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A chatbot that assists rather than manipulates.

Project description

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qary

The qary package is both a chatbot framework and a working "reference implementation" virtual assistant that actually assists! Most bots manipulate you to make money for their corporate masters. With qary, you can build your bot to protect you and amplify your intelligence and prosocial instincts.

qary was conceived as part of NLP in Action book, is maintained by an active developer community and is supported by San Diego Python User Group (some qary talks here and in docs/) and San Diego Machine Learning Group.

Install

Package install

qary package can be installed from PyPi by running:

pip install qary

Developer install

First retrieve a copy of the source code for qary:

git clone git@gitlab.com:tangibleai/qary
cd qary

Then, install and use the conda python package manager within the Anaconda software package.

conda update -y -n base -c defaults conda
conda create -y -n qaryenv 'python>=3.6.5,<3.9'
conda env update -n qaryenv -f environment.yml
conda activate qaryenv || source activate qaryenv
pip install --editable .

Windows Users: docs/README-windows-install.md

Usage

$ qary --help
usage: qary [-h] [--version] [--name STR] [-p] [-s STR] [-v] [-vv] [words [words ...]]

Running qary for just one skill

$ qary -s qa
# ... (logging messages)
YOU: When was Barack Obama born?
# ... (logging messages)
qary: August 4, 1961

qary skills

qary's probabilistic conversation manager chooses a reply from the possiblities generated by the different personalities:

  • pattern (skills/pattern.py): example skill using regex patterns to reply to greetings like "hi"
  • qa (skills/qa.py): BERT and ALBERT Wikipedia Question Answering (WikiQA reading comprehension tests)
  • faq (skills/faq.py): answers to frequently asked questions using data/faq/*.yml
  • glossary (skills/glossary.py): definitions from glossary yml files in data/faq/glossary-*.yml
  • eliza (eliza.py): a python port of the ELIZA therapist bot

Configuring default personalities

By default, qary runs with qa personality. Check out the config file in qary.ini to change the default skills loaded for your own custom skill in the skills directory.

Approach

qary's chatbot framework allows you to combine many approaches to give you state-of-the-art capability to answer questions and carry on a conversation:

  1. search: chatterbot, will
  2. pattern matching and response templates: Alexa, AIML
  3. generative deep learning: robot-bernie, movie-bot
  4. grounding: snips

It's all explained in detail at NLP in Action.

Presentations for San Diego Python User Group are in [docs/](/docs/2019-08-22--San Diego Python User Group -- How to Build a Chatbot.odp) and on the web at http://totalgood.org/midata/talks

Contributing pattern for developers

DM @hobs if you'd like to join us for weekly Zoom collaborative-coding sessions.

  1. Create a fork of the main qary repository on Gitlab.
  2. Make your changes in a branch named something different from master, e.g. create a new branch my-pull-request.
  3. Create a merge request.
  4. Help your fellow contributors out by:
  • Follow the PEP-8 style guide.
  • Try to include a docstring, at least a single line, in any function, method, or class
  • Bonus points for adding a doctest as part of your contribution.
  • If you add a new feature, write some quick docs in the README.
  • Add your name and attribution to the AUTHORS file.
  • Know we are grateful for your contribution! You've made the chatbot world a little better!

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