semvec/pypi-packages huggingface dataset:
cacahuate 3.14.1
The process virtual machine
License: MIT
Keywords: process

Cacahuate
=========

.. image:: https://travis-ci.org/tracsa/cacahuate.svg?branch=master
   :target: https://travis-ci.org/tracsa/cacahuate
   :alt: Build Status

**The process virtual machine**

This project defines storage for an abstract _process_ in a company, and
implements a virtual machine that keeps track of the execution of instances of
the process.

Develop
-------

You will need the **redis** and **mongo** databases, and **rabbitmq** for this
to work. I recommend using `pipenv` or `virtualenv` in your python projetcs ;)

* clone the repo
* install the requirements listed in `requirements.txt`
* run the tests (`pytest`)

you can control your cacahuate installation using this three environment
variables:

`CACAHUATE_SETTINGS`: absolute path to a settings file

`FLASK_APP`: import path to wsgi module (`cacahuate.http.wsgi`)

`FLASK_DEBUG`: set to `1` to turn on flask's debugging

Installation
------------

.. code-block:: bash

   pip install cacahuate

Cacahuated
----------

This is the daemon in charge of moving pointers in the process, run with:

.. code-block:: bash

   cacahuated

The Cacahuate REST API
----------------------

In this same repository you will find a flask application that exposes a REST
api for controling Cacahuate.

**How to run**

.. code-block:: bash

   FLASK_APP=cacahuate.http.wsgi flask run

You can use any wsgi-compliant server, like gunicorn, to run this:

.. code-block:: bash

   gunicorn cacahuate.http.wsgi:app

The docs
--------

Docs are built using `sphinx <http://www.sphinx-doc.org/en/master/>`_ and published in
https://tracsa.github.io/cacahuate/index.html. To build a local copy of the docs
navigate to the `docs/` directory and run:

.. code-block:: bash

   make html

For more options just run `make` by itself.

Release
-------

```bash
./release.sh cacahuate/version.txt [major|minor|patch]
```
karen-brain 0.7.1
Project Karen: Brain Module
License: MIT
Requires Python: >=3.6
Keywords: Artificial Intelligence,AI,Personal Assistant

Project Karen: Brain · |GitHub license| |Python Versions| |Read the Docs| |GitHub release (latest by date)|
===========================================================================================================

This project is dedicated to building a "Synthetic Human" which is
called Karen (for now) for which we have assigned the female gender
pronoun of "She". She has visual face recognition
(`opencv/opencv <https://github.com/opencv/opencv>`__), speech
transcription
(`mozilla/deepspeech <https://github.com/mozilla/DeepSpeech>`__), and
speech synthesis
(`festival <http://www.cstr.ed.ac.uk/projects/festival/>`__). Karen is
written in Python and is targeted primarily at the single board computer
(SBC) platforms like the `Raspberry
Pi <https://www.raspberrypi.org/>`__.

Visit our main site: https://projectkaren.ai/

Installation
------------

Karen is available as separate components that together create an
extensible environment for devices and the processing of input/output.
These components can be installed together or separately depending on
your needs. This project covers the brain module alone. For more
information on all of the components please visit the
`documentation <https://docs.projectkaren.ai>`__.

In order for Karen to work properly you must have a running instance of
``karen_brain.Brain()``. The brain is fairly straightforward to install
with the following steps:

::

    sudo apt-get install libfann2 python3-fann2 

::

    pip3 install karen-brain

Then to start the brain you can run the following:

::

    import karen
    karen.start("/path/to/config.json")

Please make note that to start the brain by itself then you must specify
your own `configuration
file <https://docs.projectkaren.ai/en/latest/config.overview/>`__ as all
of the built-in configurations will include a brain and device container
instance in their startup.

Additional Documentation
------------------------

To read more about Karen and all the components available please visit:
https://docs.projectkaren.ai

--------------

Help & Support
--------------

Help and additional details is available at https://projectkaren.ai

.. |GitHub license| image:: https://img.shields.io/github/license/lnxusr1/karen-brain
   :target: https://github.com/lnxusr1/karen-brain/blob/master/LICENSE
.. |Python Versions| image:: https://img.shields.io/pypi/pyversions/yt2mp3.svg
.. |Read the Docs| image:: https://img.shields.io/readthedocs/project-karen
.. |GitHub release (latest by date)| image:: https://img.shields.io/github/v/release/lnxusr1/karen-brain
karen-device 0.7.1
Project Karen: Device Container Module
License: MIT
Requires Python: >=3.6
Keywords: Artificial Intelligence,AI,Personal Assistant

Project Karen: Device Container · |GitHub license| |Python Versions| |Read the Docs| |GitHub release (latest by date)|
======================================================================================================================

This project is dedicated to building a "Synthetic Human" which is
called Karen (for now) for which we have assigned the female gender
pronoun of "She". She has visual face recognition
(`opencv/opencv <https://github.com/opencv/opencv>`__), speech
transcription
(`mozilla/deepspeech <https://github.com/mozilla/DeepSpeech>`__), and
speech synthesis
(`festival <http://www.cstr.ed.ac.uk/projects/festival/>`__). Karen is
written in Python and is targeted primarily at the single board computer
(SBC) platforms like the `Raspberry
Pi <https://www.raspberrypi.org/>`__.

Visit our main site: https://projectkaren.ai/

Installation
------------

Karen is available as separate components that together create an
extensible environment for devices and the processing of input/output.
These components can be installed together or separately depending on
your needs. This project covers the device container module alone. For
more information on all of the components please visit the
`documentation <https://docs.projectkaren.ai>`__.

The device container service is used to allow the brain to interact with
the input/output devices like a microphone or speaker output. The
individual device plugins can be installed separately. To install the
device container service follow the steps below:

::

    pip3 install karen-device

Then to start the brain you can run the following:

::

    import karen
    karen.start("/path/to/config.json")

Please make note that to start a Device Container by itself then you
must specify your own `configuration
file <https://docs.projectkaren.ai/en/latest/config.overview/>`__ as all
of the built-in configurations will include a brain and device container
instance in their startup.

Additional Documentation
------------------------

To read more about Karen and all the components available please visit:
https://docs.projectkaren.ai

--------------

Help & Support
--------------

Help and additional details is available at https://projectkaren.ai

.. |GitHub license| image:: https://img.shields.io/github/license/lnxusr1/karen-device
   :target: https://github.com/lnxusr1/karen-device/blob/master/LICENSE
.. |Python Versions| image:: https://img.shields.io/pypi/pyversions/yt2mp3.svg
.. |Read the Docs| image:: https://img.shields.io/readthedocs/project-karen
.. |GitHub release (latest by date)| image:: https://img.shields.io/github/v/release/lnxusr1/karen-device