hardwax_bot.R

# LOAD -----------------------------------------------------------

options(repos = "https://mran.microsoft.com")

if (!require('dplyr')) install.packages('dplyr')
if (!require('stringr')) install.packages('stringr')
if (!require('rtweet')) install.packages('rtweet')

library(dplyr)
library(stringr)
library(rtweet)

# load data
word_counts <- read.csv("https://raw.github.com/ewenme/hardwax_bot/master/Data/words.csv", stringsAsFactors = FALSE)

opener_counts <- read.csv("https://raw.github.com/ewenme/hardwax_bot/master/Data/openers.csv", stringsAsFactors = FALSE)

bigram_counts <- read.csv("https://raw.github.com/ewenme/hardwax_bot/master/Data/bigrams.csv", stringsAsFactors = FALSE)

trigram_counts <- read.csv("https://raw.github.com/ewenme/hardwax_bot/master/Data/trigrams.csv", stringsAsFactors = FALSE)

# set twitter token
twitter_token <- readRDS(gzcon(url("https://raw.github.com/ewenme/hardwax_bot/master/twitter_token.rds")))


# NEXT WORD PREDICTION -------------------------------------------

# capitalise first letter
firstup <- function(x) {
  substr(x, 1, 1) <- toupper(substr(x, 1, 1))
  x
}

# function to return third word
return_third_word <- function(woord1, woord2){
  
  # sample a word to add to first two words
  woord <- trigram_counts %>%
    filter_(~word1 == woord1, ~word2 == woord2)
  
  if(nrow(woord) > 0) {
    woord <- sample_n(woord, 1, weight = n) %>%
      .[["word3"]]
    
  } else {
    woord <- filter_(bigram_counts, ~word1 == woord2) %>%
      sample_n(1, weight = n) %>%
      .[["word2"]]
  }
  
  # print
  woord
}


# SENTENCE GENERATOR ------------------------------------------

generate_sentence <- function(word1, word2, sentencelength, debug =FALSE){
  
  # comma chance sample
  commas <- sample(0:100, 1)
  
  #input validation
  if(sentencelength <3)stop("I need more to work with")
  sentencelength <- sentencelength -2
  
  # starting to add words
  if(commas <= as.numeric(word1$comma_prob)) {
    sentence <- paste(word1$word, ", ", word2$word, sep="")
  } else {
    sentence <- c(word1$word, word2$word)
  }
  
  woord1 <- word1$word
  woord2 <- word2$word
  for(i in seq_len(sentencelength)){
    
    commas <- sample(0:100, 1)
    
    if(debug == TRUE)print(i)
    word <- return_third_word( woord1, woord2)
    
    word <- left_join(as_data_frame(word), word_counts, by=c("value"="word"))
    
    if(commas <= as.numeric(word$comma_prob)) {
      sentence <- c(sentence, ", ", word$value[1])
    } else {
      sentence <- c(sentence, word$value[1])
    }
    
    woord1 <- woord2
    woord2 <- word$value[1]
  }
  
  # paste sentence together
  output <- paste(sentence, collapse = " ")
  output <- str_replace_all(output, " ,", ",")
  output <- str_replace_all(output, "  ", " ")
  
  # add tip sometimes
  tip_n <- sample(1:20, 1)
  if(tip_n %in% c(1, 2)){
    output <- paste(output, "- TIP!")
  } else if(tip_n %in% c(3, 4)){
    output <- paste(output, "(one per customer)")
  } else if(tip_n %in% c(5)){
    output <- paste(output, "- Killer!")
  } else if(tip_n %in% c(6, 7)){
    output <- paste(output, "- Warmly Recommended!")
  } else if(tip_n %in% c(8, 9)){
    output <- paste(output, "- Highly Recommended!")
  } else if(tip_n %in% c(10, 11)){
    output <- paste(output, "(w/ download code)")
  }
  
  # print
  firstup(output)
}


# REVIEW GENERATOR -------------------------------------------------

# generate review
dumb_hardwax <- function(x) {
  a <- sample_n(opener_counts, size=1, weight = n)
  b <- sample_n(word_counts, size=1, weight = n)
  len <- sample(5:12, 1)
  
  generate_sentence(word1=a, word2=b, sentencelength=len)
}


# TWEET --------------------------------------------------------

# create tweet
tweet_text <- dumb_hardwax()

# post tweet
post_tweet(status = tweet_text, token = twitter_token)