A chatbot that assists rather than manipulates.
qary package is both a chatbot framework and a 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 prosocial intelligence.
We started work on
qary as part of 1st editition of NLP in Action.
It has slowly grown into the core framework for a social-impact startup Tangible AI.
Tangible AI interns and volunteers are constantly fixing bugs, adding new features and dialog trees to qary's repetoire.
The San Diego Python User Group meetups have been the scene for some fun qary demos.
The San Diego Machine Learning Book Club is a great place for support on advanced concepts in the NLP in Action book or anything NLP and machine learning related.
You can find more ideas in
Install from source
Retrieve the source code from GitLab using a bash console:
git clone email@example.com:tangibleai/qary
If that doesn't work or you don't know what a bash console is, then you probably want to start with the Windows Users Instructions here: docs/README-windows-install.md
Make sure you install
qary in a virtual environment using the latest version of
pip and the python
pip install --upgrade pip virtualenv
python -m virtualenv venv
Now that you have your environment activated, make sure you are in the
qary/ repository along side the pyproject.toml file so you can install qary in developer (editable) mode:
pip install --editable .
Now you're ready to run
qary from the command line (bash console):
qary is on PyPi but this install is unlikely to work, unless you've already installed all the dependencies:
pip install qary
$ 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 on SD PUG's discord server if you'd like to join us for weekly collaborative-coding sessions on
qary and other open source projects.
- 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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