====================
.. image:: https://zenodo.org/badge/130271493.svg
:target: https://zenodo.org/badge/latestdoi/130271493
Django app that uses active learning (deliberately picking the examples to annotate) to retrain the spaCy_ NER module more effectively.
Prerequisites
-------------
For spacyal to run you need a working Celery_ installation. Something along the lines of::
from __future__ import absolute_import, unicode_literals
import os
from celery import Celery
app = Celery('tasks')
# Using a string here means the worker doesn't have to serialize
# the configuration object to child processes.
# - namespace='CELERY' means all celery-related configuration keys
# should have a `CELERY_` prefix.
app.config_from_object('django.conf:settings', namespace='CELERY')
# Load task modules from all registered Django app configs.
app.autodiscover_tasks()
@app.task(bind=True)
def debug_task(self):
print('Request: {0!r}'.format(self.request))
Installation
------------
* Install the package
* include spacyal.urls and spacyal.api_urls in your main url definition
* ensure that you have a base template called base.html
* run python manage.py migrate
* and you should be good to go
.. _Celery: http://www.celeryproject.org/
.. _spaCy: https://www.spacy.io
Metadata
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