mirror of
https://github.com/discourse/discourse-ai.git
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Previous to this change we relied on explicit loading for a files in Discourse AI. This had a few downsides: - Busywork whenever you add a file (an extra require relative) - We were not keeping to conventions internally ... some places were OpenAI others are OpenAi - Autoloader did not work which lead to lots of full application broken reloads when developing. This moves all of DiscourseAI into a Zeitwerk compatible structure. It also leaves some minimal amount of manual loading (automation - which is loading into an existing namespace that may or may not be there) To avoid needing /lib/discourse_ai/... we mount a namespace thus we are able to keep /lib pointed at ::DiscourseAi Various files were renamed to get around zeitwerk rules and minimize usage of custom inflections Though we can get custom inflections to work it is not worth it, will require a Discourse core patch which means we create a hard dependency.
169 lines
5.3 KiB
Ruby
169 lines
5.3 KiB
Ruby
# frozen_string_literal: true
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if defined?(DiscourseAutomation)
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module DiscourseAutomation::LlmTriage
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def self.handle(
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post:,
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model:,
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search_for_text:,
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system_prompt:,
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category_id: nil,
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tags: nil,
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canned_reply: nil,
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canned_reply_user: nil,
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hide_topic: nil
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)
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if category_id.blank? && tags.blank? && canned_reply.blank? && hide_topic.blank?
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raise ArgumentError, "llm_triage: no action specified!"
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end
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post_template = +""
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post_template << "title: #{post.topic.title}\n"
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post_template << "#{post.raw}"
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filled_system_prompt = system_prompt.sub("%%POST%%", post_template)
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if filled_system_prompt == system_prompt
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raise ArgumentError, "llm_triage: system_prompt does not contain %%POST%% placeholder"
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end
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result = nil
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if model == "claude-2"
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# allowing double + 10 tokens
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# technically maybe just token count is fine, but this will allow for more creative bad responses
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result =
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DiscourseAi::Inference::AnthropicCompletions.perform!(
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filled_system_prompt,
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model,
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temperature: 0,
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max_tokens:
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DiscourseAi::Tokenizer::AnthropicTokenizer.tokenize(search_for_text).length * 2 + 10,
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).dig(:completion)
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else
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result =
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DiscourseAi::Inference::OpenAiCompletions.perform!(
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[{ :role => "system", "content" => filled_system_prompt }],
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model,
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temperature: 0,
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max_tokens:
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DiscourseAi::Tokenizer::OpenAiTokenizer.tokenize(search_for_text).length * 2 + 10,
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).dig(:choices, 0, :message, :content)
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end
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if result.strip == search_for_text.strip
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user = User.find_by_username(canned_reply_user) if canned_reply_user.present?
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user = user || Discourse.system_user
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if canned_reply.present?
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PostCreator.create!(
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user,
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topic_id: post.topic_id,
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raw: canned_reply,
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reply_to_post_number: post.post_number,
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skip_validations: true,
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)
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end
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changes = {}
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changes[:category_id] = category_id if category_id.present?
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changes[:tags] = tags if SiteSetting.tagging_enabled? && tags.present?
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if changes.present?
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first_post = post.topic.posts.where(post_number: 1).first
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changes[:bypass_bump] = true
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changes[:skip_validations] = true
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first_post.revise(Discourse.system_user, changes)
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end
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post.topic.update!(visible: false) if hide_topic
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end
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end
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end
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DiscourseAutomation::Scriptable::LLM_TRIAGE = "llm_triage"
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AVAILABLE_MODELS = [
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{
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id: "gpt-4",
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name:
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"discourse_automation.scriptables.#{DiscourseAutomation::Scriptable::LLM_TRIAGE}.models.gpt_4",
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},
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{
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id: "gpt-3-5-turbo",
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name:
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"discourse_automation.scriptables.#{DiscourseAutomation::Scriptable::LLM_TRIAGE}.models.gpt_3_5_turbo",
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},
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{
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id: "claude-2",
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name:
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"discourse_automation.scriptables.#{DiscourseAutomation::Scriptable::LLM_TRIAGE}.models.claude_2",
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},
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]
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DiscourseAutomation::Scriptable.add(DiscourseAutomation::Scriptable::LLM_TRIAGE) do
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version 1
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run_in_background
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placeholder :post
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triggerables %i[post_created_edited]
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field :system_prompt,
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component: :message,
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required: true,
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validator: ->(input) do
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if !input.include?("%%POST%%")
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I18n.t(
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"discourse_automation.scriptables.#{DiscourseAutomation::Scriptable::LLM_TRIAGE}.system_prompt_missing_post_placeholder",
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)
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end
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end,
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accepts_placeholders: true
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field :search_for_text, component: :text, required: true
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field :model, component: :choices, required: true, extra: { content: AVAILABLE_MODELS }
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field :category, component: :category
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field :tags, component: :tags
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field :hide_topic, component: :boolean
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field :canned_reply, component: :message
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field :canned_reply_user, component: :user
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script do |context, fields, automation|
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post = context["post"]
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system_prompt = fields["system_prompt"]["value"]
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search_for_text = fields["search_for_text"]["value"]
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model = fields["model"]["value"]
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if !%w[gpt-4 gpt-3-5-turbo claude-2].include?(model)
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Rails.logger.warn("llm_triage: model #{model} is not supported")
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next
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end
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category_id = fields.dig("category", "value")
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tags = fields.dig("tags", "value")
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hide_topic = fields.dig("hide_topic", "value")
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canned_reply = fields.dig("canned_reply", "value")
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canned_reply_user = fields.dig("canned_reply_user", "value")
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if post.raw.strip == canned_reply.to_s.strip
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# nothing to do if we already replied
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next
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end
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begin
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DiscourseAutomation::LlmTriage.handle(
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post: post,
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model: model,
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search_for_text: search_for_text,
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system_prompt: system_prompt,
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category_id: category_id,
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tags: tags,
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canned_reply: canned_reply,
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canned_reply_user: canned_reply_user,
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hide_topic: hide_topic,
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)
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rescue => e
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Discourse.warn_exception(e, message: "llm_triage: failed to run inference")
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end
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end
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end
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end
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