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from chatterbot import ChatBot
import spacy
spacy.cli.download("en_core_web_sm")
spacy.cli.download("en")
nlp = spacy.load('en_core_web_sm')
chatbot = ChatBot(
'CoronaBot',
storage_adapter='chatterbot.storage.SQLStorageAdapter',
logic_adapters=[
'chatterbot.logic.MathematicalEvaluation',
'chatterbot.logic.TimeLogicAdapter',
'chatterbot.logic.BestMatch',
{
'import_path': 'chatterbot.logic.BestMatch',
'default_response': 'I am sorry, but I do not understand. I am still learning.',
'maximum_similarity_threshold': 0.90
}
],
database_uri='sqlite:///database.sqlite3'
)
# Training With Own Questions
from chatterbot.trainers import ListTrainer
trainer = ListTrainer(chatbot)
training_data_quesans = open('training_data/ques_ans.txt').read().splitlines()
training_data_personal = open('training_data/personal_ques.txt').read().splitlines()
training_data = training_data_quesans + training_data_personal
trainer.train(training_data)
# Training With Corpus
from chatterbot.trainers import ChatterBotCorpusTrainer
trainer_corpus = ChatterBotCorpusTrainer(chatbot)
trainer_corpus.train(
'chatterbot.corpus.english'
)
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