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wut-back-end's Introduction

Development

Clone the repository and then:

With Docker:

# docker-compose up

In a traditional way:

With python installed (we recommend to use a venv enviroment):

# pip install -r requirements-dev.txt
# pip3 install https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-2.2.0/en_core_web_sm-2.2.0.tar.gz
# python  
  >>> import nltk
  >>> nltk.download('stopwords')
  >>> exit()
# ./start.sh

Play

curl --location --request POST 'localhost:5000/classification/movements' \
--header 'Content-Type: text/plain' \
--data-raw 'walmart
uber'

Test

To run classifier model tests:

python -m unittest

Production

Dockerfile copy the project instead, but still a volume has to be used to write .vector_cache.

docker-compose -f docker-compose.yml -f docker-compose.prod.yml up --build

wut-back-end's People

Contributors

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Watchers

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