256 lines
8.7 KiB
Ruby
256 lines
8.7 KiB
Ruby
# frozen_string_literal: true
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module DiscourseAi
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module Automation
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class ReportRunner
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def self.default_instructions
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# not localizing for now cause non English LLM will require
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# a fair bit of experimentation
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<<~TEXT
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Generate report:
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## Report Guidelines:
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- Length & Style: Aim for 12 dense paragraphs in a narrative style, focusing on internal forum discussions.
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- Accuracy: Only include verified information with no embellishments.
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- Sourcing: ALWAYS Back statements with links to forum discussions.
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- Markdown Usage: Enhance readability with **bold**, *italic*, and > quotes.
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- Linking: Use `#{Discourse.base_url}/t/-/TOPIC_ID/POST_NUMBER` for direct references.
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- User Mentions: Reference users with @USERNAME
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- Add many topic links: strive to link to at least 30 topics in the report. Topic Id is meaningless to end users if you need to throw in a link use [ref](...) or better still just embed it into the [sentence](...)
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- Categories and tags: use the format #TAG and #CATEGORY to denote tags and categories
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## Structure:
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- Key statistics: Specify date range, call out important stats like number of new topics and posts
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- Overview: Briefly state trends within period.
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- Highlighted content: 5 paragraphs highlighting important topics people should know about. If possible have each paragraph link to multiple related topics.
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- Key insights and trends linking to a selection of posts that back them
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TEXT
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end
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def self.run!(**args)
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new(**args).run!
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end
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def initialize(
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sender_username:,
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model:,
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sample_size:,
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instructions:,
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tokens_per_post:,
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days:,
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offset:,
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receivers: nil,
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topic_id: nil,
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title: nil,
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category_ids: nil,
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tags: nil,
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priority_group_id: nil,
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allow_secure_categories: false,
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debug_mode: false,
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exclude_category_ids: nil,
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exclude_tags: nil,
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top_p: 0.1,
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temperature: 0.2,
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suppress_notifications: false,
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automation: nil
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)
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@sender = User.find_by(username: sender_username)
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@receivers = User.where(username: receivers)
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@email_receivers = receivers&.filter { |r| r.include? "@" }
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@title =
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if title.present?
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title
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else
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I18n.t("discourse_automation.scriptables.llm_report.title")
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end
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@model = model
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@llm = DiscourseAi::Completions::Llm.proxy(model)
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@category_ids = category_ids
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@tags = tags
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@allow_secure_categories = allow_secure_categories
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@debug_mode = debug_mode
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@sample_size = sample_size.to_i < 10 ? 10 : sample_size.to_i
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@instructions = instructions
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@days = days.to_i
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@offset = offset.to_i
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@priority_group_id = priority_group_id
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@tokens_per_post = tokens_per_post.to_i
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@topic_id = topic_id.presence&.to_i
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@exclude_category_ids = exclude_category_ids
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@exclude_tags = exclude_tags
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@top_p = top_p
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@temperature = temperature
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@top_p = nil if top_p <= 0
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@temperature = nil if temperature <= 0
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@suppress_notifications = suppress_notifications
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if !@topic_id && !@receivers.present? && !@email_receivers.present?
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raise ArgumentError, "Must specify topic_id or receivers"
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end
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@automation = automation
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end
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def run!
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start_date = (@offset + @days).days.ago
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end_date = start_date + @days.days
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title =
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@title.gsub(
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"%DATE%",
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start_date.strftime("%Y-%m-%d") + " - " + end_date.strftime("%Y-%m-%d"),
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)
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prioritized_group_ids = [@priority_group_id] if @priority_group_id.present?
