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from chatterbot import utils
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from chatterbot.conversation import Statement
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from chatterbot.trainers import Trainer
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class TwitterCorpusTrainer(Trainer):
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pass
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# def train(self, *args, **kwargs):
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# """
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# Train the chat bot based on the provided list of
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# statements that represents a single conversation.
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# """
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# import twint
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#
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# c = twint.Config()
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# c.__dict__.update(kwargs)
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# twint.run.Search(c)
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#
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#
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# previous_statement_text = None
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# previous_statement_search_text = ''
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#
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# statements_to_create = []
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#
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# for conversation_count, text in enumerate(conversation):
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# if self.show_training_progress:
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# utils.print_progress_bar(
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# 'List Trainer',
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# conversation_count + 1, len(conversation)
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# )
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#
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# statement_search_text = self.chatbot.storage.tagger.get_text_index_string(text)
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#
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# statement = self.get_preprocessed_statement(
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# Statement(
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# text=text,
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# search_text=statement_search_text,
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# in_response_to=previous_statement_text,
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# search_in_response_to=previous_statement_search_text,
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# conversation='training'
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# )
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# )
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#
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# previous_statement_text = statement.text
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# previous_statement_search_text = statement_search_text
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#
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# statements_to_create.append(statement)
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#
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# self.chatbot.storage.create_many(statements_to_create)
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