165 lines
4.4 KiB
Ruby
165 lines
4.4 KiB
Ruby
# frozen_string_literal: true
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module DiscourseAi
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module AiHelper
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class LlmPrompt
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def available_prompts(name_filter: nil)
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cp = CompletionPrompt
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cp = cp.where(name: name_filter) if name_filter.present?
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cp
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.where(provider: enabled_provider)
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.where(enabled: true)
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.map do |prompt|
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translation =
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I18n.t("discourse_ai.ai_helper.prompts.#{prompt.name}", default: nil) ||
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prompt.translated_name || prompt.name
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{
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id: prompt.id,
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name: prompt.name,
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translated_name: translation,
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prompt_type: prompt.prompt_type,
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icon: icon_map(prompt.name),
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}
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end
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end
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def generate_and_send_prompt(prompt, params)
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case enabled_provider
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when "openai"
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openai_call(prompt, params)
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when "anthropic"
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anthropic_call(prompt, params)
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when "huggingface"
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huggingface_call(prompt, params)
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end
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end
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def enabled_provider
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case SiteSetting.ai_helper_model
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when /gpt/
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"openai"
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when /claude/
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"anthropic"
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else
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"huggingface"
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end
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end
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private
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def icon_map(name)
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case name
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when "translate"
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"language"
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when "generate_titles"
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"heading"
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when "proofread"
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"spell-check"
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when "markdown_table"
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"table"
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when "tone"
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"microphone"
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when "custom_prompt"
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"comment"
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when "rewrite"
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"pen"
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else
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nil
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end
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end
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def generate_diff(text, suggestion)
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cooked_text = PrettyText.cook(text)
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cooked_suggestion = PrettyText.cook(suggestion)
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DiscourseDiff.new(cooked_text, cooked_suggestion).inline_html
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end
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def parse_content(prompt, content)
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return "" if content.blank?
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case enabled_provider
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when "openai"
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return content.strip if !prompt.list?
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content.gsub("\"", "").gsub(/\d./, "").split("\n").map(&:strip)
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when "anthropic"
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parse_antropic_content(prompt, content)
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when "huggingface"
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return [content.strip.delete_prefix('"').delete_suffix('"')] if !prompt.list?
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content.gsub("\"", "").gsub(/\d./, "").split("\n").map(&:strip)
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end
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end
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def openai_call(prompt, params)
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result = { type: prompt.prompt_type }
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messages = prompt.messages_with_user_input(params)
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result[:suggestions] = DiscourseAi::Inference::OpenAiCompletions
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.perform!(messages, SiteSetting.ai_helper_model)
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.dig(:choices)
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.to_a
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.flat_map { |choice| parse_content(prompt, choice.dig(:message, :content).to_s) }
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.compact_blank
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result[:diff] = generate_diff(params[:text], result[:suggestions].first) if prompt.diff?
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result
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end
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def anthropic_call(prompt, params)
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result = { type: prompt.prompt_type }
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filled_message = prompt.messages_with_user_input(params)
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message =
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filled_message.map { |msg| "#{msg["role"]}: #{msg["content"]}" }.join("\n\n") +
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"Assistant:"
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response = DiscourseAi::Inference::AnthropicCompletions.perform!(message)
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result[:suggestions] = parse_content(prompt, response.dig(:completion))
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result[:diff] = generate_diff(params[:text], result[:suggestions].first) if prompt.diff?
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result
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end
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def huggingface_call(prompt, params)
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result = { type: prompt.prompt_type }
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message = prompt.messages_with_user_input(params)
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response =
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DiscourseAi::Inference::HuggingFaceTextGeneration.perform!(
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message,
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SiteSetting.ai_helper_model,
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)
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result[:suggestions] = parse_content(prompt, response.dig(:generated_text))
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result[:diff] = generate_diff(params[:text], result[:suggestions].first) if prompt.diff?
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result
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end
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def parse_antropic_content(prompt, content)
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if prompt.list?
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suggestions = Nokogiri::HTML5.fragment(content).search("ai").map(&:text)
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if suggestions.length > 1
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suggestions
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else
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suggestions.first.split("\n").map(&:strip)
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end
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else
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[Nokogiri::HTML5.fragment(content).at("ai").text]
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end
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end
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end
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end
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end
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