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django package for retraining spaCy NER with active learning

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Spacy Active learning

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