n level markov chain to randomly generate text

markov_chain.rb

class String
  def blank?
    self.nil? || self.empty?
  end

  def present?
    !self.blank?
  end
end

class Array
  def blank?
    self.nil? || self.empty?
  end

  def present?
    !self.blank?
  end
end

class NilClass
  def blank?
    self.nil? || self.empty?
  end

  def present?
    !self.blank?
  end
end

class MarkovChain
  attr_accessor :memory, :level

  def initialize(level: 1)
    @level = level
    @memory = [].tap{|m| level.times{m.push({})}}
  end

  def train(path: "",raw: "")
    tokens = nil
    if path.present?
      tokens = File.read(path).split(" ")
    elsif raw.present?
      tokens = raw.split(" ")
    end
    (0...(tokens.length - @level)).each do |i|
      prev_key = nil
      prev_value = nil
      (0...@level).each do |level|
        value = tokens[i + level + 1]
        key = (prev_key.present? && prev_value.present?) ?  prev_key + [prev_value] : [tokens[i]]
        # puts "i=#{i}, level=#{level}, key=#{key}, value=#{value}, memory=#{memory}"
        @memory[level][key] = [] if @memory[level][key].blank?
        @memory[level][key] = value
        prev_key = key.dup
        prev_value = value.dup
      end
    end
  end


  def next_word(curr_state=[])
    puts "next word curr_state: #{curr_state}"
    result = @memory[0].keys.sample.first if curr_state.blank?
    if result.present?
      puts "level 0: #{result}"
      return result
    end
    level = @level - 1
    while level >= 0
      result = @memory[level][curr_state[0...@level]]
      if result.present?
        puts "level #{level + 1}: #{result}"
        return result
      end
      level -= 1
    end
    puts "level 0: #{result}"
    @memory[0].keys.sample.first
  end

  def babble(length: 2)
    result = next_word
    (0..length).each do
      tokens = result.split(" ")
      range = ((-1 * (@level >= tokens.length ? tokens.length : @level))..-1)
      state = tokens[range]
      word = next_word(state)
      result += " " + word
    end
    result
  end
end

# Usage
o = MarkovChain.new(level: 3)
o.train(path: './training_data/obama.txt')
o.babble(length: 1000)