idp-engine 0.7.2

IDP-Z3 is a collection of software components implementing the Knowledge Base paradigm using the FO(.) language and a Z3 SMT solver.

The IDP-Z3 tools implement a knowledge base system combining the Microsoft Z3 solver and a grounder developed in-house, supporting the IDP language. See the presentation at www.IDP-Z3.be.

It is developed by the Knowledge Representation group at KU Leuven in Leuven, Belgium, and made available under the GNU LGPL v3 License.

Installation

• Install python3 on your machine.
• Install poetry:
  • after that, logout and login if requested, to update $PATH
• Use git to clone https://gitlab.com/krr/IDP-Z3 to a directory on your machine
• Open a terminal in that directory
• If you have several versions of python3, and want to run on a particular one, e.g., 3.9:
  • run poetry env use 3.9
  • replace python3 by python3.9 in every command below
• Run poetry install

Get started

To launch the Interactive Consultant web server:

• open a terminal in that directory and run poetry run python3 main.py
• open your browser at http://127.0.0.1:5000

Develop

You may want to read about the technical documentation and the Development and deployment guide.

The user manual is in the /docs folder and can be locally generated as follows:

poetry run sphinx-autobuild docs docs/_build/html

To view it, open http://127.0.0.1:8000

The documentation on readthedocs is automatically updated from the main branch of the GitLab repository.

The home page is in the /homepage folder and can be locally generated as follows:

poetry run sphinx-autobuild homepage homepage/_build/html

To view it, open http://127.0.0.1:8000. The website is also automatically updated from the main branch of the GitLab repository.

Testing

To generate the tests, from the top directory run poetry run python3 test.py or poetry run python3 test.py generate. After this, you can manually check what has changed using git.

There is also a testing pipeline available, which can be used by running poetry run python3 test.py pipeline.

Deploy

See the instructions here.