---
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`:
```bash
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).
```bash
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.
```bash
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.
```bash
pip install mathtext
```
## Usage
### Sentiment classification
### Directory structure with notes
```text
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
```
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