Artificial Intelligence for Django
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Failed to load latest commit information.
.github Introducing... django-aigit add . Sep 5, 2017
django_ai Version Jan 15, 2018
docs [doc] Examples polishing May 18, 2018
misc Add 'missing' django_dag migration for resolving migrations problems Sep 9, 2017
tests Towards the second release of django-ai :) Jan 15, 2018
.coveragerc [tests] Misc coverage ingnoring Dec 7, 2017
.editorconfig Introducing... django-aigit add . Sep 5, 2017
.gitignore [spam filter] Add pre-training functionality (and minor polishing) Dec 13, 2017
.travis.yml Use old travis images Jan 15, 2018
AUTHORS.rst Add 'Promoting Contributing' to doc Nov 13, 2017
CONTRIBUTING.rst Remove unappreciated joke Nov 13, 2017
HISTORY.rst Support for Django 2.0 Jan 15, 2018
LICENSE Merge branch 'master' of Sep 5, 2017
MANIFEST Introducing... django-aigit add . Sep 5, 2017 Missing omit of migrations in Manifest Jan 15, 2018
Makefile Introducing... django-aigit add . Sep 5, 2017
README.rst Fix typo in README.rst May 17, 2018
django_ai.jpg Introducing... django-aigit add . Sep 5, 2017 Introducing... django-aigit add . Sep 5, 2017
requirements.txt Support for Django 2.0 Jan 15, 2018
requirements_dev.txt Introducing... django-aigit add . Sep 5, 2017
requirements_rtd.txt Add scikit-learn to requirements Nov 17, 2017
requirements_test.txt Introducing... django-aigit add . Sep 5, 2017 Fix namespaces for tests Sep 13, 2017
setup.cfg Version Jan 15, 2018 Require numpy<1.14 in package Jan 15, 2018
tox.ini Even more fixes for Travis CI Jan 16, 2018



Artificial Intelligence for Django

django-ai is a collection of apps for integrating statistical models into your Django project so you can implement machine learning conveniently.

It integrates several libraries and engines providing your Django app with a set of tools so you can leverage the data generated in your project.


The full documentation is at or the /docs directory for offline reading.


See the Introduction section in the documentation for more information.

Communication Channels


The easiest way of trying django-ai is inside its package:

  1. Create a virtual environment and activate it:

    python3 -m venv django-ai_env
    source django-ai_env/bin/activate
  2. Upgrade pip and install django-ai:

    (django-ai_env) pip install --upgrade pip
    (django-ai_env) pip install django-ai
  3. Change into the django-ai directory, i.e.:

    (django-ai_env) cd django-ai_env/lib/python3.5/site-packages/django_ai
  4. Create the migrations for the dependencies and apply them:

    python makemigrations
    python migrate
  5. Create a superuser:

    python createsuperuser
  6. Start the development server and visit, look at the examples and start creating your statistical models:

    python runserver

You can also clone it from the repository and install the requirements in a virtualenv:

git clone

and following the previous steps, install the requirements - pip install -r requirements.txt - in a virtual environment instead of the package.

For installing it in your project, please refer here.

Running Tests

Does the code actually work?

source <YOURVIRTUALENV>/bin/activate
(myenv) $ pip install -r requirements_test.txt
(myenv) $ PYTHONHASHSEED=0 python