chatgpt.rake

require 'colorize'

# namespace :chatgpt do
#   desc "Export Categories to Swell"
#   task clean_adventure_text: :environment do
#     client = OpenAI::Client.new
    
#     Adventure.all.published.each do |adventure|
#       puts "Cleaning #{adventure.title}...".green
#       word_count = adventure.content.to_plain_text.split.count
#       if word_count < 200
#         puts "Adventure #{adventure.title} has #{word_count} words, shall I ask ChatGPT? (y/n)".red
#         begin
#           input = STDIN.gets.strip.downcase
#         end until %w(y n).include?(input)
      
#         case input
#         when 'y'
#           puts "ChatGPT working on #{adventure.title}...".green
#           full_content = ""

#           response = client.chat(
#             parameters: {
#               model: "gpt-4",
#               messages: [
#                 { role: "system", content: "You are writing content for a website selling creative teambuilding related events" },
#                 { role: "system", content: "This for an event titled: '#{adventure.title}' in the context of the category of: #{adventure.primary_category.title}" },
#                 { role: "system", content: "The output should be HTML using only starting and ending div tags and double <br><br> at the end of paragraphs" },
#                 { role: "user", content: "Can you expand this event description into 3 to 4 complete paragraphs?"},
#                 { role: "user", content: "It should be more between 150 to 180 words in length and without headings"},
#                 { role: "user", content: adventure.content.to_plain_text},
#               ],
#               max_tokens: 375,
#               top_p: 0.95,
#               temperature: 0.7,
#               stream: proc do |chunk, _bytesize|
#                 content_chunk = chunk.dig("choices", 0, "delta", "content").to_s
#                 print content_chunk
#                 full_content += content_chunk
#               end
#             }
#           )
#           adventure.content = full_content
#           adventure.save!
#         when 'n'
#           puts "No worries, I'll leave it alone, NEXT..."
#         end
#       end
#     end
#   end
# end


namespace :chatgpt do
  @about_us = "You are writing content for a website selling creative teambuilding related events. 
    It primarily sells virtual & hybrid teambuilding events to large companies although it also sells in-person events as well in large cities. It does not sell to individuals."

  desc "Export Categories to Swell"
  task clean_adventure_text: :environment do
    client = OpenAI::Client.new
    adventures =  Adventure.all.published
    adventures.each_with_index do |adventure, index|
      puts "Cleaning #{adventure.title}...".green
      word_count = adventure.content.to_plain_text.split.count
      if word_count < 150
        puts "Adventure #{adventure.title} has #{word_count} (#{index + 1} of #{adventures.count})".green
        full_content = ""

        response = client.chat(
          parameters: {
            model: "gpt-4",
            messages: [
              # Add inperson or virtual
              # Add number of people
              # Add brand
              { role: "system", content: @about_us } #this gives context to the AI,
              { role: "system", content: "This for an event titled: '#{adventure.title}' in the context of the category of: #{adventure.primary_category.title}" },
              { role: "system", content: "The output should be HTML using only starting and ending div tags and double <br><br> at the end of paragraphs" },
              { role: "user", content: "Can you expand this event description into 2 to 3 complete paragraphs?"},
              { role: "user", content: "It should be more between 120 to 180 words in length and without headings"},
              { role: "user", content: adventure.description},
              { role: "user", content: adventure.long_description.to_plain_text},
            ],
            max_tokens: 350,
            top_p: 0.95,
            temperature: 0.7,
            stream: proc do |chunk, _bytesize|
              content_chunk = chunk.dig("choices", 0, "delta", "content").to_s
              print content_chunk
              full_content += content_chunk
            end
          }
        )
        adventure.content = full_content
        adventure.save!

      end
    end
  end

  desc "Export FAQ to Swell"
  task create_adventure_faqs: :environment do
    client = OpenAI::Client.new
    adventures =  Adventure.all.published
    adventures.each_with_index do |adventure, index|
      if adventure.faq.blank?
        puts "Adventure #{adventure.title} (#{index + 1} of #{adventures.count})".green
        response_content = ""
        response = client.chat(
          parameters: {
            model: "gpt-4",
            messages: [
              { role: "system", content: @about_us }
              { role: "system", content: "Please format the response as 'Q: [Question]' followed by 'A: [Answer]'." },
              { role: "system", content: "This is for an event titled: '#{adventure.title}' in the context of the category of: #{adventure.primary_category.title}" },
              { role: "user", content: "Generate a minimum of 3 and upto 5 FAQ questions and answers that would be appropriate for this event. Start with the question 'How it works?'"},
              { role: "user", content: "Always start with the first question 'How it works?'"},
              { role: "user", content: "Ensure questions are between 3 and 12 words in length"},
              { role: "user", content: "Ensure answers are between 10 and 30 words in length"},
              { role: "user", content: adventure.description},
              { role: "user", content: adventure.long_description.to_plain_text},
              { role: "user", content: adventure.content.to_plain_text},
            ],
            max_tokens: 250,
            top_p: 0.95,
            temperature: 0.7,
            stream: proc do |chunk, _bytesize|
              content_chunk = chunk.dig("choices", 0, "delta", "content").to_s
              print content_chunk
              response_content += content_chunk
            end
          }
        )
        # Split the response content into lines
        lines = response_content.strip.split("\n")
        # Initialize an empty hash to store FAQs
        faqs_hash = {}
        lines.each_with_index do |line, i|
          # If the line starts with "Q:" it's a question
          if line.start_with?("Q:")
            question = line.gsub("Q:", "").strip
            # Check if the next line starts with "A:" and is an answer
            if lines[i + 1] && lines[i + 1].start_with?("A:")
              answer = lines[i + 1].gsub("A:", "").strip
              faqs_hash[question] = answer
            end
          end
        end
        # Save the FAQs hash directly into the faq jsonb column
        adventure.faq = faqs_hash
        adventure.save!
      end
    end
  end
end