Natural Language Understanding (text processing) for math symbols, digits, and words with a Gradio user interface and REST API.
Project description
title: MathText app_file: app.py sdk: gradio sdk_version: 3.15.0 license: agpl-3.0
MathText NLU
Natural Language Understanding for math symbols, digits, and words with a Gradio user interface and REST API.
Setup your Python environment
Launch a terminal
on linux (or the git-bash
application on Windows).
Then create a virtualenv with whatever python version you have available on your system.
Any python version greater than 3.7
should work.
Most of us on Linux systems use Python 3.9
:
git clone git@gitlab.com:tangibleai/community/mathtext
cd mathtext
pip install --upgrade virtualenv poetry
python -m virtualenv .venv
ls -hal
You should see a new .venv/
directory.
It will contain your python interpreter and a few site-packages
like pip
and distutils
.
Now activate your new virtual environment by sourcing .venv/bin/activate
(on Linux) or .venv/scripts/activate
(on Windows).
source .venv/bin/activate || source .venv/scripts/activate
Developer installation
Once you have a shiny new virtual environment activated you can install the mathtext
in --editable
mode.
This way, when you edit the files and have the package change immediately.
Make sure you are already within your cloned mathtext
project directory.
And makes sure your virtual environment is activated.
You should see the name of your virtual environment in parentheses within your command line prompt, like (.venv) $
.
Then when you install MathText it will be available to any other application within that environment.
pip install --editable .
User installation
If you don't want to contribute to the MathText source code and you just want to import and run the MathText modules, you can install it from a binary wheel on PyPi.
pip install mathtext
Usage
Sentiment classification
Directory structure with notes
mathtext
mathtext: mathtext code
data: training and test sets for various tasks
models: scripts to create models and store in/retrieve from object storage
utils: utility functions
checkers.py: T/F evaluations
converters.py: Change the data type from one to another
extractors.py: Looks for specific values or value types in a message
formatters.py: Attempts to format text in a standardized way
api_gradio.py: gradio api
predict_intent.py: functions to run multilabel recognizer on message
text_processing.py: evaluations that use sequences of utils
scripts: setup scripts
api_scaling.sh: makes calls to local api
api_scaling.py: makes async http requests to the local api
build.sh
plot_calls.py: Functions for plotting data
pyproject.template
tests: various tests
__init.py
test_cases_all.py
.git*: various git files
app.py: ties all of the api components together for huggingface
LICENSE.md: license
pyproject.toml: pyproject file
README.md: this
requirements.txt: project dependencies
Project details
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