Machine Learning

For example, here is a sample convo

Enter Your Name: James

Welcome to Chatbot Service! Let me know how can I help you

James: Hi!

Bot: everything's been good with you? i haven't been better. how about yourself?

James: I am doing well

Bot: That is good to hear

James: What are you doing today

Bot: i'm doing great. what about you? i'm absolutely lovely, thank you.

James: What is your favorite movie

Bot: that was my favorite class. you have got to be talented.

James: What class are you talking about

Bot: of course they talk to each other. what do they talk about?

James: They gossip about horrible things

Bot: i feel the same way. it smells so good after it rains. i especially love the night air when it rains.

James: quit

Bot: well, she's quite short. how tall would you say that she is?

James: bye

Bot: Bye

Here is the code I have

import numpy as np # linear algebra|
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)


from chatterbot import ChatBot
from chatterbot.trainers import ListTrainer
from chatterbot.trainers import ChatterBotCorpusTrainer
import os

import collections.abc

collections.Hashable = collections.abc.Hashable

bot = ChatBot('Buddy',
        logic_adapters=[{
        'import_path': 'chatterbot.logic.BestMatch',
        'default_response': 'I am sorry, but I do not understand.',
        'maximum_similarity_threshold': 0.90
    }],
        read_only = True,
        preprocessors=['chatterbot.preprocessors.clean_whitespace',
                    'chatterbot.preprocessors.unescape_html',
                    'chatterbot.preprocessors.convert_to_ascii']
                    )


directory = 'kaggle'

for filename in os.listdir(directory):
  if filename.endswith(".txt"): # only pick txt file for training
    print('\n Chatbot training with '+os.path.join(directory, filename)+' file')
    training_data = open(os.path.join(directory, filename), 'r', encoding='utf-8').read().splitlines()
    trainer = ListTrainer(bot) # bot training
    trainer.train(training_data)
  else:
    continue


decision = input('Train chatbot with English corpus data? (Y/N): ')

if decision == 'Y':
  print('\n Chatbot training with English corpus data')
  trainer_corpus = ChatterBotCorpusTrainer(bot)
  trainer_corpus.train('chatterbot.corpus.english')



name = input('Enter Your Name: ')

print ('Welcome to Chatbot Service! Let me know how can I help you')

while True:

  request = input(name+': ')

  if request=="Bye" or request=='bye':
    print('Bot: Bye')
    break
  else:
    response=bot.get_response(request)
    print('Bot: ', response)