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Ramping up a ChatBot, integrate with Django and deploy on Heroku – in 5 minutes | by Shahar Gino

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Custom Corpus

  1. Prepare your custom *.yml files in a similar syntax convention as the official corpus
  2. Manage the custom *.yml files in a hierarchical folders structure, where the top parent directory is adjacent to the app folder (also adjacent to manage.py and to the db.sqlite3 files).
  3. Add your custom *.yml files in the following manner (see in bold):
CHATTERBOT = {
'name': 'Heroku ChatterBot Example',
'logic_adapters' : [
"chatterbot.logic.BestMatch"
],
'trainer': 'chatterbot.trainers.ChatterBotCorpusTrainer',
'training_data': [
'chatterbot.corpus.english',
'chatterbot.corpus.hebrew',
'custom_corpus.subfolder1.my_ymls_are_here'
]
}

Then, just need to train the Bot:

% python manage.py migrate train

Note that ChatterBot enables by default an online-training scheme. This feature can be disabled by setting ‘read_only’: “True” in the above CHATTERBOT dictionary.

ChatterBot Reset

% heroku pg:reset DATABASE% heroku run python manage.py migrate
% heroku run python manage.py createsuperuser
% heroku run python manage.py shell>>> from chatterbot import ChatBot
>>> from chatterbot.ext.django_chatterbot import settings
>>> chatbot = ChatBot(**settings.CHATTERBOT)
>>> chatbot.storage.drop()
>>> exit()
% heroku run python manage.py train



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