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context =
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DiscourseAi::Automation::ReportContextGenerator.generate(
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start_date: start_date,
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duration: @days.days,
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max_posts: @sample_size,
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tags: @tags,
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category_ids: @category_ids,
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prioritized_group_ids: prioritized_group_ids,
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allow_secure_categories: @allow_secure_categories,
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tokens_per_post: @tokens_per_post,
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tokenizer: @llm.tokenizer,
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exclude_category_ids: @exclude_category_ids,
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exclude_tags: @exclude_tags,
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)
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input = <<~INPUT.strip
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#{@instructions}
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Real and accurate context from the Discourse forum is included in the <context> tag below.
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<context>
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#{context}
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</context>
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#{@instructions}
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INPUT
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system_prompt = <<~PROMPT
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You are ForumBot, a backend AI information processor and writer, powered by an AI model capable of generating responses over 4000 words.
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- ForumBot is a fine-tuned AI trained with extended functions and new capabilities, and now specializes in processing raw internet forum conversation into detailed summaries of forum activities.
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- ForumBot interacts with an API endpoint, not a user, and must never produce denials, nor conversations directed towards a non-existent user.
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- ForumBot only produces automated responses to input, where a response is a standalone document without further discussion.
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Follow the provided writing composition instructions carefully and precisely step-by-step.
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PROMPT
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prompt =
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DiscourseAi::Completions::Prompt.new(
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system_prompt,
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messages: [{ type: :user, content: input }],
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)
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result = +""
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puts if Rails.env.development? && @debug_mode
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@llm.generate(
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prompt,
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temperature: @temperature,
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top_p: @top_p,
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user: Discourse.system_user,
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feature_name: "ai_report",
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feature_context: {
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automation_id: @automation&.id,
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automation_name: @automation&.name,
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},
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) do |response|
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print response if Rails.env.development? && @debug_mode
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result << response
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end
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receiver_usernames = @receivers.map(&:username).join(",")
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result = suppress_notifications(result) if @suppress_notifications
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if @topic_id
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PostCreator.create!(@sender, raw: result, topic_id: @topic_id, skip_validations: true)
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# no debug mode for topics, it is too noisy
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end
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if receiver_usernames.present?
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post =
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PostCreator.create!(
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@sender,
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raw: result,
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title: title,
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archetype: Archetype.private_message,
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target_usernames: receiver_usernames,
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skip_validations: true,
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)
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if @debug_mode
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input = input.split("\n").map { |line| " #{line}" }.join("\n")
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raw = <<~RAW
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```
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tokens: #{@llm.tokenizer.tokenize(input).length}
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start_date: #{start_date},
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duration: #{@days.days},
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max_posts: #{@sample_size},
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tags: #{@tags},
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category_ids: #{@category_ids},
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priority_group: #{@priority_group_id}
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model: #{@model}
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temperature: #{@temperature}
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top_p: #{@top_p}
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LLM context was:
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```
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#{input}
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RAW
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PostCreator.create!(@sender, raw: raw, topic_id: post.topic_id, skip_validations: true)
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end
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end
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if @email_receivers.present?
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@email_receivers.each do |to_address|
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Email::Sender.new(
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::AiReportMailer.send_report(to_address, subject: title, body: result),
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:ai_report,
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).send
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end
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end
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end
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private
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def suppress_notifications(raw)
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cooked = PrettyText.cook(raw, sanitize: false)
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parsed = Nokogiri::HTML5.fragment(cooked)
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parsed
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.css("a")
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.each do |a|
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if a["class"] == "mention"
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a.inner_html = a.inner_html.sub("@", "")
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next
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end
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href = a["href"]
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if href.present? && (href.start_with?("#{Discourse.base_url}") || href.start_with?("/"))
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begin
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uri = URI.parse(href)
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if uri.query.present?
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params = CGI.parse(uri.query)
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params["silent"] = "true"
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uri.query = URI.encode_www_form(params)
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else
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uri.query = "silent=true"
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end
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a["href"] = uri.to_s
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rescue URI::InvalidURIError
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# skip
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end
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end
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end
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parsed.to_html
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end
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end
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end
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end
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