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A web application for custom named entity recognition

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Chem NER

Chem NER is a RESTFul based application to upload an archive of xml fies, which contains details of patents. And the application persists NERS based on inbuilt and custom model which is trained on the data provided. It contains two end point.

  • patents/archive_upload/
  • patents/delete_patent

Tech

Used a number of open source projects to work properly:

  • [django_rest_framework] - Web frame work in python for building REST API's
  • [redis] - Message Broker
  • [celery] - Celery is an open source asynchronous task queue
  • [Spacy] - Package for NLP
  • [MongoDB] - Document Based DataBase

Running

Install the dependencies.

$ pip install -r requirements.txt

Start redis server...

$ redis-server

Check if redis is running or not..

$ redis-cli ping

Run celery..

$ celery -A NER worker -l info

Make sure the mongo DB is installed and configured accordingly in settings.py

DATABASES = {
    'default': {
        'ENGINE': 'djongo',
        'NAME': 'DB_NAME',
    }
}

Make Migrations and Migrate..

$ python manage.py makemigrations
$ python namage.py migrate

Finally run the Server..

$ python manage.py runserver

API's

Archive Upload Request

HTTP VERB : POST http://localhost:8000/patents/archive_upload/ In form-data pass: archive : zip_file

Response

[
    "File uspat1_201831_back_80001_100000.zip uploaded Successfully and started processing"
]

Delete Patents Details Request

HTTP VERB : DELETE http://localhost:8000/patents/delete_patent/?patent_id=USD0437352S1

Response

{
    "message": "Patent Deleted"
}

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A web application for custom named entity recognition

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