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import sys
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from sys import stdin, stdout
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def seven(text):
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fpath = open('src/91K_nouns.txt')
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nouns = fpath.readlines()
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separated = text.split() #use nltk tokenize instead
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#print(separated)
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new_separated = []
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for word in separated:
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word = word.lower() + '\n'
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if word in nouns:
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position = nouns.index(word)
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new_word = nouns[position + 7]
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#print(" replacing", new_position)
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new_separated.append(new_word.strip())
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else:
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#print("notinlist")
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#print("adding to new_separated ", word)
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new_separated.append(word.strip())
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#print(new_separated)
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return ' '.join(new_separated)
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text = stdin.read()
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output = seven(text)
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print(output)
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#sentence = input('What is your sentence? ')
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#print(seven(sentence))
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# pytest requires that you name your tests with test_<your-name>
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# run with the 'pytest' command in your terminal
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#def test_seven():
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# assert seven('Baboons') == 'babushkas'
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# assert seven('Baboons,') == 'babushkas'
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from chatterbot import ChatBot
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from sys import stdin, stderr, stdout
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import nltk.data
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text = stdin.read()
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sent_detector = nltk.data.load('tokenizers/punkt/english.pickle')
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sentences = sent_detector.tokenize(text.strip())
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ns = []
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chatbot = ChatBot(
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'Ron Obvious',
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trainer='chatterbot.trainers.ChatterBotCorpusTrainer',
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output_format="text"
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)
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# Train based on the english corpus
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chatbot.train("chatterbot.corpus.english")
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for sen in sentences:
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# Get a response to an input statement
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response=chatbot.get_response(sen)
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ns.append(sen)
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ns.append(response.text)
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file = open('output/whatdoesthechatbotsay.txt','w')
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file.write("\n".join(ns))
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file.close()
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