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https://gitlab.com/tangibleai/community/qary-cli
Command Line Interface for developers of qary -- the open source, teachable AI assistant that truly assists, rather than manipulating you.
https://gitlab.com/tangibleai/community/qary-cli
BERT ELIZA GPT3 HACKTOBERFEST2022 NLP Virtual Assistant chatbot datasets hacktoberfest machine learning pytorch sklearn spacy torch
Last synced: 19 days ago
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Command Line Interface for developers of qary -- the open source, teachable AI assistant that truly assists, rather than manipulating you.
- Host: gitlab.com
- URL: https://gitlab.com/tangibleai/community/qary-cli
- Owner: tangibleai
- License: hippocratic-2.1
- Created: 2020-03-18T23:42:59.027Z (over 4 years ago)
- Default Branch: main
- Last Synced: 2024-10-10T11:43:18.429Z (about 1 month ago)
- Topics: BERT, ELIZA, GPT3, HACKTOBERFEST2022, NLP, Virtual Assistant, chatbot, datasets, hacktoberfest, machine learning, pytorch, sklearn, spacy, torch
- Stars: 18
- Forks: 24
- Open Issues: 70
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
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README
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[](https://pypi.org/project/qary/)
[](https://pypi.python.org/pypi/qary/)
[](https://codecov.io/gl/tangibleai/qary)
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# `qary`
The `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](https://proai.org/nlpia2-book).
It has slowly grown into the core framework for a social-impact startup [Tangible AI](https://tangibleai.com).
Tangible AI [interns and volunteers](/docs/wiki/contributors.md) are constantly fixing bugs, adding new features and dialog trees to qary's repetoire.
The [San Diego Python User Group](https://www.pythonsd.org/index.html) meetups have been the scene for [some fun qary demos](https://piped.kavin.rocks/channel/UCXU-oZwaHnoYUhja_yrrrGg).
The [San Diego Machine Learning Book Club](https://www.meetup.com/San-Diego-Machine-Learning/) 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 `docs/`.
## Install
### Install from source
Retrieve the source code from GitLab using a bash console:
```bash
git clone [email protected]:tangibleai/qary
cd 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](docs/README-windows-install.md)
Make sure you install `qary` in a _virtual environment_ using the latest version of `pip` and the python `virtualenv` package:
```bash
pip install --upgrade pip virtualenv
python -m virtualenv venv
source venv/bin/activate
```
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:
```bash
pip install --editable .
```
Now you're ready to run `qary` from the command line (bash console):
```bash
qary "Hi!"
```
### PyPi package
`qary` is on [PyPi](https://pypi.org/project/qary/) but this install is unlikely to work, unless you've already installed all the dependencies:
```bash
pip install qary
```
## Usage
```bash
$ qary --help
usage: qary [-h] [--version] [--name STR] [-p] [-s STR] [-v] [-vv] [words [words ...]]
```
### Running `qary` for just one skill
```bash
$ 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](https://github.com/gunthercox/ChatterBot), [will](https://github.com/skoczen/will)
2. pattern matching and response templates: Alexa, [AIML](https://github.com/keiffster/program-y)
3. generative deep learning: [robot-bernie](https://github.com/nlpia/robot-bernie), [movie-bot](https://github.com/totalgood/nlpia/blob/master/src/nlpia/book/examples/ch10_movie_dialog_chatbot.py)
4. grounding: [snips](https://github.com/snipsco/snips-nlu)
It's all explained in detail at [NLP in Action](https://www.manning.com/books/natural-language-processing-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](http://totalgood.org/midata/talks/)
## Contributing pattern for developers
DM @hobs on SD PUG's [discord server](https://discord.gg/yFTAQDxg) if you'd like to join us for weekly collaborative-coding sessions on `qary` and other open source projects.
1. [Create a fork](https://docs.gitlab.com/ee/user/project/repository/forking_workflow.html#creating-a-fork) of the [main qary repository](https://gitlab.com/tangibleai/qary) 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](https://docs.gitlab.com/ee/user/project/merge_requests/creating_merge_requests.html).
4. Help your fellow contributors out by:
- Follow the [PEP-8 style guide](https://www.python.org/dev/peps/pep-0008/).
- Try to include a docstring, at least a single line, in any function, method, or class
- Bonus points for adding a [doctest](https://docs.python.org/3/library/doctest.html) 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!