DashAI 0.0.14

DashAI: a graphical toolbox for training, evaluating and deploying state-of-the-art AI models.

DashAI: a graphical toolbox for training, evaluating and deploying state-of-the-art AI models

Dependencies

DashAI requires:

• Python (>= 3.8)

• FastAPI (>= 0.79.0)

• SQLAlchemy (>=1.4.36)

• scikit-learn (>=1.0.2)

Installation

You can install DashAI via pip:

$ pip install dashai

Then, to initialize the server and the graphical interface, run:

$ dashai

Finally, go to http://localhost:3000/ in your browser to access to the DashAI graphical interface.

Development

To download and run the development version of DashAI, first, download the repository and switch to the developing branch: :

$ git clone https://github.com/DashAISoftware/DashAI.git
$ git checkout staging

Frontend

Warning

All commands executed in this section must be run from DashAI/front. To move there, run:

$ cd DashAI/front

Prepare the environment

1. Install the LTS node version.

2. Install Yarn package manager following the instructions located on the yarn getting started page.

3. Move to DashAI/front and Install the project packages using yarn:

$ cd DashAI/front
$ yarn install

Running the frontend

Move to DashAI/front if you are not on that route:

$ cd DashAI/front

Then, launch the front-end development server by running the following command:

$ yarn start

If you want to launch the front-end test server (without launching the backend) with dummy data, run:

$ yarn json-server

Linting and formatting

The project uses as default linter eslint with the react/recommended, standard-with-typescript` and prettier` styles.

To manually run the linter, move to DashAI/front and run:

$ yarn eslint src

The project uses prettier as default formatter.

To format the code manually, move to DashAI/front and execute:

$ yarn prettier --write src

Build the frontend

Execute from DashAI/front:

$ yarn build

Backend

Prepare the environment

First, set the python enviroment using conda:

Then, move to DashAI/back

$ cd DashAI/back

Later, install the requirements:

$ pip install -r requirements.txt
$ pip install -r requirements-dev.txt

Running the Backend

There are two ways to run DashAI:

1. By executing DashAI as a module:

$ python -c "import DashAI;DashAI.run()"

2. Or, installing the default build:

$ pip install .
$ dashai

If you chose the second way, remember to install it each time you make changes.

Execute tests

DashAI uses pytest to perform the backend tests. To execute the backend tests

1. Move to DashAI/back

$ cd DashAI/back

2. Run:

$ pytest tests/

Note

The database session is parametrized in every endpoint as db: Session = Depends(get_db) so we can test endpoints on a test database without making changes to the main database.

Linting and formatting

The project uses as default backend linter ruff:

To manually run the linter, move to DashAI/back and execute:

$ ruff .

The project uses black as default formatter.

To manually format the code, move to DashAI/back and execute:

$ black .

Acknowledgments

This project is sponsored by the National Center for Artificial Intelligence - CENIA (FB210017), and the Millennium Institute for Foundational Data Research - IMFD (ICN17_002).

The core of the development is carried out by students from the Computer Science Department of the University of Chile and the Federico Santa Maria Technical University.

To see the full list of contributors, visit in Contributors the DashAI repository on Github.