A chatbot that assists rather than manipulates.
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.
qary package can be installed from PyPi by running:
pip install qary
First retrieve a copy of the source code for
git clone firstname.lastname@example.org: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
$ qary --help usage: qary [-h] [--version] [--name STR] [-p] [-s STR] [-v] [-vv] [words [words ...]]
qary for just one skill
$ qary -s qa # ... (logging messages) YOU: When was Barack Obama born? # ... (logging messages) qary: August 4, 1961
qary's probabilistic conversation manager chooses a reply from the possiblities generated by the different personalities:
skills/pattern.py): example skill using regex patterns to reply to greetings like "hi"
skills/qa.py): BERT and ALBERT Wikipedia Question Answering (WikiQA reading comprehension tests)
skills/faq.py): answers to frequently asked questions using data/faq/*.yml
skills/glossary.py): definitions from glossary yml files in data/faq/glossary-*.yml
eliza.py): a python port of the ELIZA therapist bot
Configuring default personalities
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.
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:
- search: chatterbot, will
- pattern matching and response templates: Alexa, AIML
- generative deep learning: robot-bernie, movie-bot
- 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.
- Create a fork of the main qary repository on Gitlab.
- Make your changes in a branch named something different from
master, e.g. create a new branch
- Create a merge request.
- 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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