necessary.
```
## Change AIT repository name
AIT name (the part `{YourAITName}`), we recommend you to follow the naming convention as below.
### Recommended naming convention of AIT
The recommended naming convention of AIT are as follows.
* `{prefix}_{target}_{format}_{task}_{measure}`
| name | mandatory | description |
|---------|-----------|---------------------------------------------------------------------------------|
| prefix | Yes | This represents the type of AIT.
- eval: Quality evaluation
- alyz: Analysis
- misc: Miscellaneous
- generate: Used for AIT that generates data to be input to AIT. |
| target | Yes | Choose either "dataset" or "model" depending on the evaluation target of AIT. |
| task | No | The problem targeted by AIT.
Example.image_classifier |
| format | No | The format of the data processed by AIT.
Example. table |
| measure | No | The quality measured by AIT.
Example. coverage_of_dataset |
* restriction
* The name must be 50 characters or less.
* The available characters are half-width alphanumeric characters and underscore `_`.
## Clone the AIT repository
Fork the AIT template and clone it to your local machine.
## Edit readme.md
After create a directory for new AIT, open `{YourAITName}/readme.md` and edit title.
* Before
```
# ait-name
...
```
* After
```
# {YourAITName}
```
## Launch development envionment
We are providing Jupyter Lab environment adjusted to the AIT development purpose as AIT development environment.
After launching them, they are provided as web application on the localhost. You can use them through your browser.
Remove docker image
* If you want to switch between multiple AIT development environments, you need to delete the AIT development environment docker images created in the past. This is because the dependent software changes depending on AIT, and the AIT development environment also changes the software installation status. We apologize for the inconvenience, but if you want to switch between multiple AITs for development, please use the following command to delete the docker image in the AIT development environment.
* Remove docker image command
```
docker rmi {ImageId of docker_jupyter}
```
* Launcher
* Windows:
```bat
cd {YourAITname}/tool
launch_devenv.bat
```
* macOS, Linux:
```sh
cd {YourAITname}/tool
sudo bash launch_devenv.sh
```
### Screenshots after launch
If the launch has succeeded, applications below are displayed automatically.
* Jupyter lab
### Development work flow
In this tutorial, we assume following work flow as default development work flow.
1. Experiment and development of an AI evaluation program.
2. Porting AI evaluation program onto the AIT template (edit my_ait.ipynb).
3. Perform unit testing of an AI evaluation program.
4. Preparing registration for Qunomon.
5. Perform integration testing of an AIT with Qunomon testbed.
6. Publishing the AIT.
This tutorial follows this sequence and explains the detailed development methods for AITs from Section 3.2 onwards.